Note: Descriptions are shown in the official language in which they were submitted.
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SENSOR SYSTEMS AND METHODS FOR CHARACTERIZING HEALTH
CONDITIONS
CROSS-REFERENCE
[01] This application claims the benefit of U.S. Provisional Patent
Application Serial No. US 63/067,179
filed August 18, 2020; U.S. Provisional Patent Application Serial No.
63/075,056 filed September 4, 2020; U.S.
Provisional Patent Application Serial No. U.S. Provisional Patent Application
Serial No. 63/075,059 filed
September 4, 2020õ U.S. Provisional Patent Application Serial No. 17/096,806
filed November 12, 2020,
PCT/IB2021/053919 filed May 8, 2021; and U.S. Provisional Patent Application
Serial No. 63/068,915 filed
August 21, 2020. The contents of the aforementioned applications are
incorporated by reference herein in their
entirety.
TECHNICAL FIELD
[02] This invention relates generally to the field of monitoring and
diagnosis, such as for identifying a health
condition or other physical condition of a subject using active and/or passive
sensing techniques.
BACKGROUND
[03] Traditionally, medical care practitioners utilize a suite of
instruments to help assess biological
characteristics of a patient, with each instrument specialized for a
particular biometric or class of biometrics.
However, the array of instruments required for a holistic and comprehensive
assessment of a patient leads to
challenges such as greater complexity, steeper learning curves for proper use,
greater cost, and relative lack of
portability and data interoperability.
[041 Furthermore, some conventional instruments have limited
functionality that contribute to an incomplete
picture of patient health. For example, medical care practitioners have
traditionally used tools such as
stethoscopes to observe audible body sounds of a patient, such as those
generated by the heart, hmgs, and
gastrointestinal system. However, conventional stethoscopes are unable to help
a medical care practitioner
observe certain cardiac, respiratory, and/or digestive related information
encoded in various low/high frequency
(within and beyond the limit of human threshold of audibility) low amplitude
inaudible signals. Furthermore, it
is not currently well-understood how to analyze such signals to assess patient
health. Thus, using conventional
technology, low/high frequency (within and beyond the limit of human threshold
of audibility), low amplitude
indicators of patient health are neither detected nor considered in
conventional medical practice, leading to non-
comprehensive diagnostic picture of a patient.
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[05] Furtherinore, conventional stethoscopes require contact with the skin
of the patient for adequate signal
detection, and thereby have limited uses when, for various reasons such as
contamination risk, modesty, or
exigency, signal detection must occur through clothing.
[06] Accordingly, there is a need for a new and improved sensor platform
for characterizing one or more
health and other physical conditions of a subject.
SUMMARY
[07] Generally, in some variations, the present technology provides systems
comprising a sensor platform.
The sensor platform may include a sensing device such as a vibroacoustic
sensor module including one or more
sensors configured to detect a vibroacoustic signal, a signal processing
system configured to extract, from the
detected vibroacoustic signal, a vibroacoustic signal component originating
from a subject, and at least one
processor configured to characterize a bodily condition of the subject based
at least in part on the extracted
vibroacoustic signal component using, for example, a machine learning model.
In some variations, the bodily
condition of a subject may include a health condition of a subject. For
example, the signal processing system
may be configured to extract a biological vibroacoustic signal component
originating from a living subject, and
at least one processor may be configured to characterize a health or other
bodily condition of the subject based
at least in part on the extracted vibroacoustic biological signal component.
Additionally or alternatively, the
bodily condition of a subject may include another suitable physical condition
(e.g., structural condition) of a
living or nonliving subject.
[08] Additionally, in some variations, a method for characterizing a bodily
condition may include detecting
a periodic or aperiodic vibroacoustic signal with a vibroacoustic sensor
module, the vibroacoustic sensor module
comprising a plurality of sensors, extracting, from the detected vibroacoustic
signal, a vibroacoustic signal
component originating from a subject, and characterizing a bodily condition of
the subject based at least in part
on the extracted vibroacoustic signal component using a machine learning
model. In some variations, the bodily
condition of a subject may include a health condition of a subject. For
example, the method may include
extracting a biological vibroacoustic signal component from a vibroacoustic
signal originating from a living
subject, and characterizing a health condition of the subject based at least
in part on the extracted biological
vibroacoustic signal component using a machine learning model. Tn other
embodiments, the method will not
use machine learning but will use interpretability of data. Additionally or
alternatively, the bodily condition of
a subject may include another suitable physical condition (e.g., structural
condition) of a living or nonliving
subject.
[09] Furthermore, in some variations, a vibroacoustic sensor module may
include one or more sensors
configured to detect a vibroacoustic signal, and one or more deflecting
structures interfacing with one or more
of the sensors, wherein the vibroacoustic sensor module has a bandwidthranging
from about 0.01 Hz to at least
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about 160 kHz, or from about 0.01 Hz to at least about 50 kHz, with low to
very low amplitudes of the
oscillations between 0.01-50 i.un, and vibrations of the skin and
tracheobronchial tree at accelerations of around
10'in. s to large motions of the entire body at about 0.1-50
[10] Advantageously, according to certain variations, there are provided
systems and methods for diagnosing
or monitoring bodily conditions of subjects remotely in a non-invasive manner.
Direct skin contact is not
required and variants of the system and method can operate through clothing.
In certain variations, systems and
methods can operate at a distance of about 1 mm, 2 mm, 1 cm, 10 cm, 1 meter, 2
meter, 3 meter, 4 meter, 5
meter, 6 meter, 7 meter, 8 meter, 9 meter or 10-50 meters from the subject.
[11] In certain variations, systems and methods may be well suited for
screening for infectious bodily
conditions, such as with a coronaviridae virus (e.g. Covid-19). Current Covid-
19 screening approaches are either
simple and fast but lack accuracy (e.g., temperature checks), or are accurate
but neither simple nor fast (e.g.,
antibody screening). The gold standard for COVID-19 diagnosis is real-time
reverse-transcriptase polymerase
chain reaction (RT-qPCR), however, RT-PCR testing has been limited in certain
situations to individuals with
overt symptoms, and there arc often significant delays between testing and
result reporting - providing
opportunity for unknown infectious spread. COVID-19 IgG antibody, or serology,
testing can inform on past
infections quickly and cheaply. However, antibodies can take days to weeks to
develop, and the duration of
their effectiveness remains unknown. Other screening approaches, such as those
now being employed by many
schools, daycares, hospitals, and other public spaces, rely on temperature
scans for fever, and self-reported
coughing and fatigue. However, these focus on non-specific symptoms that may
not emerge for days after
infection. Current screening approaches, therefore, are impractical,
inconvenient, do not identify individuals at
early infection stages, cannot discern COVID-19 or COVID-19-associated
multisystem inflammatory syndrome
in children (MIS-C), and do not consider common comorbidities, including
influenza and pneumonia,
respiratory failure, hypertension, diabetes, and cardiopulmonary dysfunction
that exacerbates disease trajectory,
and outcomes.
[l 21 in the context of the present specification, unless expressly
provided otherwise, a bodily condition may
refer to, but is not limited to, one or more of a viral infection in a
subject, a bacterial infection in a subject, a
cognitive state of the subject, a reportable disease, fracture, tear,
embolism, clot, swelling, occlusion, prolapse,
hernia, dissection, infarct, stenosis, hematoma, edema, contusion, osteopenia
and presence of a foreign body in
the subject such as an improvised explosive device (IED), surgically implanted
improvised explosive device
(SI1ED), and/or body cavity bomb (BCB). Examples of viral infections include
but are not limited to infections
of coronaviridae (e.g.COVID-19, SARS). Reportable diseases are diseases
considered to be of great public
health importance. In the United States, local, state, and national agencies
(for example, county and state health
departments or the United States Centers for Disease Control and Prevention)
require that these diseases be
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reported when they are diagnosed by doctors or laboratories. Diseases
reportable to the CDC include: Anthrax,
Arboviral diseases (diseases caused by viruses spread by mosquitoes,
sandflies, ticks, etc.) such as West Nile
virus, eastern and western equine encephalitis, Babe siosis, Botulism,
Brucellosis, Campylobacteriosis,
Chancroid, Chickenpox, Chlamydia, Cholera, Coccidioidomycosis,
Cryptosporidiosis, Cyclosporiasis, Dengue
virus infections, Diphtheria, Ebola, Ehrlichiosis, Foodbornc disease outbreak,
Giardiasis. Gonorrhea,
Haemophilus influenza, invasive disease, Hantavirus pulmonary syndrome,
Hemolytic uremic syndrome, post-
diarrheal, Hepatitis A, Hepatitis B, Hepatitis C, HIV infection, Influenza-
related infant deaths, Invasive
pneumococcal disease, elevated blood levels of lead (Pb), copper (Cu), mercury
(Hg) and other metals,
Legionnaire disease (legionellosis), Leprosy, Leptospirosis, Listeriosis, Lyme
disease, Malaria, Measles,
Meningitis (meningococcal disease), Mumps, Novel influenza A virus infections,
Pertussis, Pesticide-related
illnesses and injuries, Plague, Poliomyelitis, Poliovirus infection,
nonparalytic, Psittacosis, Q-fever, Rabies
(human and animal cases), Rubella (including congenital syndrome), Salmonella
paratyphi and typhi infections,
Salmonellosis, Severe acute respiratory syndrome-associated coronavirus
disease, Shiga toxin-producing
Escherichia coli (STEC), Shigellosis, Smallpox, Syphilis, including congenital
syphilis, Tetanus, Toxic shock
syndrome (other than streptococcal), Trichincllosis, Tuberculosis, Tularemia,
Typhoid fever, Vancomycin
intermediate Staphylococcus aurcus (VISA), Vancomycin resistant Staphylococcus
aurcus (VRSA), Vibriosis,
Viral hemorrhagic fever (including Ebola virus, Lassa virus, among others),
Waterborne disease outbreak,
Yellow fever, Zika virus disease and infection (including congenital).
[13] Nearly all diseases affect livestock, poultry, fishes and other
animals and adversely impact the quality
and quantity of food and other products, such as hides and skins, bones,
fibers, wool and animal draft power for
tilling, transport and traction. The reduction in animal production,
productivity and profitability due to
transboundary animal diseases (TADs) affect human livelihood. In the present
scenario of fast-increasing
globalization. TADs represent a serious threat to the economy and welfare of
the public and affected nations as
they drastically reduce production and productivity; disrupt trade and travel
and local and national economies;
and also threaten human health through inferior food quality and zoonotic
diseases/infections. TADs have
become of great concern due to the risk for national security on account of
their economic significance, zoonotic
nature and ever-growing threat of newer TADs in future. Examples of diseases
affecting animals and which
embodiments of the present technology relate include arbovirus, avian
influenza, B virus, brucellosis,
campylobacteriosis, cat scratch disease, cryptococcosis, cyanobacticra,
cscherichia coli, fish tank granuloma,
giardiasis, hantavirus, histoplasmosis, leptospirosis, listeriosis, lyme
disease, lymphocytic choriomeningitis,
MRSA, plague, psittacosis, Q fever (caused by coxielle burnetti bacteria),
rabies, racoon roundworm, rat bite
fever, ringworm, round worni, salmonellosis, tick-borne relapsing fever,
toxoplasmosis, tularemia, valley fever
(coccidioidomycosis), west nile virus, yellow fever, zika virus. In some
embodiments, the present technology
can operate through fur, mud, dung or other obstacles normally found in animal
facilities.
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[14] A rapid, accurate, sensitive and specific, non-invasive, readily
scalable, TADs mass screening test. Such
a test should safely manage and not become the bottleneck for faster trade,
new trade routes, globalization,
intensive animal production to meet the rising demand for animal protein,
impact of changes in forest ecology,
effect of climate change, global warming and microbial evolution, influences
of increased conflicts and unrest.
[15] From one aspect, there is provided a sensing system for detecting a
vibroacoustic signal, the sensing
system comprising: a sensing device comprising: a vibracoustic sensor module
for detecting vibroacoustic
signals, the vibroacoustic sensor module comprising: a voice coil component
comprising a coil holder
supporting wire windings; a magnet component comprising a magnet supported by
a frame (also referred to as
magnet housing), the magnet having a magnet gap configured to receive at least
a portion of the voice coil
component in a spaced and moveable manner; a connector connecting the voice
coil component to the magnet
component, the connector being compliant and permitting relative movement of
the voice coil component and
the magnet component; a diaphragm configured to induce a movement of the voice
coil component in the
magnet gap responsive to incident acoustic waves; a housing for retaining the
vibroacoustic sensor module,
wherein the sensing device is a hand-held device, the housing having a handle
end and a sensor end, the sensor
end having a sensor end surface with an opening defined therethrough, the
vibracoustic sensor module
positioned such that at least a portion of the diaphragm of the vibroacoustic
sensor extends across the opening.
[16] In certain embodiments, the sensing system further comprises a
processor of a computer system,
operatively communicable with the sensing device, the processor configured to
execute a method for
characterizing a bodily condition of a subject based at least in part on at
least a portion of the detected
vibroacoustic signal using a trained machine learning model. The processor may
be configured to execute a
method for characterizing the bodily condition using one or more combinations
of the detected vibroacoustic
signal and other signals obtained from other sensors. In certain embodiments,
the vibroacoustic sensor module
is configured to detect vibroacoustic signals having a bandwidth ranging from
about 0.01 Hz to about 160 kHz.
In certain embodiments, the detected vibroacoustic signal comprises: a first
vibroacoustic signal component
which originates from the subject, and a second vibroacoustic signal component
which does not originate from
the subject, the processor being configured to extract the first vibroacoustic
signal component from the detected
vibroacoustic signal; and to characterize the bodily condition of the subject
based on the first vibroacoustic
signal component and the trained machine learning model. In certain
embodiments, the processor is configured
to extract biological vibroacoustic signals from the first vibroacoustic
signal component, the detected
vibroacoustic signal having been detected through remote contact with the
subject, through clothed contact with
the subject, or through direct skin contact with the subject. In certain
embodiments, the sensing device further
comprising one or both of: (a) an electronics component, housed in the
housing, and connected to the voice coil
component configured to convert an induced current in the windings from the
acoustic waves to the detected
vibroacoustic signal; and (b) a power source, housed in the housing, connected
to one or both of the electronics
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component and the voice coil component; and (c) a wired or wireless
communication module configured to
communicate one or more of the detected vibroacoustic signal, an extracted
first vibroacoustic signal
component, and the characterization of the bodily condition to the processor
or to another processor. In certain
embodiments, the sensing device further comprises an Inertial Measurement Unit
(IMU) which may comprise
one or both of an accelerometer and a gyroscope. In certain embodiments, the
sensing device further comprising
a bioelectric sensor module for detecting electrical signals from the subject,
the bioelectric sensor module
comprising, at the sensor end surface, at least one capacitive electrode, and
at least one driven right leg (DRL)
electrode for providing a feedback circuit of the capacitive electrodes. In
certain embodiments, the voice coil
component has an impedance of 5 Ohm to 170 Ohm. In certain embodiments, the
connector comprises a
deflecting structure extending radially from the voice coil component and
including apertures formed therein.
The connector may comprise at least two flexure arms extending radially from
the voice coil component, the at
least two flexure arms being spaced from one another to define at least one
aperture therebetween. In certain
embodiments, a mechanical compliance of the connector is in a range of 0.1
mm/N to 5.0 mm/N. In certain
embodiments, the sensing device further comprising an outer cover at the
sensor end for covering one or both
of an interface between the diaphragm and the housing, and the opening at the
sensor end.
[17] From another aspect, there is provided a sensing system for detecting
a vibroacoustic signal, the sensing
system comprising: a sensing device comprising: a vibracoustic sensor module
for detecting vibroacoustic
signals, the vibroacoustic sensor module comprising one or more deflecting
structures: a frame for retaining the
vibroacoustic sensor module in the sensing device, and a diaphragm extending
across at least a portion of the
frame and connected thereto.
[18] From another aspect, there is provided a sensing system for non-
contact determination of a presence or
absence of a condition of a subject, the sensing system comprising: a housing
having a front side, the housing
configured such that at least a part of a body of a subject is spaced from and
faces the front side in use, the
housing configured to house: a vibroacoustic sensor module for sensing
vibroacoustic signals, the vibroacoustic
sensor module for detecting acoustic signals having a bandwidth ranging from
0.01 Hz to 160 kHz and
comprising: a voice coil component comprising a coil holder supporting wire
windings a magnet component
comprising a magnet supported by a magnet housing, the magnet having a magnet
gap configured to receive at
least a portion of the voice coil component in a spaced and moveable manner; a
connector connecting the voice
coil component to the magnet component, the connector being compliant and
permitting relative movement of
the voice coil component; a diaphragm configured to induce a movement of the
voice coil component in the
magnet gap responsive to incident acoustic signals, wherein the diaphragm is
attached to the voice coil
component and the wire windings are spaced from the diaphragm, the
vibroacoustic sensor being positioned in
the housing such that the diaphragm faces the at least a part of a body of the
subject in use. There is also provided
an Echo Doppler sensor module including at least one emitter component and at
least one receiver component.
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The vibroacoustic sensor module and Echo Doppler sensor module being
communicatively connected to a
processor of a computing device having a memory storing executable
instructions that, when executed by the
processor, cause the processor to: receive, from the -vibroacoustic sensor
module, vibroacoustic signal data
corresponding to the subject and collected by the vibroacoustic sensor module;
receive, from the Echo Doppler
sensor module, ultrasound signal data corresponding to the subject and
collected by the Echo Doppler sensor
module; and output, based on the received vibroacoustic signal data and the
ultrasound signal data and using a
trained machine learning model, an indication of the presence or absence of
the condition in the subject.
[19] In certain embodiments, the diaphragm comprises a compliant material.
In certain embodiments, the
sensing system further comprises a frame, housed in the housing, the
vibroacoustic sensor module being
positioned relative to an aperture defined by the frame and connected to the
frame. In certain embodiments, the
vibroacoustic sensor module is connected to the frame by at least one edge of
the diaphragm and by the magnet
housing. The diaphragm may be configured to cover the aperture of the frame.
In certain embodiments, the
sensing system further comprises a back cover covering the aperture of the
frame and spaced from the
diaphragm.
[20] In certain embodiments, the vibroacoustic sensor module is a first
vibroacoustic sensor module, the
sensing system further comprises: a second vibroacoustic sensor module for
sensing vibroacoustic signals, the
vibroacoustic sensor module for detecting acoustic signals having a bandwidth
ranging from 0.01 Hz to 160
kHz and comprising: a voice coil component comprising a coil holder supporting
wire windings; a magnet
component comprising a magnet supported by a magnet housing, the magnet having
a magnet gap configured
to receive at least a portion of the voice coil component in a spaced and
moveable manner; a connector
connecting the voice coil component to the magnet component, the connector
being compliant and permitting
relative movement of the voice coil component; a diaphragm configured to
induce a movement of the voice coil
component in the magnet gap responsive to incident acoustic signals, wherein
the diaphragm is attached to the
voice coil component and the wire windings are spaced from the diaphragm, the
vibroacoustic sensor being
positioned in the housing such that the diaphragm faces the at least a part of
a body of the subject in use; further
comprising a frame, housed in the housing, the first and second vibroacoustic
sensor modules being positioned
relative to an aperture defined by the frame and connected to the frame,
wherein the diaphragm of the first and
second vibroacoustic sensor modules is a same diaphragm which is connected to
the frame to cover the aperture.
[21] In certain embodiments, the vibroacoustic sensor module is a first
vibroacoustic sensor module, the
sensing system further comprises: a second vibroacoustic sensor module for
sensing vibroacoustic signals, the
vibroacoustic sensor module for detecting acoustic signals having a bandwidth
ranging from 0.01 Hz to 160
kHz and comprising: a voice coil component comprising a coil holder supporting
wire windings; a magnet
component comprising a magnet supported by a magnet housing, the magnet having
a magnet gap configured
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to receive at least a portion of the voice coil component in a spaced and
moveable manner; a connector
connecting the voice coil component to the magnet component, the coimector
being compliant and permitting
relative movement of the voice coil component; a diaphragm configured to
induce a movement of the voice coil
component in the magnet gap responsive to incident acoustic signals, wherein
the diaphragm is attached to the
voice coil component and the wire windings arc spaced from the diaphragm, the
vibroacoustic sensor being
positioned in the housing such that the diaphragm faces the at least a part of
a body of the subject in use; a
frame, housed in the housing, the frame defining a first aperture for housing
the first vibroacoustic sensor
module and a second aperture for housing the second vibroacoustic sensor
modules, the diaphragm of the first
and second vibroacoustic sensor modules being connected to the frame. The
first aperture and the second
aperture may be different sizes.
[22] In certain embodiments, the sensing system further comprises an
Inertial Measurement Unit (IMU)
mounted to the diaphragm. In certain embodiments, the sensing system further
comprises a heat sensor module
for sensing a temperature of the at least a part of the body of the subject in
use, and wherein the processor is
configured to: receive, from the heat sensor module, temperature data
corresponding to the subject and collected
by the heat sensor module; and output, based on the received vibroacoustic
signal data, the ultrasound signal
data and the heat sensor module and using a trained machine learning model, an
indication of the presence or
absence of the condition in the subject.
[23] In certain embodiments, the sensing system further comprises a camera
communicatively coupled to
the processor for imaging the at least one body part of the subject and
identifying a predetermined body part,
the processor configured to determine and utilize heat sensor data associated
with that predetermined body part
for determining an indication of the presence or absence of the condition in
the subject.
[24] In certain embodiments, the sensing system further comprises a camera
communicatively coupled to
the processor for imaging the at least one body part of the subject and
identifying a predetermined body part,
the processor configured to cause an adjustment mechanism to adjust a position
of one or both of the Echo
Doppler sensor module and the vibroacoustic sensor module so that at least a
portion of the one or both of the
Echo Doppler sensor module and the vibroacoustic sensor module are aligned
with the predetermined body part.
[25] In certain embodiments, the adjustment mechanism comprises an elongate
shaft and a movable member
mounted on the elongate shaft, the movable member being connected to the at
least a portion of the one or both
of the Echo Doppler sensor module and the vibroacoustic sensor module.
[26] In certain embodiments, the sensing system further comprises an
environmental sensor configured to
detect one or more of an ambient temperature, a barometric pressure, an
altitude, ambient noise, and ambient
light; and wherein the processor is configured to receive, from the
environmental sensor, the one or inure of the
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ambient temperature, the barometric pressure, the altitude, the ambient noise,
and the ambient light
corresponding to an environment around the sensing device; and calibrate one
or both of the received
vibroacoustic signal data and the ultrasound signal data based on the one or
more of the ambient temperature,
the barometric pressure, the altitude, the ambient noise, and the ambient
light corresponding to an environment
around the sensing device.
[27] In certain embodiments, a ratio of an inductance and moving mass of
the vibroacoustic sensor module
is at least 6.5 mH per gram at 1 kHz. In certain embodiments, a ratio of a
mechanical compliance of the connector
of the vibroacoustic sensor module and moving mass of the vibroacoustic sensor
module is at least 0.3 mm/N
per gram. in certain embodiments, a ratio of a BL product and moving mass of
the vibroacoustic sensor module
is at least 16 N/Amp per gram. In certain embodiments, the housing is
substantially upright and is configured
to be supported by a wall, a floor or a ceiling. In certain embodiments, the
housing has an arch-like configuration
including at least one substantially upright portion including the front side
and sized so that the subject can stand
under the housing. In certain embodiments, the front side of the housing
includes a display for displaying
information to the subject. From another aspect, there is provided sensing
system for monitoring blood pressure
of a subject, the sensing system comprising: a housing configured to be
positioned on a skin of the subject; a
pressure module housed in the housing and configured to apply pressure to the
skin; a vibroacoustic sensor
module housed in the housing and configured to detect acoustic signals,
responsive to the applied pressure, the
vibroacoustic sensor module comprising: a voice coil component comprising a
coil holder supporting wire
windings; a magnet component comprising a magnet supported by a magnet
housing, the magnet having a
magnet gap configured to receive at least a portion of the voice coil
component in a spaced and moveable
manner; a connector connecting the voice coil component to the magnet
component, the connector being
compliant and permitting relative movement of the voice coil component; a
diaphragm configured to induce a
movement of the voice coil component in the magnet gap responsive to incident
acoustic signals, wherein the
diaphragm is attached to the voice coil component and the wire windings are
spaced from the diaphragm, the
vibroacoustic sensor being positioned in the housing such that the diaphragm
faces the skin of the subject when
the housing is positioned on the skin.
[28] In certain embodiments, the pressure module is communicatively
connected to a processor of a
computing system having a memory storing executable instructions that, when
executed by the processor, cause
the processor to apply the pressure to the skin. In certain embodiments, the
vibroacoustic sensor module is
communicatively connected to a processor of a computing system having a memory
storing executable
instructions that, when executed by the processor, cause the processor to
receive acoustic data from the
vibroacoustic sensor module. In certain embodiments, the sensing system
further comprises the processor of the
computing system, wherein the processor is configured to receive the acoustic
data and to execute a method for
determining the blood pressure of the patient from the acoustic data and
optionally the applied pressure. In
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certain embodiments, the pressure module comprises: a fluid channel network
configured to selectively permit
fluid flow therewith to selectively apply a pressure to the skin of the
subject; a fluid reservoir in fluid
communication with the fluid channel network for supplying fluid to and/or
from the fluid channel network,
and at least one pump for causing the fluid to flow from the fluid reservoir
to and/or from the fluid channel
network. In certain embodiments, the applied pressure to the skin has a
predetermined pressure profile, the
processor being configured to cause the pressure component to create the
predetermined pressure profile,
wherein the predetermined pressure profile corresponds to Korotkoff sounds. In
certain embodiments, the
sensing system further comprises an electric sensor for measuring electric
potential of the skin. In certain
embodiments, the housing is one or more of: a sleeve to be worn over a limb of
the patient, at least one patch to
be applied to the skin of the patient; a band-aid; and a compression bandage.
In certain embodiments, the
pressure module is configured such that pressure is applied to at least one
target area on the skin, wherein the at
least one target area does not extend all the way around a limb of the
subject. In certain embodiments, the
housing is configured to contact at least one target area on the skin, wherein
the at least one target area on the
skin does not extend all the way around a limb of the subject. In certain
embodiments, the sensing system further
comprises one or more of: an optical sensor for obtaining optical data
relating to the skin or components under
the skin; an enviromnental sensor for obtaining data relating to an
environment of the subject, comprising one
or more selected from: ambient temperature, barometric pressure, altitude,
ambient noise, and ambient light. In
certain embodiments, the vibroacoustic sensor module is configured to detect
acoustic signals having a
bandwidth ranging from 0.01 Hz to 160 kHz sensor. In certain embodiments, the
sensing system further
comprises a haptic device associated with a user of the system, the haptic
device communicatively coupled to
the processor, the processor is configured to cause the haptic device to
vibrate with a vibration pattern
corresponding to the determined blood pressure of the subject and optionally
including a functional state of the
subject.
[29] From another aspect, there is provided a sensing system for monitoring
blood pressure of a subject, the
sensing system comprising: a first device comprising a first housing
configured to be positioned on a skin of
the subject at a first location, a first vibroacoustic sensor module housed in
the housing and configured to detect
acoustic signals relating to the subject; a second device comprising a second
housing configured to be positioned
on the skin of the subject at a second location, a second vibroacoustic sensor
module housed in the housing and
configured to detect acoustic signals relating to the subject; and a processor
configured to receive a first set of
data from the first device and a second set of data from the second device and
to determine the blood pressure
of the subject by triangulation.
[30] In certain embodiments, the sensing device further comprises a sensor
(such as a contextual sensor)
configured to measure one or more of: optical data, GPS, motion, humidity,
pressure, ambient temperature,
body temperature, light, sound, radiation, pulse, bioimpedance, skin
conductance, galvanic skin response,
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electrodermal response, and electrodermal activity (which may be
environmental/social determinants of
health data). In certain embodiments, the first device and second device are
arranged to be positioned on the
same or different limbs of the subject. In certain embodiments, one or both of
the first and the second device
further comprises a sensor configured to capture location data relating to a
physical location of the one or both
of the first and the second device. In certain embodiments, the processor is
configured to receive the location
data and calibrate the determined blood pressure according to a difference in
location between the first device
and the second device and an associated approximate expected pressure
differential in blood vessels at the first
location and the second location. In certain embodiments, the sensing device
further comprises a signal
generation device for delivering an electrical signal to the subject remote
from one or both of the first device
and the second device, which may be a biological vibroacoustic, electric
potential, electromagnetic,
electroencephalogram (EEG), electrocardiogram (ECG), electro-oculography
(EOG), surface electromyogram
(sEMG), and/or galvanic skin response (GSR) signal. In certain embodiments,
the first and/or the second
vibroacoustic sensor module comprises a voice coil component comprising a coil
holder supporting wire
windings; a magnet component comprising a magnet supported by a magnet
housing, the magnet having a
magnet gap configured to receive at least a portion of the voice coil
component in a spaced and moveable
manner; a connector connecting the voice coil component to the magnet
component, the connector being
compliant and permitting relative movement of the voice coil component; a
diaphragm configured to induce a
movement of the voice coil component in the magnet gap responsive to incident
acoustic signals, wherein the
diaphragm is attached to the voice coil component and the wire windings are
spaced from the diaphragm, the
vibroacoustic sensor being positioned in the housing such that the diaphragm
faces the skin of the subject when
the housing is positioned on the skin. In certain embodiments, the housing is
one or more of: a sleeve to be worn
over a limb of the patient, at least one patch to be applied to the skin of
the patient; a band-aid; and a compression
bandage. In certain embodiments, the housing is configured to contact at least
one target area on the skin,
wherein the at least one target area on the skin does not extend all the way
around a limb of the subject. In
certain embodiments, the sensing system further comprises one or more of: an
optical sensor for obtaining
optical data relating to the skin or components under the skin; an
environmental sensor for obtaining data
relating to an environment of the subject, comprising one or more selected
from: ambient temperature,
barometric pressure, altitude, ambient noise, and ambient light. In certain
embodiments, the vibroacoustic sensor
module is configured to detect acoustic signals having a bandwidth ranging
from 0.01 Hz to 160 kHz sensor. In
certain embodiments, the sensing system further comprises a haptic device
associated with a user of the system,
the haptic device communicatively coupled to the processor, the processor is
configured to cause the haptic
device to vibrate with a vibration pattern corresponding to the determined
blood pressure of the subject and
optionally including a functional state of the subject.
1311 From another aspect, there is provided a sensing system for
monitoring blood pressure of a subject, the
sensing system comprising: a housing configured to be positioned on a skin of
the subject; a capacitive sensor
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for detecting electric potential signals from the subject; a vibroacoustic
sensor module housed in the housing
and configured to detect acoustic signals, responsive to the applied pressure,
the vibroacoustic sensor module
comprising: a voice coil component comprising a coil holder supporting wire
windings; a magnet component
comprising a magnet supported by a magnet housing, the magnet having a magnet
gap configured to receive at
least a portion of the voice coil component in a spaced and moveable manner; a
connector connecting the voice
coil component to the magnet component, the connector being compliant and
permitting relative movement of
the voice coil component; a diaphragm configured to induce a movement of the
voice coil component in the
magnet gap responsive to incident acoustic signals, wherein the diaphragm is
attached to the voice coil
component and the wire windings are spaced from the diaphragm, the
vibroacoustic sensor being positioned in
the housing such that the diaphragm faces the skin of the subject when the
housing is positioned on the skin. In
certain embodiments, the vibroacoustic sensor module is communicatively
connected to a processor of a
computing system having a memory storing executable instructions that, when
executed by the processor, cause
the processor to receive acoustic data from the vibroacoustic sensor module.
In certain embodiments, the sensing
system further comprising the processor of the computing system, wherein the
processor is configured to receive
the acoustic data and to execute a method for determining the blood pressure
of the patient from the acoustic
data and electric potential data from the capacitive sensor. In certain
embodiments, the housing is one or more
of: a sleeve to be worn over a limb of the patient, at least one patch to be
applied to the skin of the patient; a
band-aid; and a compression bandage. In certain embodiments, the housing is
configured to contact at least one
target area on the skin, wherein the at least one target area on the skin does
not extend all the way around a limb
of the subject. In certain embodiments, the sensing system further comprises
one or more of: an optical sensor
for obtaining optical data relating to the skin or components under the skin;
an environmental sensor for
obtaining data relating to an environment of the subject, comprising one or
more selected from: ambient
temperature, barometric pressure, altitude, ambient noise, and ambient light.
In certain embodiments, the
vibroacoustic sensor module is configured to detect acoustic signals having a
bandwidth ranging from 0.01 Hz
to 160 kHz sensor. In certain embodiments, the sensing system further
comprises a haptic device associated
with a user of the system, the haptic device communicatively coupled to the
processor, the processor is
configured to cause the haptic device to vibrate with a vibration pattern
corresponding to the determined blood
pressure of the subject and optionally including a functional state of the
subject.
[32] In the context of the present specification, tuiless expressly
provided otherwise, by "remote screening"
is meant that the subject does not have direct contact, such as skin contact,
with at least sensor module
components of the present system. Remote screening includes situations in
which certain components of the
system are spaced from the subject. There is no limitation on a distance of
the spacing. Remote screening
includes signal detection over clothing" and/or "through clothing".
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[331 In the context of the present specification, unless expressly
provided otherwise, by animal is meant an
individual animal that is a mammal, bird, or fish. Specifically, mammal refers
to a vertebrate animal that is
human and non-human, which are members of the taxonomic class Mammalia. Non-
exclusive examples of non-
human mammals include companion animals and livestock. Animals in the context
of the present disclosure are
understood to include vertebrates. The term vertebrate in this context is
understood to comprise, for example
fishes, amphibians, reptiles, birds, and mammals including humans. As used
herein, the term "animal" may
refer to a mammal and a non-mammal, such as a bird or fish. In the case of a
mammal, it may be a human or
non-human mammal. Non-human mammals include, but are not limited to, livestock
animals and companion
animals.
[34] In the context of the present specification, unless expressly provided
otherwise, a computer system may
refer, but is not limited to, an "electronic device", an "operating system", a
"communications system", a
"system", a "computer-based system", a "controller unit", a "control device"
and/or any combination thereof
appropriate to the relevant task at hand.
[35] In the context of the present specification, unless expressly provided
otherwise, the expression
"computer-readable medium" and "memory" are intended to include media of any
nature and kind whatsoever,
non-limiting examples of which include RAM, ROM, disks (CD-ROMs, DVDs, floppy
disks, hard disk drives,
etc.), USB keys, flash memory cards, solid state-drives, and tape drives.
[36] in the context of the present specification, a "database" is any
structured collection of data, irrespective
of its particular structure, the database management software, or the computer
hardware on which the data is
stored, implemented or otherwise rendered available for use. A database may
reside on the same hardware as
the process that stores or makes use of the information stored in the database
or it may reside on separate
hardware, such as a dedicated server or plurality of servers.
[37] In the context of the present specification, unless expressly provided
otherwise, the words "first",
second", "third", etc. have been used as adjectives only for the purpose of
allowing for distinction between the
nouns that they modify from one another, and not for the purpose of describing
any particular relationship
between those nouns.
[38] In the context of the present specification, vibroacoustic refers to
vibrations or acoustical signals
propagating through air, biological structures, solids, gases, liquids, or
other fluids. This term also encompasses
the term me chano -acoustic.
[391 In the context of the present specification, the sensing device
may be a sensoriactuator, which can be
considered as a device configured to generate a sensor signal that is a
function of its electrical response to an
electrical input signal and its mechanical response.
13
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[40] Variations of the present technology each have at least one of
the above-mentioned object and/or
aspects, but do not necessarily have all of them. It should be understood that
some aspects of the present
technology that have resulted from attempting to attain the above-mentioned
object may not satisfy this object
and/or may satisfy other objects not specifically recited herein.
[411 Additional and/or alternative features, aspects and advantages
of embodiments of the present
technology will become apparent from the following description, the
accompanying drawings and the appended
claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[42] The patent or application file contains at least one drawing executed
in color. Copies of this patent or
patent application publication with color drawing(s) will be provided by the
Office upon request and payment
of the necessary fee.
[43] FIGS. lA to 1D depict schematic illustrations of a sensor system for
characterizing a bodily condition
of a subject.
[44] FIG. IE illustrates various types of vibroacoustic data across a range
of frequencies, energy
distributions, and amplitudes in relation to the human ear's sensitivity
across the range of frequencies.
[45] FIGS. 1F-1H depict schematic illustrations of various output
interfaces of components of an example
variation of a sensor system for characterizing a bodily condition of a
subject.
[46] FIG. 2 depicts a schematic illustration of an example variation of a
vibroacoustic sensing device for
characterizing a bodily condition of a subject.
[47] FIGS. 3A and 3B depict an assembled view and an exploded view,
respectively, of an example variation
of a sensing device for characterizing a bodily condition of a subject.
[48] FIGS. 4A and 4B depict an assembled view and an exploded view,
respectively, of another example
variation of a sensing device for characterizing a bodily condition of a
subject. FIG. 4C depicts a perspective
view from a sensor end of the sensing device of FIGS. 4A and 4B. FIG. 4D
depicts a cross-section through the
sensing device of FIGS 4Aand 4B with some of the internal components omitted
for clarity. FIG. 4E depicts a
perspective view from a handle end of the sensing device of FIGS. 4A and 4B.
FIG, 4F depicts a close-up
perspective view of the sensor end of the sensing device of FIGS. 4A and 4B
with some of the housing cut-
away for clarity. FIG. 4G depicts a close-up plan view of the sensor end of
the sensing device of FIG. 4F. FIG.
4H depicts a perspective view of another example variation of a sensing device
for characterizing a bodily
condition of a subject. FIG. 41 depicts a close-up plan view of the sensor end
of a variant sensing device to the
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one of FIG. 4G. FIG. 4J depicts a cross-sectional perspective view of a
variant of a voice coil module of the
sensing device showing only a partial view of the housing. FIG. 4K depicts an
exploded view of a variant of the
sensing device and a voice coil module showing the housing has two parts.
[49] FIGS. 5A and 5B depict a perspective cross-sectional view and a cross-
sectional view, respectively, of
a portion of an example variation of a sensing device for characterizing a
bodily condition of a subject. FIGS.
5C and 5D depict upper and lower perspective views, respectively, of an
example variation of a vibroacoustic
sensor module with flexure arms. FIG. 5E depicts a cross-sectional view of the
vibroacoustic sensor module
depicted in FIGS. 5C and 5D. FIG. 5F depicts an exploded view of the
vibroacoustic sensor module depicted in
FIGS. 5C and 5D. FIG. 5G depicts an upper perspective view of the example
variation of a vibroacoustic sensor
module with flexure arms shown in FIG. 5C. FIG. 5H depicts an example
variation of a flex circuit in the
vibroacoustic sensor module depicted in FIG. 5G. FIG. 51 depicts an example
variation of a deflecting structure
with flexure arms in the vibroacoustic sensor module depicted in FIG. 5G.
[50] FIG. 6A depicts a schematic illustration of an example variation of a
vibroacoustic sensor module with
flexure arms. FIG. 6B depicts a schematic illustration of an example variation
of a flex circuit in the
vibroacoustic sensor module depicted in FIG. 6A.
[51] FIGS. 7A and 7B depict cross-sectional views of an example variation
of a vibroacoustic sensor module
with differing clearance distances between a deflecting structure and surface
of a subject.
[52] FIGS. 8A and 8B depict perspective and plan views, respectively, of a
schematic illustration of an
example variation of a vibroacoustic sensor module with flexure arms.
[531 FIGS. 9A and 9B depict upper perspective and lower perspective
views, respectively, of an example
variation of a vibroacoustic sensor module including flexure arms. FIG. 9C
depicts a schematic illustration of
an example variation of a deflecting structure with flexure arms in the
vibroacoustic sensor module depicted in
FIGS. 9A and 9B. FIG. 9D depicts a schematic illustration of an example
variation of a flex circuit in the
vibroacoustic sensor module depicted in FIGS. 9A and 9B.
[54] FIGS. 10A and 10B depict perspective and cross-sectional views,
respectively, of an example variation
of a vibroacoustic sensor module including a membrane and at least one cross-
axis inertial sensor (e.g.,
accelerometer).
[55] FIGS_ 11A and 11B depict cross-sectional and cross-sectional exploded
views, respectively, of an
example variation of a vibroacoustic sensor module including a membrane and at
least one cross-axis inertial
sensor (e.g., pressure sensor). FIGS. 11C-11E depict top, side, and bottom
views of an example variation of a
circuit board with a pressure sensor in the vibroacoustic sensor module
depicted in FIGS_ 11A and 11B.
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[56] FIGS. 12A and 12B depict cross-sectional and cross-sectional exploded
views, respectively, of an
example variation of a vibroacoustic sensor module including a dampening
feature.
[57] FIGS. 13A, 13B, and 13C depict perspective, cross-sectional, and
exploded views, respectively, of an
example variation of a vibroacoustic sensor module including an accelerometer
and a microphone.
[58] FIG. 14 depicts an example variation of a vibroacoustic sensor module
including a handle portion.
[59] FIG. 15 depicts an example variation of a vibroacoustic sensor module
including flexure arms and a
plurality of cross-axis inertial sensors (e.g., accelerometer, pressure
sensor).
[60] FIG. 16A depicts an assembled view of an example variation of a
vibroacoustic sensor module including
a voice coil having one or more spider layers. FIG. 16B is an exploded view of
a vibroacoustic sensor module,
such as the vibroacoustic sensor module of FIG. 16A, and having a single layer
spider. FIG. 16C is an exploded
view of a vibroacoustic sensor module, such as the vibroacoustic sensor module
of FIG. 16A, and having a
double layer spider. FIG. 16D is a perspective view of the example
vibroacoustic sensor module of FIG. 16A
with an outer housing omitted for clarity. FIG. 16E is an exploded view of the
vibroacoustic sensor module of
FIG. 16D.
[61] FIG. 17A and 17B are cross-sectional views of the example
vibroacoustic sensor modules of FIGS. 16A
and 16B, respectively.
[62] FIGS. 18A-18AB are example spiders for use with variants of the
vibroacoustic sensor modules of any
of FIGS. 16A-E, and 17A-B.
[63] FIG. 19 depicts an example circuit of an ECG sensor module of example
variations of the sensing
device.
[64] FIG. 20 shows a comparison between results obtained an example
variation of the ECG sensor module
of the present technology and traditional wet electrodes for leads II and a
VL.
[65] FIG. 21 depicts an example circuit of Driven Right Leg sensor used
during ECG procedures of the prior
art.
[66] FIG. 22A depicts a prototype circuit diagram for a Driven Right Leg
(DRL) sensor for use in an example
variation of a sensing device. FIG. 22B depicts an experimental set up
involving five DRL electrodes spaced
between and around two EPIC electrodes, with optional guard electrodes, for
use in an example variation of a
sensing device. FIGS. 22C and 22D show experimental results of a gain and
phase response of the DRL
feedback circuit of FIG. 22E compared to simulation using various numbers of
0.58 mm cloth separators. FIG.
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22E depicts an example variation of a DRL feedback circuit of a Driven Right
Leg sensor of the present
technology. FIG. 22F depicts a wet electrode bioimpedance analysis application
diagram. FIG. 22G depicts a
system diagram of an example sensor for bioimpedance. FIG. 22H depicts a
circuit diagram of an example
Electric Potential Integrated Circuit (EPIC) sensor. FIG. 221 and 22J are heat
maps of two simulations of EPIC
sensors in dircct skin contact for incorporation in an example variation of
the sensing device. FIG. 22K depicts
an experimental set up of an example variation of a sensing device for testing
bioimpedance sensors in which a
pair of conductive cloth pieces are connected by a resistor to create
repeatable "skin" resistance. FIGS. 22L and
22M show alternative "skin"_surrogate testing configurations". FIG. 22N shows
impedance versus frequency
scans obtained using two different skin surrogates and an arm and FIG. 220
shows phase versus frequency
scans obtained using two different skin surrogates versus and an arm. FIG. 22P
shows impedance versus
frequency response for various layers of conductive paper skin surrogate,
direct contact and cloth.
[67] FIG. 23 is a schematic illustration of an example variation of an
electronics system in a sensing device.
[68] FIG. 24 is a schematic illustration of an example variation of a
signal processing chain for conditioning
vibroacoustic signals from a sensing device.
[69] FIG. 25A illustrates an example signal processing circuitry in an
analog portion of the signal processing
chain of FIG. 24. FIG 25B shows the gain and phase response versus frequency
for the circuit of FIG. 25A.
FIG. 25C illustrates transfer functions for another example signal processing
circuitry.
[70] FIG. 26 is a schematic illustration of an example variation of a
portion of signal processing circuitry in
the signal processing chain shown in FIG. 24.
[71] FIGS. 27A and 27B depict an assembled view and an exploded view,
respectively, of an example
variation of a handheld sensing device for characterizing a bodily condition
of a subject.
[72] FIGS. 28A and 28B depict an assembled view and an exploded view,
respectively, of an example
variation of a handheld sensing device for characterizing a bodily condition
of a subject.
[73] FIG. 29A is a schematic illustration of an example variation of a
wearable sensing device for
characterizing a bodily condition of a subject. FIG. 29B and 29C are other
example variations of a wearable
sensing device for characterizing a bodily condition of a subject.
[74] FIG. 30 is a schematic illustration of an example variation of a
stethoscope sensing device for
characterizing a bodily condition of a subject.
[75] FIG. 31A depicts front and perspective views of an example variation
of a sensing device embodied as
a panel.
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[76] FIG. 31B is a cross-section of the sensing device of FIG. 31A.
FIG. 31C depicts an exploded view of
the sensing device of FIG. 31A.
1771 FIG. 31D depicts a front perspective view of another example
variation of a sensing device embodied
as a panel. FIG. 31E depicts a close-up of a portion of the sensing device of
FIG. 31D.
[78] FIG. 32A depicts a perspective view of an example variation of a
sensing device embodied as a panel
and including a base unit. FIG. 32B depicts an example variation of the
sensing device of FIG. 32A.
[79] FIG. 33A depicts an example variation of a sensing device embodied as
a gateway. FIG. 33B depicts
partially folded and fully folded example views of the sensing device of FIG.
33A. FIG. 33C depicts the sensing
device of FIG. 33A and including an output display unit.
[80] FIG. 33D-G arc schematics of emitted and received signals in example
variations of sensing devices
including an Echo Doppler sensor module, in which the sensing device includes
a single emitter and receiver
(FIG. 33D); two emitters and a single receiver (FIG. 33E); two receivers and a
single emitter (FIG. 33F); two
receivers and two emitters (FIG. 33G). FIG. 33H depicts the sensing device
variation of FIG. 33D and including
example losses.
[81] FIG. 34 depicts a flowchart summarizing an example variation of a
method for characterizing a bodily
condition of a subject.
[82] FIGS. 35A and 35B depict exemplary sensor data using an accelerometer-
based example variation of a
vibroacoustic sensor module of the present technology.
[83] FIG. 36A is a summary of development of classification models in an
example of training and testing a
machine learning model for classification of fatigue and non-fatigue states in
a subject in example variations of
a system of the present technology. FIG. 36B depicts sample heart sound data
extracted as segments from a
vibroacoustic waveform using an example variation of a sensing device of an
example variation of a system.
FIG. 36C depicts a Receiver Operator Curve (ROC) for a classification model
fit closest to a mean area under
the ROC values of data obtained using an example variation of a sensing device
of an example variation of a
system of the present technology.
[84] FIGS. 37A and 37B depict vibroacoustic data taken in the 3 Hz time
domain and frequency domain,
respectively, captured after applying signals using an example variation of a
sensing device of an example
variation of a system of the present technology to a human manikin phantom.
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[85] FIGS. 37C and 37D depict example vibroacoustic data taken in the 10 Hz
time domain and frequency
domain, respectively, captured after applying signals using an example
variation of a sensing device of an
example variation of a system of the present technology- to a human manikin
phantom.
[86] FIGS. 38A and 38B, FIGS. 39A and 39B, and FIGS. 40A and 40B depict
example vibrometer data
captured after applying signals to human skin using an example variation of a
sensing device of an example
variation of a system of the present technology through direct coupling (FIGS.
38A and 38B), through a T-shirt
(FIGS. 39A and 39B), and through a wool sweater (FIGS. 40A and 40B).
[87] FIGS. 41A-41E depict program output for example programs for
classification tasks on example
vibroacoustic data.
[88] FIGS. 42A and 42B depict program output on segmentation tasks on
example vibroacoustic data.
[89] FIG. 43 depicts example signals from an example variation of a
contextual sensor module of an example
variation of a sensing device including a microphone and a 9-axis inertial
measurement unit (including a tri-
axis accelerometer, a tri-axis gyroscope, and a tri-axis magnetometer).
[90] FIG. 44 depicts example vibroacoustic test data gathered for a
consumer drone.
[91] FIG. 45 depicts example vibroacoustic test data collected by a sensing
device of the present technology
from control subjects (control), asymptomatic subjects with a covid-19
infection, symptomatic subjects with a
covid-19 infection, and subjects with another respiratory disease (control).
[92] FIG. 46 depicts an example workflow of processing detected data
including windowing and feature
extraction.
[93] FIG. 47 depicts example vibroacoustic test data collected by a sensing
device of the present technology
from control subjects (control 1, control 2, control 3), and subjects with a
covid-19 infection (S002, S003, S004)
in which the vibroacoustic test data was collected while the subjects were in
the supine position, and the data
was collected from the right 2nd intercoastal space (ICS) of the subjects'
body.
[94] FIG. 48 depicts example vibroacoustic test data collected by a sensing
device of the present technology
from subjects with a covid-19 infection (S002, S003, S004), in a first visit
and a second visit, in which the
vibroacoustic test data was collected while the subjects were in the supine
position, and the data was collected
from the right 2' ICS of the subjects' body.
[95] FIG. 49 depicts example vibroacoustic test data collected by a sensing
device of the present technology
from control subjects (control 1, control 2, control 3), and subjects with a
covid-19 infection (S001 ¨ S0015) in
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which the vibroacoustic test data was collected while the subjects were in the
supine position, and the data was
collected from the right 2"d ICS of the subjects' body.
[96] FIG. 50 depicts example vibroacoustic test data collected by a sensing
device of the present technology
from control subjects, and subjects with a covid-19 infection in which the
vibroacoustic test data was collected
while the patients were in the supine position, and from different locations
on their bodies (carotid, right clavicle,
left clavicle, left 2nd ICS, right 2nd ICS, right 41h ICS, left 41h ICS, left
61h ICS, right 6th ICS).
[97] FIG. 51 shows sensor data extracts (vibroacoustic only) of two Subject
Cases and three Control Cases
taken while the patients were in different positions and performing different
actions (sitting, standing, supine,
left lateral, cough and hand squeeze, speech) with the sensing device position
on the right 2 ICS location on
their bodies.
[98] FIGS. 52A-52D show vibroacoustic test data collected by a sensing
device of the present technology,
FIG. 52A, when a subject without a clothing barrier is positioned 12 cm from a
diaphragm of the sensing device,
FIG. 52B, when a subject without a clothing barrier is positioned 100 cm from
a diaphragm of the sensing
device 100 cm away, FIG. 52C, when a subject wearing a sweater is positioned
12 cm from a diaphragm of the
sensing device, and FIG. 52D, when a subject wearing a sweater is positioned
100 cm from a diaphragm of the
sensing device 100 cm.
[99] FIGS. 53A-53C show vibroacoustic test data collected by a sensing
device of the present technology,
FIG. 53A, when a subject wearing a sweater is positioned 10 cm from a
diaphragm of the sensing device and is
facing the diaphragm, FIG 53B, when the subject wearing a sweater is
positioned 10 cm from a diaphragm of
the sensing device and is facing away from the diaphragm, and FIG. 53C, when
the subject wearing a sweater
is positioned 100 cm from a diaphragm of the sensing device and is facing the
diaphragm.
[100] FIGS. 54-59 show vibroacoustic test data collected by a sensing device
of the present technology, such
as the sensing device of FIGS. 4A-I from cows, sheep and goats, according to
certain embodiments of the
present technology.
[101] FIG. 60 depicts a perspective view of an example variation of a sensing
device embodied as an animal
gate, according to certain embodiments of the present technology.
DETAILED DESCRIPTION
[102] Non-limiting examples of various aspects and variations of the invention
are described herein and
illustrated in the accompanying drawings.
1. Systems for characterizing a bodily condition
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1.a. Overview
[103] As shown in FIG. 1A, a system 100 for characterizing a bodily condition
(e.g., health condition) may
include one or more sensing devices 110 with one or more sensors configured to
detect one or more biological
parameters (e.g., vibroacoustic signals) of a subject.
[104] In some variations, the one or more sensing devices 110 may be modular
and include interchangeable
subsystems adapted for modular experimentation, optimization, manufacture,
rapid field configurability, etc. as
part of a modular sensing platform. For example, the sensing device 110 may
include a sensor module with one
or more various sensor types, an electronics module, a housing, and/or other
modular components that may be
interchangeable for different applications and contexts. Such a modular
sensing platform may provide an
architecture well-suited for a modular suite of, for example, ambulatory
wearable devices, remote screening
devices and/or point-of-care solutions for healthcare, etc.
[105] The one or more sensing devices 110 may have any suitable form factor
for detecting biological
parameters of the subject in a non-contact or contact manner. The sensing
device 110 may be configured and
positionable in any suitable manner relative to the subject to capture the
suitable parameter(s).
[106] For example, the sensing device 110 may include a handheld housing such
that a user may hold and/or
manipulate the sensing device 110 sufficiently near or on the subject to
capture sensor data (FIG. 1A). The
sensing device 110 may be configured to capture suitable parameters through
clothing of the subject, or on
direct contact with skin of the subject.
[107] As another example, the sensing device 110 may include a wearable
housing that may be applied to the
subject (e.g., with an adhesive patch, and/or optionally targeted and applied
by a remotely controlled robotic
arm) (FIG. 1A), a cuff to be worn around a limb, or coupled to clothing or
other garments worn by the subject.
[108] In some variations, the sensing device 110 is configured to capture data
from the subject in a remote
manner. In this respect, the sensing device 110 may be a standalone device
(FIG. 1B and 1C), arranged to be
supported by a floor, wall, ceiling or other structural support, and
configured to capture data from the subject in
proximity to, but spaced from, the sensing device 110.
[109] In other variations, the sensing device 110 may be integrated in
furniture as beds, bedding, mattresses,
pillows, blankets, couches, chairs, vehicle seating, or devices such as
scales, mirrors, panels, kiosks, doorways,
signs and fitness equipment, etc.
[110] The sensing device 110 may be configured to communicate (e.g.,
wirelessly communicate) with one or
more computing devices 102, such as a mobile computing device, smart watch,
local data gateway, provide
feedback to a remotely controlled robot or prosthetic limb, or computer for
processing, analyzing,
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communication, and/or storage, etc. of sensor data and/or other suitable
information. For example, as shown in
FIG. ID, the sensing device 110 may be configured to communicate over a
network 104 with the computing
device 102 and/or other suitable modules. The computing device 102 may
additionally or alternatively collect
data from other devices such as scales, fitness and sports equipment, blood
pressure sensors, blood glucose
sensors, and/or one or more suitable mobile applications that can provide
supplementary environmental and
social determinants of health contextual information.
[111] Additionally or alternatively, the sensing device 110 may be configured
to communicate directly with
the computing device 102 and/or other devices without the network 104 (e.g.,
in pairwise fashion). In other
variations, the sensing device 11() may be configured to communicate directly
with the network 104.
[112] In some variations, the sensing device 110 may be configured to
communicate with suitable modules
such as, for example, a pattern evaluation module 106 which may incorporate
artificial intelligence (e.g.,
through application of one or more trained machine learning models) to
characterize one or more bodily
conditions of the subject based on sensor data. Parsed data may be stored
locally on a computing device and/or
on smartphonc gateway (e.g., sensor data, results of analysis of sensor data,
etc.) or may be stored in a suitable
data storage module 108 such as a server or through cloud storage, and/or an
electronic medical record 109
associated with the subject. Additionally, in some variations the machine
learning model(s) used to analyze the
sensor data may be continuously trained or updated using additional health
history, sensor fusion, and/or
environmental and/or social determinants of health context data over time as
further described below. For
example, sensor data may be mined via a data mining module 107 for use in
training and increasing the accuracy
of predictive and/or prescriptive models across patient populations. A
communication module may be provided
for communicating data between the various modules of the system.
[113] In some variations, one or more components of the system 100 for
characterizing a bodily condition
(e.g., health condition) may include various output interfaces such as for
communicating information relating
to the bodily condition (e.g., sensor data, analysis of sensor data,
operational status, etc.). For example, as shown
in FIGS. 1A-1H, the system 100 for characterizing a bodily condition may
include the sensing device 110 (e.g.,
handheld device, wearable device, standalone device, etc.), and the computing
device 102. The computing
device 102 may be a stand alone device and separate from the sensing device
(e.g. smartphone), or be
incorporated with the sensing device 110. In some variations, the computing
device 102 may be implemented
as a network-on-chip (NoC) technology. In some variations, the computing
device 102 and/or the sensing device
may be implemented as a wearable device. The sensing device 110 may include a
charging base 120 (FIG. 1H).
Furthermore, one or more of the sensing device 110, the computing device 102,
and the charging base 120 may
include at least one output interface. For example, as shown in FIG. 1F, the
sensing device 110 may include a
display and/or one or more other suitable visual indicators such as a light
indicator (e.g., LED indicator). As
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another example, the computing device 102 may include a haptic interface
and/or audio output (e.g., speaker
device). As another example, the charging base 120 may include a haptic
interface and/or visual indicator such
as a light indicator (e.g., LED indicator). However, it should also be
understood that in some variations, any of
the sensing device 110, the computing device 102, and/or the charging base 120
may include any suitable
combination of interfaces, such as one or more of visual, audio, haptic, etc.
One or more of the sensing device
110, the computing device 102, the network, and the charging base 120 may be
configured to communicate
information among each other (e.g., in a wireless manner, over a network,
etc.) as described in further detail
herein.
1.b. Vibroacoustic sensor platform
[114] In some variations, the system 100 for characterizing a bodily condition
is a vibroacoustic sensor
platform configured to detect and process vibracoustic signals, either alone
or in combination with other sensor
signals (not necessarily vibroacoustic signals), to diagnose or monitor a
bodily condition of the subject.
[115] In these variations, the system 100 includes a sensor module comprising
one or more sensors configured
to detect vibroacoustic signals as well as, optionally, signals which arc not
vibroacoustic signals, such as subject
temperature, environmental conditions, etc. The detected signals by the sensor
module is referred to generally
herein as "sensor data". The sensor data may originate at least partially from
the subject as well as from an
environment of the subject. The sensor module may be embodied in a single
sensing device 110 or in multiple
sensing devices 110.
[116] The system 100 may further comprise a signal processing system
configured to extract from the detected
sensor data a biological signal component originating from the subject. In
some variations, the extracted
biological signal component comprises one or more of a biological
vibroacoustic signal component, an
electroencephalogram (EEG) component, an electrocardiogram (ECG) component, an
electro-oculography
(EOG) component; a surface electromyogram (sEMG) component, and/or galvanic
skin response (GSR)
component originating from the subject.
[117] The system 100 may also comprise at least one processor configured to
characterize or monitor a bodily
condition of the subject based at least in part on the extracted biological
signal component, such as the biological
vibroacoustic signal component, using for example a machine learning model. It
is to be understood that the
bodily condition may be characterized on the sensor data, such as, one or more
of: the vibroacoustic signal data,
the extracted biological vibroacoustic signal component; signals which are not
vibroacoustic signals; and
biological signals extracted from the non-vibroacoustic signals originating
from the subject. Sensor data may
further include that from one or more of electroencephalogram (EEG),
electrocardiogram (ECG), electro-
oculography (EOG), surface electromyogram (sEMG), and/or galvanic skin
response (GSR).
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[118] The at least one processor may be embodied in one or more computing
devices configured to perform
processing, analysis, communication, and/or storage, etc. of sensor data from
the sensor module.
[119] The sensor module may be configured to detect a wide spectrum of
vibroacoustic frequencies, which
may provide useful indications of human health, animal health, and/or
structural health separately and
concurrently, including those that are not conventionally monitored or
detected. More specifically, in certain
variations, the sensor module is configured to detect vibroacoustic signals
below and above the threshold of human
audibility.
[120] As shown in FIG. 1E, the threshold of human audibility decreases sharply
as vibrational frequency falls
below about 500 Hz. However, in a healthy subject at rest, most cardiac,
respiratory, digestive, and movement-
related information is inaudible to humans, as this information occurs at
frequencies below those associated
with speech. Thus, the majority of bodily vibrations are neither detected nor
included in conventional diagnostic
medical practices due to the low frequency band of these vibrations, and the
limited bandwidth limits of
conventional instruments (e.g., conventional stethoscopes). Variations of the
system 100 described herein are
capable of detecting, amplifying and analyzing a broad spectrum of infrasound,
ultrasound, and far-ultrasound
vibroacoustic frequencies, and are thus advantageous for a more comprehensive,
holistic picture of subject
health and condition.
[121] Additional details of the system 100 and its components, sensing devices
110 and methods are described
further below. Such systems 100, sensing devices 110 and methods are primarily
described with respect to
characterizing a bodily condition of a subject, which may be, for example, a
human or other animal (e.g., for
human healthcare and/or veterinary care). However, it should be understood
that other applications of the
systems 100, sensing devices 110 and methods may relate to characterization of
non-living items, including but
not limited to heating, ventilation, air conditioning (HVAC) systems, internal
combustion engines, jet engines,
turbines, bridges, aircraft wings, environmental infrasound, ballistics, drone
and/or seacraft identification etc.
For example, the systems 100, sensing devices 110, and methods may be applied
to characterize structural health
(e.g., characterizing structural integrity of bridges, buildings, aircraft,
vehicles, etc.), environmental noise
pollution, rotating motor engine performance optimization, surveillance etc.
1.c. Example sensing devices
1.c.i. Hand-held sensing devices
[122] In some variations, the system 100 may include, as shown schematically
in FIG. 2, a sensing device
200 which is hand-held. The sensing device 200 includes a sensor module
comprising: a vibroacoustic sensor
module 220, and optionally a contextual sensor module 230; an electronics
system 240 which may, for example,
handle sensor data from the vibroacoustic sensor module 220 and/or the
contextual sensor module 230. One or
more of these components may be enclosed or otherwise at least partially
arranged in a housing 210 of the
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sensing device 200, which may have any suitable forin factor for different
applications as further described
below. In some variations, the housing 210 may include a display 250 for
providing a user interface of the
sensing device (e.g., for displaying information to a user, for permitting
control of the sensing device, etc.).
Certain other examples of the form factor of the sensing device 110 or 200 are
illustrated in FIGS. 3A and 3B,
4A ¨ 4E, 4F-4G, 5A-5I, 27A-27B, 28A-28B, 29, 30, 31A-31E, 32A-32B, and 33A-
33C.
[123] FIGS. 3A and 3B illustrate another example sensing device 300, which is
a variation of the sensing
device 110. As shown in FIG. 3A, the sensing device 300 may include a housing
310 within which various
sensing device components may be arranged. The housing 310 shown in FIG. 3A is
configured as a handheld
housing 310 having a generally cuboid shape; however, it should be understood
that other housing variations
may have other shapes (e.g., spherical, ellipsoid, other prismatic shapes,
etc.). Other exemplary sensing device
form factors are described in further detail below.
[124] In some variations, a base 302 may be coupled to the housing 310. The
base 302 may, for example,
provide a surface on which the housing 310 may rest and/or provide an
indication of device orientation (e.g.,
indicate a primary direction along which the sensor module within the housing
310 is sensing). In some
variations, the base 302 may function as a charging cradle, with the housing
310 separable from the base 302
when the sensing device 300 is in use.
[125_1 As shown in the exploded view of FIG. 3B, the housing 310 may surround
a vibroacoustic sensor
module 320 that includes one or more sensors for collecting vibroacoustic
signals, an optional contextual sensor
module 330, and an electronics system 340 including components for processing
the sensor data from the
vibroacoustic sensor module 320 and optionally the contextual sensor module
330. In some variations,
electronic components (within the vibroacoustic sensor module and/or in the
electronics system 340, for
example) may perform various signal processing functions to extract a
biological vibroacoustic signal
component from sensor data, and/or perform analysis via artificial
intelligence (e.g., utilizing one or more
machine learning models) to characterize a bodily condition based on the
biological vibroacoustic signal
component.
[126] In some variations, the housing 310 may include one or more guides or
compartments for receiving and
positioning the various internal device components. For example, as shown in
FIG. 3B, the housing 310 may
include one or more internal projections 316 (e.g., shoulder, lip, or other
guide) configured to restrain an
adjacent device component such as the vibroacoustic sensor module 320 or
electronics system 340. The restraint
may be provided by an interference fit, one or more fasteners, and/or the
like. Although FIG. 3B depicts the
internal device components as generally axially aligned, it should be
understood that in other variations, the
components may be arranged in any suitable manner (e.g., orthogonal to one
another, etc.).
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[127] The housing 310 may include one or more openings and/or other structures
to facilitate communication
with sensors. For example, the housing 310 may include a sensor opening
adjacent to the vibroacoustic sensor
module 320 to permit entry and propagation of vibroacoustic waves toward the
vibroacoustic sensor(s) in the
module and/or a membrane or other receiver that interfaces with the
vibroacoustic sensor(s). Additionally or
alternatively, in some variations the sensing device 300 may include an
impedance matching diaphragm 350
arranged in series with the vibroacoustic sensor module 320 to improve
sensitivity to a wide range of
vibroacoustic frequencies. The diaphragm 350 may be dome shaped, for example,
impedance matching may
refer to the operating state in which the load impedance and the internal
impedance of the excitation source
match to each other (e.g., within a tolerated impedance difference), thereby
leading to a maximum power output.
A mismatch in the impedances may result in undesirably high attenuation and/or
reflection of source signals
away from the vibroacoustic sensor module. This problem may be addressed, for
example, by developing
impedance matching circuits using machine-fabricated tunable components
leveraging a plurality of diaphragm
cutout designs (also referred to as "apertures", examples of which are shown
in FIG. 18) for an optimal dynamic
range in the low infrasotmd domain. A combined diaphragm/transducer solution
may include a suitable
protective material (e.g., rubber, felt liner, light foam, etc.) around the
diaphragm and fixture area to protect the
interior of the transducer from water and particulate matter by sealing any
gaps. Diaphragm may include a
passive material (including but not limited to polymer, polyamide,
polycarbonate, polypropylene, carbon fiber,
fiber glass, etc.) fabricated as the structural layer with optimized
dimensions for the physical system form factor.
In order to obtain the tunable impedance matching system and structural
layer(s), the gap between the diaphragm
and voice coil may be tunable. The structural layer(s) may be spun and
patterned to ensure the shape and optimal
weight and subsequently bonded. In the case where direct or through clothing
skin contact is made, impedance
matching may be performed by applying varying pressure to the subject, thus
loading the diaphragm to the
desired extent.
[128] In some variations, the housing 310 may include a power connection port
314 enabling a connection of
an auxiliary power source to the electronics system 340 and/or other powered
components. Additionally or
alternatively, the housing 310 may include a data connection port (not shown)
that may provide a (wired option
for uploading or downloading data or other information to and from the
electronics sy stem 340. In some
variations, power and data may be communicated via the same port (e.g., via a
USB connection).
[129] Furthermore, in some variations the housing 310 may include a user
interface, such as a display 360
which is visible through a screen or opening in a bezel 312 of a top cover 313
or other suitable portion of the
housing 310. The display 360 may include an LED screen, LCD screen, or other
suitable monitor screen. The
display 360 may be configured to display information to a user (e.g.,
diagnostic information, sensor data. device
status, etc.) such as on a graphical user interface (GUI), to permit control
of the sensing device (e.g., power
states, operational mode, etc.), and/or the like. In some variations, the
display 360 may include a touchscreen to
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receive user input. In some variations, the vibroacoustic sensor or a
dedicated microphone may be used to
receive vocal user input. Additionally, or alternatively, user input may be
provided to the sensing device 300
through one or more hardware user interface elements on or coupled to the
housing (e.g., buttons, slides,
switches, touch sensors, etc.). Additionally, or alternatively, information
about the device and/or analysis may
be communicated through other components (e.g., visual notifications with an
array of LEDs, audible
notifications with a speaker device, tactile notifications with a vibrational
motor, etc.). For example, in some
variations, acoustic data may be played back over one or more speaker devices
(or communicated to a peripheral
device for playback). Furthermore, in some variations, one or more device
orientation and/or positional sensors
(e.g., Inertial Measuring Unit (IMU), accelerometer, gyroscope, etc.) may be
used for user input and function
manipulation of the sensing device (e.g., shaking or rotating the sensing
device may toggle between device
settings, wake up or put the sensing device into a sleep or standby mode,
etc.).
[130] The housing 310 may be constructed in various suitable manners, such as
injection molding, milling,
3D printing, etc. As shown in FIG. 3B, the housing 310 may include multiple
connectable portions (e.g., two
halves of a shelled housing) that join to form one or more internal volumes
receiving internal device
components. The connectable portions may be coupled together with mechanical
interlocking features (e.g.,
pins and holes sized to engage in a friction fit), fasteners (e.g., screws,
adhesive, etc.), and/or in any suitable
manner. Alternatively, the housing 310 may be integrally formed as a single
piece.
[131] In some variations, some of the components of the sensing device 300 may
be intended as reusable
and/or upcycled, while other components may be disposable. For example, in
some variations inexpensive
components such as the housing 310 and/or subject-contacting components (e.g.,
impedance-matching
diaphragm) may be replaced, while more expensive components such the
electronic components of the sensing
device 300 may be re-used. In some variations, components may be disinfected
(e.g., with isopropyl alcohol)
instead of being replaced and disposed of In this respect, the disinfectable
components may be made of a
material suitable for disinfection such as by one or more of alcohol, hydrogen
peroxide, steam, ethylene dioxide,
gamma irradiation, ultraviolet light. In some variations, the sensing device
300 may include one or more sensors
(e.g., proximity sensors, Hall effect sensors, contact sensors, etc.) that
detect and authenticate the attachment
and detachment of replaceable parts, so that the system 100 can intelligently
monitor uses, sterile change events,
duration of use between changes in sterile covers, battery levels, number of
uses and/or other usage data, etc.
Such data may, for example, be used to monitor a report on compliance with
best practices and required
protocols for maintaining cleanliness.
[132] in some variations, the housing 310 may be configured to be attachable
to another type of device such
as a stethoscope. In this respect, retroactive attachability may be
facilitated by windings for screw attachment
or other fasteners.
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[133] FIGS. 4A ¨ 4E illustrate a sensing device 400, which is another example
variation of the sensing device
110 of the system 100. The sensing device 400 is also modular and includes
multiple components that can be
assembled together. For example, the sensing device 400 includes a housing 410
connectable to a top cover 413
and a bottom cover 415. The sensing device 400 has a handle end H and a sensor
end S. As before, the housing
410 may be couplablc to a base (not shown), for charging and/or support. The
housing 410 is configured to
substantially surround one or more of the components including: a
vibroacoustic sensor module 420, an
electronics system 440, a power source 442, a diaphragm 450 (such as an
impedance matching diaphragm 450),
first and optionally second capacitive electrodes 460, 470 for
electrocardiogram (ECG) measurements. In
certain variations, the first capacitive electrodes 460 comprise Electric
Potential Integrated Circuit (EPIC)
electrodes 460. In certain variations, the second capacitive electrodes 470
comprise Driven Right Leg (DRL)
electrodes 470. in certain other variations, the capacitive electrodes 460,
470 may be omitted (FIG. 4H). The
diaphragm 450 is supported by the bottom cover 415 and extends from an opening
in the bottom cover 415. The
diaphragm 450 may be dome-shaped. In other embodiments, the diaphragm 450 may
have a different shape
such a cuboid, cylindrical, spherical conical, pyramidal, or torusal.
[134] As seen in FIG. 4F and 4G, in certain variations, an outer cover 480 may
also be provided to seal a
connection between the bottom cover 415 and the diaphragm 450 for limiting or
preventing foreign body
ingress. The outer cover 480 may be made of rubber, or any other suitable
material including material suitable
for medical applications. The outer cover 480 may be connected to the bottom
cover 415, such as by adhesive.
In the variations of FIGS. 4F and 4G, the outer cover 480 stops short of a
perimeter of the bottom cover 415.
However, in certain other variations, the outer cover 480 extends entirely
across the bottom cover 415, and may
also extend upwards from the bottom cover 415 like a cap. This can allow the
sensor end S of the sensing device
400 to be soaked in liquid, such as a disinfecting solution. Solution could be
provided within a base like 302,
for sterilization or cleaning. In certain variations, a gap between the
diaphragm 450 and the bottom cover 415
to be covered can be anywhere between 0.001 mm and 20 mm; such as bout 2 mm,
about 4 mm, about 6 mm,
about 8 mm, or about 10 mm.
11351 FIG. 41 depicts a variation of the outer cover 480 of the sensing device
400, in that a bend 481 is included
in the outer cover 480 which can permit expansion of the outer cover 480 to
account for movement of the
diaphragm. The bend is positioned radially. In this variation, a gap between
the diaphragm 450 and the bottom
cover 415 is about 2 mm, and the bend 481 has a radius of about 2 mm. This may
allow compliant and linear
travel of the diaphragm for up to 4mm out of plane. As a variation, the outer
cover 480, including the bend 481
may extend all the way across the bottom and up the side of the device to be
fluid resistant (not shown). In other
words, the sensor end of the housing 410 may be covered by a one piece outer
cover 480.
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[136] hi other variations, there may be provided a sensor 490 attached to the
diaphragm 450, on an inner
surface thereof. The sensor 490 may comprise one or more of an Inertial
Measuring Unit (IMU), an
accelerometer, or a gyroscope for example. In certain embodiments, the sensor
490 comprises a gyroscope and
an accelerometer. In this respect, the voice coil module 420 measures a
velocity proportional signal. In contrast
the accelerometer measures acceleration and the gyroscope measures angle
velocity therefore enabling the
capture of non-orthogonal soundwaves. The data from the voice coil module 420
and the sensor 490 may be
combined and processed to increase data fidelity. In certain embodiments, the
sensor 490 comprises a 4-24 kHz
sampling rate, 1-8kHz bandwidth and 22.5-50 itiV/-NiHz noise spectral density.
In other embodiments, the sensor
490 comprises a 32-96 kHz sampling rate, 4-24 kHz bandwidth and 50-70 noise
spectral density.
[137] The sensor 490 may be positioned at any suitable location on the
diaphragm 450. For example, when
the sensor 490 is positioned at an apex of the dome-like diaphragm 450, an
amplitude of the data collected is
larger than when the sensor 490 is positioned near an edge of the dome-like
diaphragm 450 where there is
relatively less movement. The data obtained from the sensor 490 as an IMU can
tend to be noisy and sensitive
compared to the data obtained from the voice coil module 420 when the voice
coil module is implemented as
shown and described in relation to Figures 16-18.
[138] This is illustrated for example in FIG. 4J which illustrates the voice
coil module 420 as comprising a
frame 492 (also referred to as a magnet housing or a surround pot) having a
cylindrical body portion with a bore
and a flange extending radially outwardly from the cylindrical body portion.
An iron core 493 is attached to the
cylindrical body portion and lines the bore of the cylindrical body portion. A
magnet 494 is positioned in the
bore and is surrounded by, and spaced from, the iron core 493 to define a
magnet gap 495. A voice coil 496,
comprising one or more layers of wire windings supported by a coil holder is
suspended and centered in relation
to the magnet gap 495 by one or more deflecting members (spiders 497). A
periphery of the spider 497 is
attached to the frame 492, and a center portion is attached to the voice coil
496. The voice coil 496 at least
partially extends into the magnet gap 495 through the open end of the iron
core 493. The one or more spiders
497 allow for relative movement between the voice coil 496 and the magnet 494
whilst minimizing or avoiding
torsion and in-plane movements. The diaphragm 450 is attached to the voice
coil 496.
[139] The housing 410 may be configured to mount the voice coil module 420
thereto in a manner that limits
or prevents radial movement of the frame 492 of the voice coil module 420
relative to the housing 410. In this
respect, the voice coil module 420 may be arranged to be permanently attached
to the housing 410 such as by
adhesive, welding or the like. Alternatively, the voice coil module 420 may be
arranged to be removably
attached to the housing 410 such as by inter-engaging elements between the
frame 492 and the housing. One
example of such inter-engaging elements comprise notches 498 for receiving
protrusions 499. As illustrated in
Fig. 4K, the notches 498 may be formed on an inner surface of the housing 410
and the protrusions 499 may be
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provided on the frame 492. As above, the housing 410 may also be modular and
include an outer cover 410a
and a main body portion 410b.
[140] The sensing device 400 differs from the sensing device 300 in form
factor, as well as the type of sensors
included. More specifically, the sensing device 400 does not include the
contextual sensor module 330 in certain
embodiments. The sensing device 400 may include the EPIC electrodes 460 and
DRL electrodes 470 for
collecting ECG data. The EPIC and DRL electrodes 460, 470 will be described in
further detail below with
reference to FIGS. 19 - 22.
[141] In certain variations, the sensing device 400 is sized and shaped to be
handheld. Optimization of the
size and shape of the sensing device 400 has a number of considerations
including one or more of: a spacing of
the EPIC electrodes 460 and the DRL electrodes 470 from one another and/or the
vibroacoustic sensor module
420 to avoid interference, and a size of the diaphragm 450. Accordingly in one
variation, four EPIC electrodes
460 and four DRL electrodes 470 are provided, spaced apart from one another
and positioned around the
diaphragm 450. The diaphragm 450 has a diameter of about 39 mm, and each EPIC
electrode is about 10 mm
long. It will be appreciated that the arrangement of the electrodes 460, 470
and their size may vary from that as
illustrated. Sensing devices with alternative dimensions are within the scope
of this present disclosure.
[142] In certain variations, one or more of the DRL electrodes 470 may
comprise a guard electrode. In fact,
in certain variants, a function of the electrode 470 may be configurable as
either a guard electrode or a DRL
electrode depending on whether the use is skin contact or no direct skin
contact. In certain other variants the
bottom cover 415 is made of a conductive material and configured as a guard
electrode.
[143] FIG. 4H illustrates a sensing device 400' which is a variation of the
sensing device 400 of FIGS. A-E,
which differs only in that the EPIC electrodes 460 and Driven Right Leg (DRL)
electrodes 470 for sensing ECG
data have been omitted. The sensing device 400' is configured to detect only
vibroacoustic signals.
1.c. ii. Example sensors of the vibroacoustic sensor modules
[144] In certain variations, a vibroacoustic sensor module, such as the
vibroacoustic sensor module 220, 320,
420, 2720, 2820, 2920, 3140 may include one or more sensors configured to
detect a vibroacoustic signal. The
vibroacoustic sensor module may also include one or more deflecting structures
interfacing with a sensor
component of the sensor. For example, the one or more sensors may be selected
and/or arranged to interface
with the one or more deflecting structures so as to measure various
characteristics of the movement of the
deflecting structure(s) (e.g., in response to vibroacoustic waves). Such
movement, which is measurable by the
one or more sensors, may be analyzed to assess bodily condition(s) of a
subject. As further described below, in
some variations, the one or more sensors may also be a printable circuit,
flexible skin-friendly printable circuits
embodied as an electronic tattoos, and/or arranged on a flexible circuit board
or other structure that is suitably
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flexible so as to not significantly interfere with the interfacing of the
sensor(s) and deflecting structure(s),
thereby avoiding reduction in sensitivity and/or bandwidth of the
vibroacoustic sensor module. Exemplary
variations of sensor arrangements and deflecting structures are described in
further detail below.
[145] In some variations, the vibroacoustic sensor module may have a bandwidth
suitable for detecting
vibroacoustic signals in the infrasound range, such as a bandwidth ranging
from about 0.01 Hz to at least about
20 Hz. Furthermore, in some variations, the vibroacoustic sensor module may
have wider bandwidths covering
a wider spectrum of infrasound-to-ultrasound, such as a bandwidth ranging from
about 0.01 Hz to at least 160
kHz. In some variations, the biological vibroacoustic signal component
extracted from the detected
vibroacoustic signal may have a bandwidth ranging from about 0.01 Hz to 0.1
Hz.
[146] For example, in some variations the vibroacoustic sensor module may have
an overall bandwidth
ranging from about 0.01 Hz to at least about 50 kHz, from about 0.01 Hz to at
least about 60 kHz, from about
0.01 Hz to at least about 70 kHz, from about 0.01 Hz to at least about 80 kHz.
from about 0.01 Hz to at least
about 90 kHz, from about 0.01 Hz to at least about 100 kHz, from about 0.01 Hz
to at least about 110 kHz, from
about 0.01 Hz to at least about 120 kHz, from about 0.01 Hz to at least about
130 kHz, from about 0.01 Hz to
at least about 140 kHz, from about 0.01 Hz to at least about 150 kHz, from
about 0.01 Hz to at least about 160
kHz, from about 0.01 Hz to more than about 150 kHz.
[147] The vibroacoustic sensor module may, in some variations, include a
single sensor that provides one or
more of the abovementioned bandwidths of detected vibroacoustic signals.
[148] In some other variations, the vibroacoustic sensor module may include a
suite of multiple vibroacoustic
sensors, each having a respective bandwidth forming a segment of the overall
vibroacoustic sensor module
bandwidth. At least some of these multiple sensors may have respective
bandwidths that at least partially
overlap. Accordingly, various sensor module bandwidths may be achieved based
on a selection of particular
sensors that collectively contribute to a particular vibroacoustic sensor
module bandwidth. In other words,
bandwidth extension and linearization approach (bandwidth predistortion) may
utilize modular sensor fusion
and response feedback information, such as to compensate for bandwidth
limitations of any particular single
sensor with overlapped combinations of sensors to cover a wider bandwidth with
optimal performance.
[149] For example, the vibroacoustic sensor modulo may include one or more
sensors for measuring
vibroacoustic signals. The one or more sensors may be selected from passive
and active sensors for obtaining
vibroacoustic data such as one or more of a microphone, a voice coil,
accelerometer, pressure sensors,
piezoelectric transducer elements, doppler sensors, etc. For example, the
vibracoustic sensor module may
include a voice coil-based sensor. In another example, the vibracoustic sensor
module may include a voice coil-
based sensor and an echo doppler based ultrasound sensor. The vibroacoustic
sensor module may include one
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or more microphones such as a dynamic microphone, a large diaphragm condenser
microphone, a small
diaphragm condenser microphone, and/or a ribbon microphone. Additionally, or
alternatively, the vibroacoustic
sensor module may include a linear position transducer. Such sensors may be
configured to detect and measure
vibroacoustic signals by interfacing with a suitable deflecting structure that
moves in response to a vibroacoustic
signal. In some variations, the vibroacoustic sensor module may combine
multiple microelectromechanical
systems technologies cross-axis inertial sensors capable of detecting
vibroacoustic signals ranging from about
20 Hz to about 20 kHz, when intentionally limited to human auditory range.
[150] Additionally, or alternatively. the vibroacoustic sensor module may
include a MEMS cross-axis inertial
sensor fusion capable of detecting vibroacoustic signals ranging from about 1
Hz (or less) to a few kHz (e.g.,
between about 1 Hz and about 2 kHz). Even further, the vibroacoustic sensor
module may additionally or
alternatively include a MEMS cross-axis inertial sensor capable of detecting
vibroacoustic signals ranging from
about 0.01 Hz to several hundred Hz (e.g., between about 0.05 Hz and about 10
kHz). Additionally, or
alternatively, other suitable vibroacoustic sensors may be included in the
vibroacoustic sensor module, such as
a voice coil transducer, piezoelectric transducer, etc. In some variations,
transmission of vibroacoustic waves
may occur through an intermediate medium such as air and/or across a
deflecting structure.
[151] Furthermore, a suite of multiple kinds of sensors in the vibroacoustic
sensor module may be configured
to more fully capture longitudinal and transverse vibrations, as well as
environmental context and environmental
disturbances (alone or in combination with the contextual sensor module
described in further detail below). In
some variations, environmental context signals may be useful for
contextualizing the relevant vital physiology
data collected. Additionally, or alternatively, in some variations,
environmental disturbance data (e.g., ambient
noise) may be used for noise cancellation from the relevant biological
vibroacoustic signal component. Such
noise cancellation may, for example, be performed as active noise cancellation
on the device, or as a
postprocessing step. In some variations, a deflecting structure in the
vibroacoustic sensor module may generally
have a nominal or resting configuration in which the deflecting structure is
arranged in a plane, and the
deflecting structure may deflect or flex in response to out-of-plane forces.
In these variations, the deflecting
structure may be configured to have low stiffness (or resistance) against out-
of-plane movement with good
compliance to skin movement, yet high stiffness or resistance against in-plane
movement and low crosstalk
between axes within the plane. Accordingly, a deflecting structure have high
sensitivity to acoustic waves
directed toward the deflecting structure (that is, acoustic waves having a
vector component that is orthogonal to
the deflecting structure) but be robust against noise contributed by other
forces.
[152] Furthermore, in sonic variations, a deflecting structure in the
vibroacoustic sensor module may have
relatively low mass on the movable portion of the deflecting structure to
reduce inertia (and further improve
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sensitivity to out-of-plane forces). In some variations, the deflecting
structure may be designed with low or no
hysteresis, such that out-of-plane movement is highly linear.
[153[ Additionally, or alternatively, the deflecting structure may be designed
to have low material fatigue
over time, so as to be predictable and consistent over the long-term use of
the sensing device.
[154] The deflecting structure may, in some variations, include a more rigid
material such as a rigid plastic,
and may be formed through 3D printing, milling, injection molding, or in any
suitable manner. For example,
the deflecting structure may include a material including but not limited to
poly amide, polycarbonate,
polypropylene, carbon fiber, fiber glass, and/or other suitable material.
Flexure arm-type vibroacoustic sensor modules
[155] In some variations, the vibroacoustic sensor module may include one or
more deflecting structures that
include at least one flexure arm. For example, FIGS. 5A-5I depict an exemplary
variation of a vibroacoustic
sensor module 500 having multiple flexure arms. As shown in the cross-
sectional views of FIGS. 5A and 5B,
the vibroacoustic sensor module 500 may be arranged in a housing 510 of a
vibroacoustic sensing device (e.g.,
which may be similar, for example, to the sensing device 300 shown in FIGS. 3A
and 3B or the sensing device
400 shown in FIGS. 4A and 4B), such as restrained in a slot or other cavity of
the housing 510. In some
variations, the vibroacoustic sensor module 500 may include one or more
flexure arms configured to deflect in
a direction generally orthogonal to a sensing side (S) of the housing 510.
[156] As shown in FIGS. 5C-5F, the vibroacoustic sensor module 500 may include
a deflecting structure 520
and a flex circuit 530 including a cross-axis inertial sensor such as an
accelerometer 532 (e.g., MEMS
accelerometer). The deflecting structure 520 may include two or more flexure
arms 524 supported at an outer
end by a frame 520 and supported at an inner end by a central hub 526
functioning as a signal pickup. In some
variations, the flexure arms may be radially distributed around the central
hub 526. The flex circuit 530 may
include at least one accelerometer 532 and may be attached at an inner end to
the central hub 526, such that the
accelerometer 532 moves with the central hub 526 in response to impinging
vibroacoustic waves. In some
variations, an impedance matching receiver 540 may also be coupled to the
central hub 526 to enhance the
sensitivity of the deflecting structure 420 to impinging vibroacoustic waves.
As shown in FIG. 5E, the receiver
540 may be a dome-shaped diaphragm, for example. Thus, vibroacoustic waves may
cause movement of the
receiver 540 and deflecting structure 520 that is detected and measured by the
accelerometer 532.
[157] FIGS. 5G-5I illustrate additional details of the vibroacoustic sensor
module 500. As shown in FIGS. 5G
and 51, the deflecting structure 520 may include two flexure arms 524 coupled
to the central hub 526 generally
within a plane. The flexure arms 524 may be radially distributed around the
central hub 526, and in some
variations radially equidistant or asymmetrically distant (as to be tuned to
different resonance frequencies and
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thereby different frequency bands) from each other (i.e., the two flexure arms
524 may be arranged about 180
degrees apart around the central hub). The flexure arms 524 may be wavy (e.g.,
arched or sinusoidal), which
helps optimize out-of-plane flexibility and in-plane rigidity. The cross-axis
inertial sensor (on the flex circuit
530) may rest on a cantilever to allow effective coupling with minimal
mechanical constraints from other parts
of the system. A pre-buckled, out-of-planc, arc-shaped geometry allows the
flexure arms 424 (e.g., serpentine
interconnects) to assume traction free architectures that absorb tensile
deformations in multiple modes. Finite
element modeling (FEM) may highlight significant mechanical advantages of
these noncoplanar interconnects,
via out of plane linearity and compliance with stiffness to in- plane
movement, compared with conventional
planar serpentine layouts. Accordingly, out-of-plane forces (e.g.,
vibroacoustic waves) may urge the flexure
arms 524 to deflect and the central hub to move out-of-plane, while the
flexure arms 524 have low or no lateral
in-plane movement. in some variations, as shown in FIG. 51, the central hub
may be at least partially cored out
with one or more cutouts to reduce the hub's mass and inertia (which may, for
example help improve its
sensitivity to out-of-plane forces).
[158] As described above, the flex circuit 530 may, like the flexure arms 524,
be flexible and receptive to out-
of-plane movement. The flex circuit 430 may provide the vibroacoustic sensor
module with an overall lower
agile stiffness that is advantageously more isotropic. In some variations, as
shown in FIG. 5H, the flexible circuit
board 530 may have a general spiral shape within a plane, winding outwards
from an inner end to an outer end.
As described above, the inner end of the flexible circuit board 530 may be
coupled to the central hub 526 such
that an accelerometer 532 on the inner end of the flexible circuit board 430
may move in tandem with the central
hub 526 (e.g., in response to vibroacoustic waves). At its outer end, the
flexible circuit board 530 may be
configured to attach to a flex circuit anchor 523 (e.g., on or coupled to the
frame of the deflecting member 520)
shown in FIG. 51. The outer end of the flexible circuit board 530 may also
include a cable connector 534
electrically connected to conductive traces (not shown) that traverse the
flexible circuit board 530 to and from
the accelerometer 532, such that signals can be communicated to and from the
accelerometer 532 via the cable
connector 534 and conductive traces.
11591 However, the flexible circuit board 530 may have any suitable shape that
may be sufficiently flexible
and receptive to out-of-plane movement. For example, FIG. 6A depicts an
exemplary variation of a
vibroacoustic sensor module 600 that includes a deflecting structure 620 with
two flexure arms meeting at a
central hub and a flexible circuit board 630 coupled to the deflecting
structure 620. Similar to flexible circuit
board 530 described above with respect to FIGS. 5A-5I, the flexible circuit
board 630 includes a cable connector
634 on an outer end of the flexible circuit board 630, and an accelerometer
632 on an inner end of the flexible
circuit board 630, with conductive traces extending between the accelerometer
632 and the cable connector 634
for signal communication to and from the accelerometer 632. However, as shown
in FIG. 6B, unlike the spiral-
shaped flexible circuit board 530, the flexible circuit board 630 may have a
generally zig-zag shape.
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[160] In some variations, the flexure arms may have a flexure thickness of
less than about lmm to be
sufficiently sensitive to vibroacoustic signals, yet sufficiently resilient.
For example, flexure arms may be
formed from an SLA type photopolymer with good stiffness and low internal
damping.
[161] In some variations, the central hub of the deflecting structure (e.g.,
deflecting structures 520 and 620)
may have varying thicknesses to provide for different amounts of clearance for
the flexure arms. For example,
FIG. 7A depicts a vibroacoustic sensor module 700 including a deflecting
structure 720 and a flexible circuit
board 730. Similar to that described above, the deflecting structure 720 may
include a central hub 726 that is
configured to move in a transverse direction as indicated by the arrow, as
flexure arms move in an out-of-plane
manner.
[162] FIG. 7B depicts a similar vibroacoustic sensor module 700' that is
similar to vibroacoustic sensor
module 700, except that the vibroacoustic sensing module 700' has a thicker
central hub 726' that extends
farther from the rest of the deflecting structure. The central hubs 726 and
726' may be placed against a contact
surface (C) (e.g., a subject's skin) when the sensing device is in use, but
the thicker central hub 726' provides
for a greater distance between the flexure arms of the deflecting structure
720 and the contact surface (C) than
central hub 726 does.
[163] Although FIGS. 5A-5I depict an exemplary variation of a deflecting
structure 520 having two flexure
arms, it should be understood that other variations of deflecting structures
may include other suitable numbers
of flexure arms. The flexure arms may be radially distributed around a central
hub, and in some variations may
be equally radially or asymmetrically distributed around the central hub so as
to be tuned to different resonance
frequencies and thereby different frequency bands. For example, FIGS. 8A and
8B depict a vibroacoustic sensor
module 800 including a deflecting structure 820 having three flexure arms 824.
The three flexure arms may be
wavy (e.g., arched or sinusoidal) and equally radially arranged around a
central hub of the deflecting structure
(i.e., the three flexure arms may be arranged about 120 degrees apart around
the central hub). The vibroacoustic
sensor module 800 may further include a flexible circuit board 830. While the
flexible circuit board 830 is
shown in FIGS. 8A and 8B as having a zig-zag shaped similar to the flexible
circuit board 620 shown in FIGS.
6B, in other variations the flexible circuit board 830 may be spiral shaped
similar to that shown in FIG. 5H, or
other suitable shapes.
[164_1 Furthermore, the flex circuit may be unnecessary if the sensor(s) can
be powered through induction or
piezoelectrical phenomena and the sensor can communicate data back to the
electronic systems through
induction, radio frequencies, magnetic flux changes, or optical communication.
[165] Furthermore, in some variations the deflecting structure may have four
or more flexure arms. For
example, in some variations, the deflecting structure may include four flexure
arms in hue with the sensor mass
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edges (e.g., based on FEM for design optimization). In yet other variations,
the deflecting structure may include
five, six, or more than six flexure arms. In addition to such a mechanical
deflecting structure design, higher-
performance flexible dielectric nanocomposite materials may be incorporated
into the deflecting structure,
including but not limited to any combination of graphene, reduced graphene
oxide/titanium dioxide (rGO/TiO2)
nanocompositcs, polyvinyl alcohol modified polyvinylidene fluoridc-graphenc
oxide, polyvinyl fluoride (PVF)
or ¨(CH2CHF)n¨, and/or poly (viny lidene fluoride) or poly vinylidene fluoride
or poly vinylidene difluoride
(PVDF) incorporated with reduced graphene oxide (rGO) and poly(vinyl alcohol)-
modified rGO (rGO-PVA).
Nanocomposites may have inherently unique properties and convenience to
fabricate into different
morphological nanostructures, such as by spraying and doping of substrates as
atomically thin single layers to
nanoribbons. In yet other variations, the deflecting structure may include
five, six, or more than six flexure arms.
[166] While the above description primarily describes deflecting structures in
which an accelerometer is
coupled to a central hub that connects two or more flexure arms, in some
variations the deflecting structure may
include multiple accelerometers, with each accelerometer coupled to a
respective flexure arm. For example, as
shown in FIGS. 9A-9C, an exemplary variation of a vibroacoustic sensor module
900 may include a deflecting
structure 920 having multiple flexure arms 924 arranged radially around a
central hub 926, and accelerometers
932 located on the outer or distal ends of the flexure arms 924. In some
variations, the deflecting structure 920
may include a handle portion 950 may be handheld (and/or be used to secure to
another portion of the sensing
device). The flexure arms 924 may be wavy (e.g., sinusoidal or arched) and/or
equally radially arranged around
the central hub 926, similar to that described above. In this variation, as
shown in FIG. 9D, a flexible circuit
board 930 may be coupled to each flexure arm 924 and shaped in a similar
manner as its respective flexure arm
924. Furthermore, in some variations, the vibroacoustic sensor module 900 may
include a receiver (e.g., dome-
shaped diaphragm) coupled to the central hub 926 of the deflecting structure.
Similar to the vibroacoustic sensor
modules described above, the central hub 926 may move out-of-plane in response
to vibroacoustic signals,
which may result in a set of corresponding out-of-plane movements of the
accelerometer mounts 928 effected
by the flexure arms 924 that are detectable by the accelerometers 932 on the
outer ends of the flexure arms 924.
11671 Although the vibroacoustic sensor module 900 is shown in FIGS. 9A and 9B
as including a deflecting
structure with three flexure arms, it should be understood that the deflecting
structure may include more than
three (e.g., four, five, six, or more than six) flexure arms arranged around
the central hub, each flexure arm
having a respective accelerometer arranged thereon.
Membrane-type vibroacoustic sensor modules
[168] in some variations, the deflecting structure may include a membrane, and
one or more sensors may be
arranged to interface with the membrane to detect the membrane's out-of-plane
movement in response to
vibroacoustic signals. For example, as shown in FIGS. 10A and 10B, a
vibroacoustic sensor module 1000 may
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include a deflecting structure 1020 having a membrane 1024 extending across a
frame 1022, and an
accelerometer 1032 coupled to a central region of the membrane 1024 via a
flexible circuit board 1030. The
membrane may comprise a thin sheet or diaphragm of flexible material that is
taut over the frame 1022, such as
an elastomeric material (e.g., latex, nitrile, etc.). In some variations, the
membrane may be coupled to the frame
1022 with one or more suitable fasteners, such as a clamp ring 1025 that
radially compresses and secures the
membrane 1024 to the frame 1022, other suitable fasteners (e.g., epoxy) or in
any other suitable manner. In
some variations, FEM design optimization models suggest an optimal membrane
thickness range of 10 to 5000
micrometers and diameter between about 2.5 millimeters and about 75
millimeters. One goal of the membrane
is to enable collection of high data fidelity while providing a comfortable,
non-irritating data harvest interface.
The membrane material may be configured to deform naturally with low amplitude
movements of the body. For
example, in some variations, the membrane design may incorporate deformable,
non-coplanar interconnects, a
strain-isolation layer at the base, a soft-encapsulation overlayer and/or a
hollow air-pocket configuration.
Together, these features may provide low-modulus, elastic mechanics for
ultrasensitive signal pickup.
[169] Similar to the flexure anna-based variations of vibroacoustic sensor
modules described above, the
vibroacoustic sensor module 1000 may include a flexible circuit board 1030
that is flexible and receptive to out-
of-plane forces. For example, FIGS. 10A and 10B depict a flexible circuit
board 1030 that has a zig-zag shape
similar to that shown in FIG. 6B, but it should be understood that the
flexible circuit 1030 may alternatively
have a spiral shape (such as that shown in FIG. 5H) or any suitable shape. The
flexible circuit board 1030 may
have an inner end having an accelerometer 1032 and an outer end having a cable
connector 1034, with
conductive traces extending between the accelerometer 1032 and the cable
connector for signal communication
to and from the accelerometer 1032. In some variations, at least the inner end
the flexible circuit board 1030
may be coupled to the membrane with epoxy or any other suitable fastener or in
any suitable manner.
Accordingly, movement of the membrane 1024 may be tracked and measured by the
accelerometer 1032, and
corresponding vibroacoustic sensor signals from the accelerometer 1032 may be
analyzed such as for detecting
one or more bodily conditions of a subject.
11701 Additionally or alternatively, in some variations, a vibroacoustic
sensor module may include a
membrane-based deflecting structure that interfaces with or interacts with one
or more sensors across a cavity.
For example, as shown in FIGS. 11A and 11B, a vibroacoustic sensor module 1100
may include a deflecting
structure 1120 having a cavity 1126 that is sealed by a membrane 1124
extending across a frame 1122. In some
variations, the deflecting structure 1120 may include a handle portion 1150
may be handheld (and/or be used to
secure to another portion of the sensing device).
[171] The membrane 1124 may be constructed and attached in a manner similar to
that described above with
respect to FIGS. 10A and 10B. Furthermore, FIGS. 11C-11E depict an exemplary
rigid circuit board 1130
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including one or more sensors 1132 and a cable connector 1134. Signals to and
from the sensor(s) 1032 may be
communicated via conductive traces extending between the sensor(s) 1132 and a
cable connector 1134. As
shown in FIGS. 11A and 11B, the rigid circuit board 1130 may be positioned in
the vibroacoustic sensor module
1100 such that the one or more sensors 1132 are located within or adjacent the
cavity (or otherwise arranged in
fluid communication with the cavity, such as through an opening). For example,
as shown in FIG. 11A, a sensor
1132 may be located opposite the membrane 1124. In such arrangements,
deflection of the membrane 1124 in
response to vibroacoustic waves may cause changes within the cavity that are
detectable and measurable by the
one or more cross-axis inertial sensors 1132. For example, in some variations
the one or more sensors 1132 may
include a pressure sensor (e.g., MEMS pressure sensor) that detects pressure
variations in the cavity induced by
the deflection of the membrane 1124. For example, the pressure sensor may be
read at a high rate (e.g., more
than about 500 Hz) and the pressure data may be used to construct a low
frequency signal waveform (e.g.,
between about 0.01 Hz to about 1 kHz; or about 0.01 Hz to about 0.5 kHz). As
another example, in some
variations the one or more sensors 1132 may include a microphone (e.g., MEMS
microphone) that detects
vibroacoustic waves traversing the cavity and induced by deflection of the
membrane 1124. The microphone
may be configured to sense a different bandwidth, such as between about 5 Hz
to about 2 kHz ¨ 10 kHz.
[172] Furthermore, in some variations, the one or more sensors 1132 may
include both a pressure sensor and
a microphone, and/or any other suitable sensors (e.g., voice coil transducer,
piezoelectric transducer, etc.).
[173] In some variations, a vibroacoustic sensor module may include a
dampening feature to help isolate the
sensing components from hand movements that may introduce noise and/or error
into the acquired vibroacoustic
signals. For example, FIGS. 12A and 12B depict a variation of a vibroacoustic
sensor module 1200 that is
similar to that described above with reference to FIGS. 10A and 10B, in that
the vibroacoustic sensor module
1200 may include a deflecting structure 1220 having a cavity 1226 that is
sealed by a membrane 1224 extending
across a frame 1222. The deflecting structure 1220 may include an annular
handle portion 1250 that is indirectly
coupled to the central frame 1212 via a flexible layer 1228 and/or other
suitable flexible structures that help
isolate the sensing components (e.g., sensor(s) 1232, membrane 1224, etc.)
from hand pressure and other
movement variations. The flexible layer 1228 may, for example, include a
dampening material such as foam or
an clastomeric material, and/or include dampening structures such as radial
ribs that help dampen and/or
decouple movements from the handle 1250 from the rest of the deflecting
structure. The dampening could also
be implemented in other "active" ways with one or more controlled mechanisms
or materials, such as actuators
(e.g., micro- and or servo motors), piezoelectric or electrosensitive
polymers, etc.
Combination-type vibroacoustic sensor modules
[174] Furthermore, in some variations, a vibroacoustic sensor module may
combine aspects of any of the
above-described variations, such as to integrate multiple sensors for
detecting vibroacoustic sensors in the same
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sensor module. For example, as shown in FIGS. 13A-13C, an exemplary variation
of a vibroacoustic sensor
module 1300 may include a variety of components enabling integration of an
accelerometer and a microphone
for a broader sensing bandwidth. For example, the vibroacoustic sensor module
1300 may include a deflecting
structure 1320 including a membrane 1324 that interacts with both an
accelerometer 1342 coupled to the
membrane 1324 via a rigid or semi-rigid coupling disc 1344. The membrane 1324
may be tensioned over and
attached to a support ring 1326, and the support ring 1326 may be attached to
the frame 1322. Furthermore, the
coupling disc 1324 may, for example, be coupled to the membrane 1324 with
epoxy or another suitable kind of
fastener, and simultaneously coupled to a portion of a flexible circuit board
1340 that includes the accelerometer
1342. Similar to that described above with respect to flexure arm- type sensor
modules, movement of the
membrane 1324 may be detected and measured by the attached accelerometer 1342
and translated into a
vibroacoustic signal.
[175] Furthermore, similar to that described above with membrane-type sensor
modules, the membrane 1324
may extend over a cavity, and interface with a microphone sensor 1332 via the
cavity. For example, the
vibroacoustic sensor module 1300 may include a rigid circuit board 1330 having
a microphone sensor 1332
configured to detect vibroacoustic signals transmitted across the membrane
1324 and the cavity. Additionally,
or alternatively, the rigid circuit board 1330 may include a pressure sensor
and/or other suitable sensor (e.g.,
voice coil transducer, piezoelectric transducer, etc.).
[176] In some variations, a combined-type sensor module may include a handle
portion for enabling manual
manipulation of the sensor module. For example, as shown in FIG. 14, a
vibroacoustic sensor module 1400 may
include an accelerometer and a microphone for detecting and measuring
vibroacoustic waves, and may be
similar to the vibroacoustic sensor module 1400, except that the vibroacoustic
sensor module 1400 may include
a handle portion 1450 having a flange-like gripping feature. However, other
variations may include a handle
portion having any suitable shape.
[177] in some variations, a vibroacoustic sensor module may include a variety
of components enabling
integration of an accelerometer and a pressure sensor. For example, as shown
in FIG. 15, an exemplary variation
of a vibroacoustic sensor module 1500 may include one or more accelerometers
1532 arranged on respective
flexure arms 1524 (e.g., similar to the vibroacoustic sensor module 900
described above with reference to FIGS.
9A-9D), and a membrane whose deflection is measurable with a pressure sensor
1532 (e.g., similar to that
described above with respect to FIGS. 11A and 11B.
[178] Furthermore, it should be understood that other variations of
vibroacoustic sensor modules may include
combinations of different aspects of the above-described variations, such as
to accommodate different kinds
sensors capable of providing vibroacoustic signals (e.g., for various
bandwidths or frequency ranges) and/or for
use in different sensing device form factors and applications, etc.
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Voice coil transducer
[179] As described above, in some variations, the vibroacoustic sensor module
may include a voice coil
transducer alone or in combination with any of the above-described sensors
and/or other suitable sensors. For
example, FIGS. 16A -16C depict an exemplary variation of the voice coil
transducer 1600. The voice coil
transducer 1600 comprises a frame 1610 (also referred to as a magnet housing
or a surround pot) having a
cylindrical body portion 1620 with a bore 1630, and a flange 1640 extending
radially outvvardly from the
cylindrical body portion 1620. The frame 1610 may be made of steel. An iron
core 1650 such as soft iron or
other magnetic material is attached to the cylindrical body portion 1620 and
lines the bore 1630 of the cylindrical
body portion 1620. As can be seen, the iron core 1650 extends around the bore
1630 of the cylindrical body
portion 1620 as well as across an end 1660 of the cylindrical body portion
1620. The iron core 1650 has an open
end. A magnet 1670 is positioned in the bore 1630 and is surrounded by, and
spaced from, the iron core 1650
to define a magnet gap 1680. A voice coil 1690, comprising one or more layers
of wire windings 1692 supported
by a coil holder 1693, is suspended and centered in relation to the magnet gap
1680 by one or more spiders
1695. The wire windings 1692 may be made of a conductive material such as
copper or aluminum. A periphery
of the spider is attached to the frame 1610, and a center portion is attached
to the voice coil 1690. The voice
coil 1690 at least partially extends into the magnet gap1680 through the open
end of the iron core 1650. The
one or more spiders 1695 allow for relative movement between the voice coil
1690 and the magnet 1670 whilst
minimizing or avoiding torsion and in-plane movements. A diaphragm (not shown
in FIG. 16) is provided which
may be attached to the voice coil transducer 1600. The diaphragm may be
equated to the diaphragm 450. In
steady state, when no pressure is being applied to the diaphragm, the voice
coil 1690 may be positioned such
that it is not fully received in the magnet gap (off-center in respect to
optimal placement within the magnet gap).
In other words, at least some of the wire windings 1692 supported by a coil
holder 1693 of the voice coil 1690
are positioned outside of the magnet gap when not in use. In use, the voice
coil 1690 can be pushed into the
magnet gap to center it when pressure is applied to the diaphragm under normal
use.
[180] In certain embodiments, an optimal positioning of the voice coil 1690
relative to the magnet gap, when
the voice coil transducer 1600 is in use, is determined by determining an
average force used to hold or place the
voice coil transducer 1600 on skin and/or and clothing and deriving a
displacement distance of the voice coil
1690 relative to the magnet gap when the average force is applied to the
diaphragm 450. Based on an optimal
positioning of the voice coil 1690 in the magnet gap in use, a default "not in
use" position of the voice coil 1690
is deten-nined such that when no pressure is being applied, the voice coil
1690 extends out of the magnet gap
by the determined displacement distance. In this way, in use, when the average
force is applied to the diaphragm
by holding it against skin or clothing, the voice coil 1690 is moved into the
magnet gap to the optimal positioning
to increase or maximize signal-to-noise ratio as well as reduce or minimize
non-linearities. This is in part
possible as the present technology provides a decoupled solution in which the
position of the voice coil 1690
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can be adjusted relative to the magnet gap. The applied pressure may also be
used to tune the impedance
matching between sensor and subject.
[181] A dust cap 1697 may be provided over the open end to prevent foreign
object access. The voice coil
transducer 1600 of FIGS. 16A-C may be incorporated into any of the sensing
devices described herein, such as
the sensing device 400 of FIGS. 4A ¨ 4F. The attachment of the diaphragm to a
portion of the voice coil
transducer 1600 (such as the cylindrical body portion 1620) may be by any
suitable attachment means such as
by adhesive. Alternatively, the diaphragm and the voice coil 1690 may be made
as a single piece. In any of
these variations, an outer cover (not shown) may be provided on top of the
diaphragm to seal any openings
between the diaphragm and the frame 1610. The outer cover may be made of an
elastomeric material such as
rubber. The outer cover may be configured to be attached to a housing (not
shown in FIG. 16, but similar for
example to the housing 310 or the housing 410). The outer cover may have a one-
piece configuration. The voice
coil transducer 1600 may be configured to be positioned within the housing so
that rotational movement of the
frame 1610 relative to the housing is limited. This may be achieved by means
of inter-engaging elements
between the frame 1610 and the housing, such as notches and spigots.
[182] In use, the sensing device 400 or the sensing device 300 can be used to
detect acoustic signals of the
subject by either coupling the diaphragm 450 or outer cover of the sensing
device 400 to skin or clothing of the
subject, or by positioning the subject and the sensing device 400 proximate to
one another. Movements induced
in the acoustic waves will cause the diaphragm 450 to move, in turn inducing
movement of the voice coil 1690
within the magnet gap, resulting in an induced electrical signal.
[183] In certain variations of the voice coil transducer, the configuration of
the transducer is arranged to pick
up more orthogonal signals than in-plane signals, thereby improving
sensitivity. For example, the one or more
spiders are designed to have out-of-plane compliance and be stiff in-plane.
The same is true of the diaphragm
whose material and stiffness properties can be selected to improve out-of-
plane compliance. The diaphragm
may have a convex configuration (e.g. dome shaped) to further help in
rejecting non-orthogonal signals by
deflecting them away. Furthermore, signal processing may further derive any
non-orthogonal signals e.g. by
using a 3 axis accelerometer. This either to further reject non-orthogonal
signals or even to particularly allow
non-orthogonal signals through the sensor to derive the angle of origin of the
incoming acoustic wave.
[184] It will be appreciated that different uses of the sensing device may
require different sensitivities and
face different noise / signal ratios challenges. For example, higher
sensitivity and increased signal/noise ratio
will be required for clothing contact uses compared to direct skin contact
uses. Similarly, higher sensitivity and
increased signal/noise ratio will be required for non-contact uses compared to
contact uses.
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[185] Therefore, in order to provide sensing devices having sensitivities and
signal/noise ratios suitable for
different form factors (e.g. contact or non-contact uses), developers have
discovered that modulation of certain
variables can optimize the voice coil transducer for the specific intended
use: magnet strength, magnet volume,
voice coil height, wire thickness, number of windings, number of winding
layers, winding material (e.g. copper
vs aluminum), and spider configuration. This is further explained in Example
6.
[186] In certain variations, the voice coil 1690 is configured to have an
impedance of more than about 10
Ohms, more than about 20 Ohms, more than about 30 Ohms, more than about 40
Ohms, more than about 50
Ohms, more than about 60 Ohms, more than about 70 Ohms, more than about 80
Ohms, more than about 90
Ohms, more than about 100 Ohms, more than about 110 Ohms, more than about 120
Ohms, more than about
130 Ohms, more than about 150 Ohms, or about 150 Ohms. This is higher than a
conventional heavy magnet
voice coil transducer which has an impedance of about 4-8 Ohms. This is
achieved by modulating one or more
of the number of windings, wire diameter, and winding layers in the voice
coil. Many permutations of these
parameters are possible, and have been tested by the developers, as set out in
Example 6. In one such variation,
the voice coil comprises fine wire and was configured to have an impedance of
about 150 Ohms, and associated
lowered power requirement, by increasing the wire windings.
[187] Developers also discovered that adaptation of the configuration of the
spider 1695 contributed to
increasing sensitivity and signal/noise ratio increases. More specifically, it
was determined via experiment and
simulation that making the spider more compliant such as by incorporating
apertures in the spider 1695,
increased sensitivity. Apertures also allow for free air flow. These are
described in further detail below in
relation to FIGS. 17 and 18.
[188] The use of voice-coil based transducers for present uses is unintuitive,
such as but not limited to contact
with a body and/or the capture of sound below the audible threshold. Voice
coils are commonly used in audio
speaker systems and are optimized for the translation of electrical energy to
acoustical energy. To achieve
useful sound pressure levels, these audio speaker voice coils must be capable
of handling high power in the
range of 10 to 500 watts. The design considerations employed for this make
them inappropriate for microphony
or general sensing applications. Since electrical power can be described by
the equation P = IV = V2/R, low
resistance voice coils allow for high power handling at relatively low
voltages, that are compatible with the
power semiconductors typically used in audio amplifiers. In fact, most
manufacturers of audio equipment note
the ability of their amplifiers to drive low impedance speaker loads as
advantages. While a high turn number,
high impedance coil would be more efficient in terms of force generated for a
unit current, the voltage required
to drive such a current would require bulky insulation that would interfere
with thermal management. While
ferrofluid cooling is a possible solution, the viscosity of such fluids reduce
sensitivity. Of course, when high
power amplifiers are available, that is not an issue. Therefore, low impedance
speakers, such as 8- and 4-Ohm
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models are relatively common. These are characterized by heavy voice coils and
magnet structures built to
accommodate the heavy windings that these coils comprise. Noise may also be a
factor: temperature induced
thermal noise increases with higher impedance of a conductor/resistor.
[189] Moreover, in order to maintain reasonable efficiency at low frequencies
of around 20 Hz, woofers and
subwoofers typically use very heavy cones, so voice coil mass is not a
critical issue. Contrary, tweeters need
light voice coils to enable reasonable efficiency in air-diaphragm impedance
matching using small diaphragms
with higher frequency bandwidth, and are therefore very inefficient when
operating at low frequencies.
Tweeters typically have very light and delicate diaphragms as well, thus are
not suitable for direct contact
m icrophony. .
[190] Crossover circuitry is also usually necessary in order to achieve wide
frequency response of audio
speakers operating between 20 Hz and 20 kHz due to the need of two-way and
three-way transducer speaker
designs.
[191] However, conventional microphones typically operate under totally
different conditions, where low
sound pressure levels need to be picked up with a minimum of noise. To such
end, they are typically constructed
with low weight diaphragms and the best microphones typically need external
power sources as they operate as
variable capacitors rather than as true voice coil/magnetic gap transducers.
Again, just like tweeters, the delicate
diaphragms of sensitive microphone designs are not suitable for direct contact
microphony due to their fragility.
Owing to their method of operation, they also suffer from low dynamic range
and high natural resonance
frequencies.
[192] Therefore, the discovery that an adapted voice coil transducer can be
used as a biosignal microphone
was a surprising development by the Developers. In certain variations of the
present technology, it was
discovered that by adapting the configurations of at least the voice coil and
the spider of a traditional heavy
magnet structure audio speaker, it was possible to achieve a microphone with a
higher sensitivity, broader
frequency range detection capabilities, dynamic and tuneable frequency range,
and high signal to noise
characteristics. In certain variations, a single voice coil transducer of the
current technology can provide a
microphonic frequency response of less than about 1 Hz to over about 150 kHz
or about 0.01 Hz to about 160
kHz
[193] Furthermore, the use of such a vibroacoustic sensor module also enabled
the size of the vibroacoustic
sensor module to be kept to a practical minimum for hand-held applications.
These combinations of changes
allowed for relatively higher voltage generation by the voice coil in response
to vibroacoustic signals than would
be possible using typical audio speaker voice coils. Consequently, the sensing
of these voltages can be
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accomplished with low-noise J-FET based amplifiers, for example, to achieve
the desired combination of
frequency response, dynamic range, spurious signal rejection and signal to
noise ratio.
[194] In certain variations of the present technology, the voice coil
transducer 1600 comprises a single layer
of spider 1695 (FIG. 16C). In certain other variations of the present
technology, the voice coil transducer 1600
comprises a double layer of the spider 1695 (FIG.16D). Multiple spider 1695
layers comprising three, four or
five layers, without limitation, are also possible.
[195] Certain configurations of the spider 1695 are illustrated in FIGS. 17
and 18A-18AB. As can be seen,
instead of a one-piece corrugated continuous configuration as is known in
conventional spiders of conventional
voice coils, in certain variations of the current technology, the spider 1695
has a discontinuous surface. The
spider 1695 may comprise at least two deflecting structures 1700 which are
spaced from one another, permitting
air flow therebetween. In certain configurations, the deflecting structures
1700 comprises two or more arms
1710 extending radially, and spaced from one another, from a central portion
1720 of the spider 1695. In the
variation illustrated in FIGS. 17A and B, and 18B the deflecting structure
1700 comprises four arms 1719
extending radially from the central portion 1720. The four arms 1710 increase
in width as they extend outwardly.
Each of the arms 1710 has a corrugated configuration. An aperture 1730 between
each of the arms 1710 is larger
than an area of each deflecting arm.
[196] FIGS. 18A-AB show other variants of a spider 1800 for a voice coil
transducer, such as the voice coil
transducer 1600. The spider comprises a deflecting structure 1800 comprising
one or more arms 1810 extending
from a central portion 1820 and defining apertures 1830 therebetween. The one
or more arms 1810 may be
straight or curved. The one or more arms 1810 may have a width which varies
along its length, or which is
constant along its length. The one or more arms 1810 may be configured to
extend from the central portion
1820 in a spiral manner to a perimeter 1840 of the spider 1800. A solid ring
may be provided at the perimeter
1840 of the spider 1800_ This has been omitted from FIGS 18A-AB for clarity,
but can be seen in FIG. 16E. In
certain variations, there may be provided a single arm 1810 configured to
extend as a spiral from the central
portion 1820 of the spider 1800 to the perimeter 1840 of the spider 1800. In
these cases, turns of the spiral arms
1810 define the apertures 1830. The spider 1800 may be defined as comprising a
segmented form including
portions that are solid (the arm (s) 1810) and portions which are the
aperture(s) 1830 defined therebetween. The
anus 1810 may be the same or different (e.g. FIG. 18C). In variants where more
than one layer of the spider
1800 is provided in the voice coil transducer, the spiders 1800 of each layer
may be the same or different.
[197] The configuration chosen for a given use of the sensing device will
depend on the amount of compliance
required for that given use. For example, a voice coil configuration of low
compliance may be chosen for contact
applications than non-contact applications. For contact applications, spider
may be coupled to the voice coil in
such a way as to off-set the voice coil from the magnet gap when there is no
pressure applied to the diaphragm,
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and when the expected pressure is applied to the diaphragm, the voice coil
will be pushed into the magnet gap
for optimum positioning and acoustic signal detection.
[198] In certain variations, a compliance of the diaphragm may range from
about 0.4 to 3.2 mm/N. The
compliance range may be described as low, medium and high, as follows:
= 0.4 mm/N: low compliance -> fs around 80-100 Hz;
= 1.3 mm/N: medium compliance-> fs around 130 Hz;
= 3.2 mm/N: high compliance -> fs around 170 Hz.
[199] In some variations, two or more voice coil sensors may be included in
the sensing device (e.g., in the
vibroacoustic sensor module) which may enable triangulation of faint body
sounds detected by the voice coil
sensors, and/or to better enable cancellation and/or filtering of noise such
as environmental disturbances. Sensor
fusion data of two or more voice coil sensors can be used to produce low
resolution sound intensity images.
[200] In some variations, the voice coil transducer may be optimized for
vibroacoustic detection, such as by
using non-conventional voice coil materials and/or winding techniques. For
example, in some variations, the
voice coil material may include aluminum instead of conventional copper.
Although aluminum has a lower
specific conductance, overall sensitivity of the voice coil transducer may be
improved with the use of aluminum
due to the lower mass of aluminum. Additionally, or alternatively, the voice
coil may include more than two
layers or levels of winding (e.g., three, four, five, or more layers or
levels), in order to improve sensitivity. In
certain variants, the wire windings may comprise silver, gold or alloys for
desired properties. Any suitable
material may be used for the wire windings for the desired function. In
certain other variants, the windings may
be printed, using for example conductive inks onto the diaphragm.
[201] Advantageously, certain variants of the present technology can be used
as a standalone stethoscope or
addition to a traditional acoustic stethoscope or appendage to a smartphone or
phonocardiogram device to detect
infrasound-to-ultrasound vibroacoustic signals from the subject. The sensing
device may have any suitable form
factor for contact or contactless vibroacoustic detection. The vibroacoustic
sensor module of certain variants of
the present technology has advantages over conventional acoustic and
electrical stethoscopes which are used to
detect acoustic signals relating to the subject.
12021 Firstly, the present technology can be deployed for contactless
applications such as remote monitoring.
On the other hand, traditional acoustic stethoscopes require contact with the
skin of the subject for adequate
sound detection.
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[203] Secondly, acoustic signals can be detected over a broad range and with
good signal to noise ratios.
Conversely, traditional acoustic stethoscopes have poor sound volume and
clarity as they convert the movement
of the stethoscope diaphragm into air pressure, which is directly transferred
via tubing to the listener's ears by
inefficient acoustic energy transfer. The listener therefore hears the direct
vibration of the diaphragm via air
tubes.
[204] The current technology also has advantages over conventional electrical
stethoscope transducers, which
tend to be one of two types: (1) microphones mounted behind the stethoscope
diaphragm, or (2) piezo-electric
sensors mounted on, or physically connected to, the diaphragm.
[205] Microphones mounted behind the stethoscope diaphragm pick up the sound
pressure created by the
stethoscope diaphragm, and convert it to electrical signals. The microphone
itself has a diaphragm, and thus the
acoustic transmission path comprises or consists of a stethoscope diaphragm,
the air inside the stethoscope
housing, and finally the microphone's diaphragm. The existence of two
diaphragms, and the intervening air
path, can result in excess ambient noise pickup by the microphone, as well as
inefficient acoustic energy transfer.
This inefficient acoustic energy transfer is a prevalent problem in the below-
described electrical stethoscopes.
Existing electronic stethoscopes use additional technologies to counteract
this fundamentally inferior sensing
technique, such as adaptive noise canceling and various mechanical isolation
mountings for the microphone.
However, these merely compensate for the inherent inadequacies of the acoustic-
to-electrical transducers.
[206] Piezo-electric sensors operate on a somewhat different principle than
merely sensing diaphragm sound
pressure. Piezo-electric sensors produce electrical energy by deformation of a
crystal substance. In one case,
the diaphragm motion deforms a piezoelectric sensor crystal mechanically
coupled to the diaphragm, resulting
in an electrical signal. The problem with this sensor is that the conversion
mechanism can produce signal
distortion compared with sensing the pure motion of the diaphragm. The
resulting sound is thus somewhat
different in tone, and distorted compared with an acoustic stethoscope.
[207] Capacitive acoustic sensors are in common use in high-performance
microphones and hydrophones. A
capacitive microphone utilizes the variable capacitance produced by a
vibrating capacitive plate to perform
acoustic-to-electrical conversion. A capacitive microphone placed behind a
stethoscope diaphragm would suffer
from the same ambient noise and energy transfer problems that occur with any
other microphone mounted
behind a stethoscope diaphragm.
[208] Acoustic-to-electrical transducers operate on a capacitance-to-
electrical conversion principle detecting
diaphragm movement directly, converting the diaphragm movement to an
electrical signal which is a measure
of the diaphragm motion. Further amplification or processing of the electrical
signal facilitates the production
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of an amplified sound with characteristics very closely resembling the
acoustic stethoscope sound, but with
increased amplification, while maintaining low distortion.
[209] This is a significant improvement over the more indirect diaphragm sound
sensing produced by the
microphonic or piezoelectric approaches described above. Since the diaphragm
motion is sensed directly, the
sensor is less sensitive to outside noise, and the signal is a more accurate
measure of the diaphragm movement.
With an acoustic stethoscope, diaphragm movement produces the acoustic
pressure waves sensed by the
listener's ears. With an acoustic-to-electrical sensor, that same diaphragm
movement produces the electrical
signal in a direct manner. The signal is used to drive an acoustic output
transducer such as earphones or
headphones, to set up the same acoustic pressure waves impinging on the
listener's ears.
[210] While acoustic-to-electrical transducers overcome many of the inherent
problems faced by earlier
stethoscope designs, it adds considerable white noise to the signal. White
noise is a sound that contains every
frequency within the range of human hearing (generally from 20 Hz to 20 kHz)
in equal amounts. Most people
perceive this sound as having more high-frequency content than low, but this
is not the case. This perception
occurs because each successive octave has twice as many frequencies as the one
preceding it. For example,
from 100 Hz 10 200 Hz, there are one hundred discrete frequencies. In the next
octave (from 200 Hz to 400 Hz),
there are two hundred frequencies.
[211] As a result, the listener has difficulty discerning the human body sound
from the white noise. For sounds
of the body with higher intensities (i.e., louder sounds) the listener can
hear the body sounds well, but lower-
intensity sounds disappear into the background white noise. This is not the
case in certain variations of the
present technology.
Echo sensor-based vibroacoustic modules
[212] Variants of the system 10 or the sensing device 110 may include one or
more echo sensor based
vibroacoustic modules, such as but not limited to one or more of: echo sensors
based on Continuous Wave
Doppler (CWD), Pulsed Wave Doppler (PWD), and Time-of-Flight.
[213] Continuous Wave Doppler (CWD): A continuous ultrasound signal is
emitted by a source oscillator,
reflected of a subject and back into a receiver. Vibrations on the subject
change the frequency/phase of the
emitted Ultrasound signal which allows to retrieve the original vibration
signal. This offers maximum sampling
frequency of the subject under investigation.
[214] Pulsed Wave Doppler (PWD): Short ultrasound bursts are sent, and
receiver waits for response. This
technique can resolve subject vibrations like the CWD, but due to the burst
interval introduces a sampling
frequency of the subject. The Nyquist frequency of the corresponding sampling
frequency is (pulses per
second)/2. Hence with one pulse every millisecond the maximum resolved subject
vibration frequency is 500Hz.
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However, the PWD can resolve vibrations at a specific depth, or distance from
the emitter/sensor. This is
achieved by taking the time-of-flight information of the pulse into account
and reject signals that outside the
desired distance. Hence, the PWD can reject signals outside the target
distance; signals that either are created
by other sources or the emitted pulse that has traveled beyond the subject and
reflected of a wall.
[215] Time-of-Flight: A simpler version compared to the PWD is a pulsed
ultrasound signal where only the
time-of-flight is considered.
[216] Advantageously, these echo-based modules can permit measurement of
vibrations (such as
vibroacoustic signals from the subject), as well as distance or velocity. The
echo-based modules are non-contact,
non-invasive and not harmful to the subject. Vibroacoustic signals can be
detected from a distance of about 1
cm to about 10 meters, in certain variations. A detection distance may be
about 10 meters, about 9 meters, about
8 meters, about 7 meters, about 6 meters, about 5 meters, about 4 meters,
about 3 meters, about 2 meters or
about 1 meter. Signal detection can be performed through clothing or other
apparel of the subject. Furthermore,
signal detection over a broad spectrum can be obtained.
[217] The echo based acoustic systems broadly comprise an emitter component
and a receiver component and
are active systems which rely on the receiver component detecting a signal
from the subject responsive to an
emitted signal by the emitter incident on the subject. Therefore, in certain
variations, emission signals within
the ultrasound range are used, preferably above 25 kHz to keep some headroom
to the end of the audible
spectrum (as it is not desirable to use emission signals within the audible
range). On the higher end, the
maximum may be around 100 kHz due to ultrasonic signal absorption in air and
ADC sampling rates. At 50
kHz the acoustic absorption in air is about 1-2 dB/m, at 100 kHz about 2-5
dB/m, at 500 kHz about 40-60 dB/m
and at 1Mhz about 150-200 dB/m. Technological challenges at higher frequencies
involve the ability to capture
the signal in sufficient quality, such as the availability of fast Analog-to-
Digital converters.
[218] The number of emitter components and receiver components in the echo
sensor module is not limited.
Different combinations may be used as will be explained in further detail with
reference to FIGs. 33D-H. For
example, there may be provided a single emitter component and a single
receiver component; or two emitter
components and a single receiver component; or single emitter component and
two receiver components; or two
emitter components and two receiver components.
[219] The emitter component can be any type of emitter configured to emit an
ultrasound signal. Emitters
should possibly be as unidirectional as possible. One example is the Pro-Wave
Electronics 400ET/R250 Air
Ultrasonic Ceramic Transducer.
[220] The receiver component can be of any receiver type configured to detect
the emitted ultrasound signal
from the subject. In certain variations, the receiver component can be a
microphone capable of capturing the
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ultrasound signal with sufficient signal-to-noise ratio. This could include
any type of microphone such as
condenser, dynamic or MEMS microphones. In certain variations, Ultrasound
capable MEMS microphones are
preferred due to compactness. In other variations, the receiver component is a
specialized Ultrasound receiver
that is tuned to that frequency. In certain variations, the receiver component
is as unidirectional as possible.
Examples of receiver components include the Pro-Wave Electronics 400ST/R100
Transducer; the Pro-Wave
Electronics 400ST/R160 Transducer; or Invensense ICS-41352.
1.c.iii. Examples of other sensors
[221] According to certain variations, the system 100 may include sensor
modules, other than the
vibroacoustic sensor modules described above. The one or more other sensor
modules may be incorporated
within a housing of the sensing device, or may be separate and connected
thereto.
Bioelectric-based sensor module
[222] In certain variations of the system 10, such as the sensing device 400,
there is also provided a
bioelectric-based sensor module. In certain variations, the bioelectric-based
sensor module is configured to
detect electrical impulses on the skin of the subject. These may be
representative of electrical impulses in the
nerves of the heart tissue of the subject. The bio-electric based sensor
module can therefore function as an ECG
module, and is therefore referred to herein as an ECG sensor module. The ECG
sensor module may indicate
bodily conditions, such as: trauma to the nervous tissue network of the heart;
damage to the heart tissue such as
from a prior heart attack or infection, severe nutritional imbalances, stress
from excessive physiological or
psychological pressure.
[223] For example, as illustrated in FIG. 4B, in certain variations, the
sensing device 400 of the sensing
module comprises capacitive sensor electrodes such as the Electrical Potential
Integrated Circuit (EPIC)
electrodes 460 and the Driven right Leg (DRL) electrodes 470.
[224] FIG.19 illustrates the basic circuit of the ECG sensor module. The
operation can be described as follows.
[225] The dipole is the elemental unit of cardiac activity. Each dipole
consists of a positive (+) and negative
(¨) charge generated by the action of ion channels. As activation spreads, the
sources sum together and act as a
continuous layer of sources. Stated simply, an electric dipole consists of two
particles with charges equal in
magnitude and opposite in sign separated by a short distance. In the heart,
the charged particles are ions such as
sodium (Na), potassium (K), calcium (Ca2+), phosphates (P043), and proteins.
The separation is the distance
across the cardiac cell membrane. Because they are too large to pass through
the small cell membrane channels,
the negatively charged particles remain in the cell, whereas the positive ions
move back and forth through
specific channels and -ion pumps" to create polarization and depolarization
across the membrane.
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[226] If enough dipoles are present together, they create a measurable
voltage. Resting cardiac cells within
the heart are normally at ¨70 mV. This means that at rest, there is naturally
a charge imbalance present in the
heart. This imbalance, called polarization of the cell, attracts positive ions
toward the interior of the cell. When
a cardiac cell is activated by an outside stimulus, channels in the cell
membrane activate, and the excess positive
ions outside of the cell rush into the cell. This process, called
depolarization, makes the cell less negatively
charged and is associated with "activation" of the cardiac cell. When millions
of these cells activate together,
the heart contracts and pumps blood to the rest of the body. The combined
activation of these cells generates
enough voltage to be measured on the surface of the skin by an
electrocardiogram (ECG). The resulting
intracardiac electrogram (EGM) extends beyond the area of the dipole signal by
a factor of five, reducing
resolution and acuity.
[227] Variations of the ECG sensor module of the present technology comprise
one or more bio-electric
sensors to measure electrical fields and electrical impulses.
[228] For close coupling (Cext>> Cõ,) this is usually defined by Equation 1:
coEra
Cext = ¨
d
where:
a = the equivalent shared electrode/target area
the distance between target and sensor
Eo the permittivity of free space
Er= the relative permittivity of the dielectric in which
the sensor is operating
[229_1 For remote coupling (Ceit>> C,õ) we have the limiting case (self-
capacitance) shown in Equation 2:
Cext 8 EOEr
where r is the diameter of the sensor plate.
[230] Analysis of the circuit shows us that we have a classic single-pole
transfer function as shown in
Equation 3:
V,(t) Zin
Vin(t) Zõt
[231] The corner frequency (Fc 1) can be expressed in Equation 4:
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1
Fcl ¨ ____________________________________________________
(Cext + Cin)Rin
[232] The input capacitance for the ECG sensor module can be driven as low as
10' F with the input
resistance being boosted to values up to around 101512, thus keeping the
interaction with the target field to an
absolute minimum and ensuring that all currents arc small displacement
currents only. Bootstrapping techniques
control the values for C,õ and R,õ to give effective values, allowing us to
control both the gain plateau and the
corner frequency (Fc 1 moves to Fc2). The response of the ECG sensor module
was optimized via staging design
and positive feedback loops.
[233] The ECG sensor module can be used, as a replacement technology for
traditional wet-electrode ECG
pads, because it requires neither gels nor other contact-enhancing substances.
When the ECG sensor module is
placed on (or in close proximity to) the patient, an ECG signal can be
recovered. The sensor is capable of both
simple "monitoring" ECG as well as making more exacting clinical screening and
pre-diagnostic measurements.
In applications for infectious bodily condition diagnosis, such as for Covid-
19, the ECG sensor module can be
used as a replacement for the traditional twelve-lead ECG, in which electrodes
are placed on the limbs and torso
to achieve a clearer picture of how the patient's heart is working. The ECG
sensor module four-lead array of
electric potential sensors can be used to recreate each and all the 12-lead
ECG traces required with resolution
as good as or better than that achieved using traditional systems. Figure 20
shows a comparison between the
results using variations of the ECG sensor module and using traditional wet
electrodes for leads II and a VL.
The top figure illustrates the control and the lower figure is the
experimental.
[234] Referring now to the DRL electrodes and their operation, with reference
to FIGS. 4B-E, FIGS. 21 and
22.
12351 Driven Right Leg (DRL) is a technology within conventional ECG systems
for attempting to reduce the
noise that is picked up by ECG sensors. DRL is a differential electronic
technique for improving spurious signal
rejection and signal to noise ratio in the acquisition of bioelectric signals.
Typically, this technique is used
during ECG procedures and involves the application of at least one electrode,
in contact with the skin, to the
lower leg of a subject, as shown in Fig. 21. However, the existing technique
cannot be used through clothing,
and is not practical for use in an ambulating patient as it typically requires
a patient to be sitting or lying down,
at least for skin contact electrode placement. Therefore, Developers have
developed the current ECG sensor
module which, in certain variations, does not require attachment to the leg of
the subject, whilst improving
spurious signal rejection and improving signal to noise ratio. In certain
variations, the ECG sensor module
comprises at least one EPIC sensor and at least one DRL sensor.
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[236] According to certain variations of the current technology, a prototype
circuit diagram for the at least
one DRL sensor is shown in FIG. 22A. FIG. 22B shows an experimental set up
involving five DRL electrodes
spaced between and around two EPIC electrodes, with optional guard electrodes.
The guard electrodes provide
grounding which is important when there is direct contact to skin. They
provide a reference of the signal to
system ground when in direct contact with skin; otherwise the ECG signal would
not be detected or be very
noisy. The guard electrodes, as a 3D structure, can also function as a Faraday
cage to provide EMI shielding.
When there is no direct contact with skin (such as with through clothed uses),
that is where the DRL comes in
to provide that reference through capacitive coupling and an active feedback
signal. Then, the guard electrodes
lose their grounding purpose but still offer EMI shielding. It can allow the
switching from DRL to non-DRL
functionalities. In the experimental set-up, the two EPIC electrodes were
spaced about 46 mm apart. The DRL
sensor between the two EPIC sensors was about 21 mm wide. Each DRL sensor
surrounding each EPIC sensor
had an outer dimension of about 15 mm squared.
[237] The gain and phase response of the full circuit model of the DRL
feedback circuit shown in FIG. 22E
was compared to the SPICE ("Simulation Program with Integrated Circuit
Emphasis") simulation using various
numbers of 0.58 mm cloth separators and the results are shown in FIGS. 22C and
22D, showing satisfactory
results with four layers of cloth between the sensor and skin even at 200 kHz.
The DRL feedback circuit
incorporates a twin-T filter, the bioelectric sensor model, 60 Hz noise source
and a simulated ECG signal.
[238] Without being bound to any theory, the EPIC capacitive sensors generally
require some ground
reference to be able to pick up the body electrical signals without being
dominated by noise. Such noise is often
dominated by the 50/60Hz powerline interference. In contact EPIC use, meaning
the ECG sensor setup has
direct contact with the skin, this issue is less relevant as electrically
conductive grounding electrodes can supply
the necessary signal reference to the body. However, when trying to use the
EPIC sensor in a non-contact setup
the missing conductive path to the body introduces challenges. This can be
solved by using a DRL feedback to
the body, either through a direct conductive or non-contact capacitive
electrode. Since the focus of the EPIC
technology is on capacitive (non-galvanic) measurements of body electrical
signals, it makes most sense to feed
back the DRL signal capacitively as well. This allows the integration of DRL
electrodes directly on the
stethoscope nearby the EPIC sensors with the ability to measure electrical
signals through clothing or other
obstacles, and without any conductive path to the skin.
[239] The DRL works by feeding back an amplified signal of the sum or in any
other suitable combination
(i.e. weighted sum. difference, sum of only a subset of sensors, etc.) of two
or more EPIC sensor signals.
Amplification needs proper tuning to cancel the noise picked up by the EPIC
sensors but can be implemented
as an automatic algorithm. Also, there can be a number of combinations on
which and how many EPIC sensor
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signals are combined to create a DRL signal for each of the available DRL
electrodes. This process can as well
be automated.
[240[ In certain variations, advantageously, the EPIC and the DLR electrodes
required for performing an ECG
may be spaced within about 5 cm or less of each other. Furthermore, in certain
variations, advantageously, the
relative disposition of the electrodes provides for increase in spurious
signal rejection and higher signal to noise
in the signal compared to where the DRL electrodes are disposed further away
from each other as they typically
are in existing ECG tests.
Bioimpedance-based sensor modules
[241] Bioimpedance-based sensor modules can be used to detect skin potentials.
Electrodermal activity
(EDA) is a marker of sympathetic network activity. Electrodermal activity is
generated by the sweat glands and
overlying epidermis and mediated by supraspinal sites that include the
orbitofrontal cortex, posterior
hypothalamus, dorsal thalamus, and ventrolateral reticular formation. This
response, which occurs
spontaneously and can be evoked by stimuli such as respiration, cough, loud
sounds, startle, mental stress, and
electrical stimuli, is referred to as the sympathetic skin response or the
peripheral autonomic surface potential.
EDA is composed of two components: (1) the phasic component of the skin
conductance response (SCR), which
is observed after activation of sudomotor fibers, and (2) the skin conductance
level (SCL) which corresponds
to the baseline of the skin conductance specific to a given subject. The SCR
is the component used as a strong
marker of the sympathetic network. It ranges from 0.05 to 1.5 Hz. The EDA
active recording electrode is placed
on the palmar or plantar surface and the indifferent electrode on the volar
surface. With low pass filter settings
of 0.1-2 Hz and high pass filter setting of 1-5 kHz, the latency in the upper
extremity ranges between 1.3 and
1.5 seconds and in the lower extremity between 1.8 and 2.1 seconds.
[242] While ECG and related techniques measure bioelectric signals that
originate within a subject, bio-
impedance measurements, such as galvanic skin response, interrogate the
subject's resistance or response to an
applied electromotive force. Measurement of galvanic skin response
traditionally was a DC measurement
requiring Silver/Silver Chloride electrodes. A general term for DC and AC
measurement is electrodermal
activity (EDA), and bioimpedance for AC-only measurements. An advantage of AC
measurement over DC is
that dry electrodes may be used. In certain variations of the present system
10, non-contact electrodes are
possible, as only an alternating potential needs to be applied to the body to
induce an alternating current in the
body.
[243] The problem of electrode impedance is dealt with by employing a four-
wire measurement topology that
mostly removes the effect of electrode impedance on measurements. Two drive
electrodes force a signal through
the body and two sense electrodes measure the differential voltage. The
impedance is calculated using Ohm's
law: Impedance = sense voltage drive current. The capacitors block DC current
from flowing. RACCESSX
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represent wire & electrode resistances in traditional contact meastu-ements.
Rumir is a safety current limit, to
stay within safety requirements in case of hardware or software failure.
[244[ The typical wet electrode bioimpedance analysis application diagram is
shown in FIG. 22F.
[245] One example sensor for bioimpedance is the AD5940 (Analog Devices, Inc.,
Norwood, MA) (FIG.
22G). The chip can perform AC measurements from sub-Hz up to 200 kHz. However,
the application notes for
this device do not enable the use of dry, or non-contact electrodes, or, of
measurements through clothing.
[246] Here we disclose devices, methods and systems for the measurement of
electrodermal activity (EDA)
and body impedance analysis (BIA) using Electric Potential Integrated Circuit
(EPIC) sensors (such as those
from Plessey Semiconductors Ltd., Roborough, Plymouth Devon), that allow non-
contact, at a distance and
through-clothing measurements. Certain EPIC sensors used within present
systems and devices may include
one or more as described in: U58,923,956; US 8,860,401; US 8,264,246; US
8,264,247; US 8,054,061; US
7,885,700; the contents of which arc herein incorporated by reference. A
schematic diagram is shown in FIG.
22H.
[247] In certain variations, there is provided the AD5940 functions as
described, with the contact sense
electrodes replaced by EPIC sensors. A DRL electrode may also be included, as
with ECG, to prevent or
minimize the sensors from saturating in a 50/60 Hz environment. Capacitive
coupling to the DRL electrode and
coupling to earth can affect the measurements: keeping the sense electrodes
separated from the DRL electrode
will minimize this error source. To couple enough bioimpedance drive current
to the body through a small
capacitance, the AD5940's output is amplified. The EPIC sensors, with a gain
of 10, have their outputs padded
down, to prevent overloading the AD5940's inputs. The DRL filter and amplifier
is the same one described
herein.
[248] In some instances, a non-contact DRL electrode can be used. In other
instances, a transconductance
amplifier, such as a LM13700 OTA, Texas Instruments, Inc., Dallas, TX., can be
used to mitigate variances in
drive electrode capacitance.
Example of bioimpedance analysis using EPIC sensors
[249] The AD5940's drive electrodes were in direct skin contact. Simulations
of the electrodes were run and
a heat map display generated. FIGS. 221 and J show heat map results of two
simulations. The highest voltage
(red) is at the bioimpedance drive electrode. The lowest voltage (green) is
zero volts at the bioimpedance
current-sensing input electrode. The voltage difference between the EPIC
sensors was extracted in the
simulation. In these figures, the difference between active and floating DRL
electrodes is shown. Grounding
the DRL electrodes significantly reduces the sensed voltage. Therefore, for
initial experiments, these electrodes
were left floating.
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[250] FIG. 22K shows the test configuration, consisting of an AD5940 Eval
board, a pair of EPIC sensors, a
DRL circuit, and a (floating) battery supply for the sensors. Electrodes were
fabricated from a 0.8 mm thick
PCB with Copper milled out between the electrodes and openings milled for the
EPIC sensors. Various test
arrangements were created to ascertain system performance. In FIG. 22K, a pair
of conductive cloth squares are
connected by a resistor to create repeatable "skin" resistance.
[251] An alternative "skin", shown in FIG. 22L and FIG. 22M, uses conductive
paper (Eisco Labs
PH0918DFM). The paper is used as a teaching aid for visualizing electric
fields: current is sent through the
paper and voltages are measured along its surface. Progressive layers of
Kapton tape were placed on the paper
over the EPIC sensor areas. These layers were used to compare measurements
with various spacing to the
sensors. FIG. 22L shows the test configuration used for conductive paper and
mesh "skins-: the skin was
clamped firmly against the sensors through compliant foam. The paper was
clamped directly to the driven
electrodes.
Two changes were made to the system as the result of early measurements:
[252] The EPIC sensors were the PS25014A5 model, with a low frequency cutoff
of 30 Hz (not a limitation
for bioimpedance). The DRL electrodes were connected to the bioimpedance drive
electrodes. This increased
contact area, improving measurement consistency.
[253] FIG. 22N and 220 show impedance frequency scans of three "skins":
1. Conductive paper
2. Conductive mesh
3. Forearm
[254] The paper has the highest resistance, around 15 k2, the mesh at 1340 S2,
and the forearm much lower,
in the range 220 ¨ 30 a
[255] The phase plot shown in FIG. 220 shows that the real "skin" ¨ the
forearm, has a large reactive
component. Forearm impedance is lower than expected. This may be attributable
to the large areas for the drive
electrodes. The measured impedance of the 2 kS2 mesh is low by about 20%. This
reflects a lower gain of the
EPIC sensors than expected.
12561 The effects of spacing between the skin and electrodes were tested using
conductive paper (these tests
were run prior to discovering how low the forearm impedance was). The results
are shown in FIG. 22P. The
larger the spacing, the lower the apparent impedance. This is the result of
the EPIC sensor measuring lower
signal levels with increased spacing.
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[257] After consistent measurements were achieved with the synthetic "skins",
testing with a forearm showed
that typical impedances are much lower. Typical body fat bioimpedance
measurements are made with widely
spaced electrodes, which results in higher impedances. Signal levels are lower
with lower impedances, but
repeatable measurements with lower levels are to be reasonably expected.
[258] Even without the DRL signal, the AD5940 seemed unperturbed by 60 Hz
pickup. Between
measurements, the EPIC sensors showed high levels of 60 Hz pickup. When the
measurements started, however,
60 Hz noise level dropped dramatically. This may be due to the drive
electrodes presenting a low impedance
when active. The measurement method used by the AD5940 is also tolerant of 60
Hz interference.
[259] We have developed a software-defined multi-modal sensor fusion and data
fusion platform for
improved data capture and low power/weak biosignals from diverse sensing
modalities modeled after how the
brain, five senses, and central and autonomic nervous systems are intertwined.
This means using vibroacoustic
sensors, electric potential sensors, volatile organic compound e-nose's, heat
and light sensors, and cameras in
the same ways that humans use their nose, eyes, ears and touch to understand
their surroundings intuitively. Our
goal was to develop a sensory modular platform, whereby the entire signal
chain from electromechanical
initiation at cell/tissue level through to mechano-acoustic transduction and
vibroacoustic biosignal data (various
audible and inaudible sounds from the human body) can be used to assess
health. For example, a cough can
signal many things by its length, intensity, frequency, etc. There are >64
human illnesses and diseases with air
and/or fluid movement etiology. We have successfully developed methods for
automated recognition of
respiratory diseases such as COVID-19, pneumonia, asthma, cystic fibrosis, and
chronic obstructive pulmonary
disease (COPD), etc. Additionally, vibroacoustic features such as articulation
rate, effort, and auditory
roughness can give clues to health of an individual, as can the pronunciations
of vowel sounds and other speech
patterns.
Contextual sensor module
[260] Little is known about what happens in real life, how lifestyle and daily
context impacts vital signs, how
quality of life is impacted by disease and medical conditions and to what
degree therapeutic and care
recommendations are actually adhered to. Developers have determined that
putting health data and care into
context of daily life, can in certain variations, add key insights to get
richer and personalized interpretation of
biosignals, vital signs, and wellbeing. In some variations, the system 100 may
further include one or more
sensors providing environmental and/or other contextual data (e.g., social
determinants of health). This may be
used to calibrate and/or better interpret the vibroacoustic data acquired with
the vibroacoustic sensor module,
or any of the other sensor modules. Such data (e.g., environmental and/or
social determinants of health) may,
for example, help contextualize data for more accurate machine learning and/or
Al data analysis. For example,
as shown in FIG. 3B, in some variations, the sensing device 300 may include a
contextual sensor module 330.
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Like the vibroacoustic sensor module 320, the contextual sensor module 330 may
be interchangeable and
modular, such as for use in a variety of different sensing device form factors
including an integrated handheld
sensing device as shown in FIG. 3B. The contextual sensor module 330 may be in
communication with one or
more processors (e.g., in the electronics system 340) such that sensor data
from the contextual sensor module
330 may be taken into account when analyzing vibroacoustic data and/or other
suitable data.
[261] The contextual sensor module 330 may include one or more suitable
sensors such as environmental
sensors to measure one or more ambient characteristics and/or one or more
characteristics of the sensing device
relative to the environment. For example, the contextual sensor module 330 may
include an ambient light sensor,
an ambient humidity sensor, an ambient pressure sensor, an ambient temperature
sensor, an air quality sensor
(e.g., detection of volatile organic compounds (VOCs)), altitude sensor (e.g.,
relative pressure sensor), GPS,
and/or other suitable sensor(s) to characterize the environment in which the
sensing device is operating.
Additionally, or alternatively, the contextual sensor module 330 may include
an inertial measurement unit
(IMU), individual gyroscope and/or accelerometer, and/or other suitable
sensor(s) to characterize the sensing
device relative to the environment.
Acoustocardiography (ACG) sensor module
[262] in some variations, the system 100 may further include one or more
sensor modules for detecting
vibrations of the heart as the blood moves through the various chambers,
valves, and large vessels, using an
acoustic cardiography sensor module. The ACG sensor module can record these
vibrations at four locations of
the heart and provides a "graph signature." While the opening and closing of
the heart valves contributes to the
graph, so does the contraction and strength of the heart muscle. As a result,
a dynamic picture is presented of
the heart in motion. If the heart is efficient and without stress, the graph
is smooth and clear. If the heart is
inefficient, there are definite patterns associated each type of contributing
dysfunction. The ACG is not the same
as an ECG, which is a common diagnostic test. The electrocardiograph (ECG)
records the electrical impulses
as it moves through the nerves of the heart tissue as they appear on the skin.
The ECG primarily indicates if the
nervous tissue network of the heart is affected by any trauma, damage (for
example from a prior heart attack or
infection), severe nutritional imbalances, stress from excessive pressure.
Only the effect on the nervous system
is detected. It will not tell how well the muscle or valves are functioning,
etc. In addition, the ECG is primarily
used to diagnose a disease. The ACG not only looks at electrical function but
also looks at heart muscle function,
which serves as a window of the metabolism of the entire nervous system and
the muscles. Using the heart
allows a "real-time" look at the nerves and muscles working together. As a
result of this interface, unique and
objective insights into health of the heart and the entire person can better
be seen.
Passive Acoustocerebrography (ACG) sensor module
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[263] In some variations, the system 100 may further include one or more
passive acoustocerebrography
sensor modules for detecting blood circulation in brain tissue. This blood
circulation is influenced by blood
circulating in the brain's vascular system. With each heartbeat, blood
circulates in the skull, following a
recurring pattern according to the oscillation produced. This oscillation's
effect, in turn, depends on the brain's
size, form, structure and its vascular system. Thus, every heartbeat
stimulates minuscule motion in the brain
tissue as well as cerebrospinal fluid and therefore produces small changes in
intracranial pressure. These
changes can be monitored and measured in the skull. The one or more passive
acoustocerebrography sensor
modules may include passive sensors like accelerometers to identify these
signals correctly. Sometimes highly
sensitive microphones can be used.
Active acoustocerebrography (ACG) sensor module
[264] In some variations, the system 100 may further include one or more
active acoustocerebrography sensor
modules. Active ACG sensor modules can be used to detect a multi-frequency
ultrasonic signal for classifying
adverse changes at the cellular or molecular level. In addition to all of the
advantages that passive ACG sensor
modules provide, the active ACG sensor module can also conduct a spectral
analysis of the acoustic signals
received. These spectrum analyses not only display changes in the brain's
vascular system, but also those in its
cellular and molecular structures. The active ACG sensor module can also be
used to perform a Transcranial
Doppler test, and optionally in color. These ultrasonic procedures can measure
blood flow velocity within the
brain's blood vessels. They can diagnose embolisms, stenoses and vascular
constrictions, for example, in the
aftermath of a subarachnoid hemorrhage.
Ballistocardiography (BCG) sensor module
[265] In some variations, the system 100 may further include one or more
ballistocardiograph sensor modules
(BCG) for detecting ballistic forces generated by the heart. The downward
movement of blood through the
descending aorta produces an upward recoil, moving the body upward with each
heartbeat. As different parts
of the aorta expand and contract, the body continues to move downward and
upward in a repeating pattern.
Ballistocardiography is a technique for producing a graphical representation
of repetitive motions of the human
body arising from the sudden ejection of blood into the great vessels with
each heart beat. It is a vital sign in the
1-20 Hz frequency range which is caused by the mechanical movement of the
heart and can be recorded by
noninvasive methods from the surface of the body. Main heart malfunctions can
be identified by observing and
analyzing the BCG signal. BCG can also be monitored using a camera-based
system in a non-contact manner.
One example of the use of a BCG is a ballistocardiographic scale, which
measures the recoil of the person's
body who is on the scale. A BCG scale is able to show a person's heart rate as
well as their weight.
Electromyography (EMG) sensor module
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[266] In some variations, the system 100 may further include one or more
Electromyography (EMG) sensor
modules for detecting electrical activity produced by skeletal muscles. The
EMG sensor module may include
an electromyograph to produce a record called an electromyogram. An electromy-
ograph detects the electric
potential generated by muscle cells when these cells are electrically or
neurologically activated. The signals can
be analyzed to detect medical abnommlities, activation level, or recruitment
order, or to analyze the
biomechanics of human or animal movement. EMG can also be used in gesture
recognition.
Electrooculography (EOG) sensor module
[267] In some variations, the system 100 may further include one or more
electrooculography (EOG) sensor
modules for measuring the comeo-retinal standing potential that exists between
the front and the back of the
human eye. The resulting signal is called the electrooculogram. Primary
applications are in ophthalmological
diagnosis and in recording eye movements. Unlike the electroretinogram, the
EOG does not measure response
to individual visual stimuli. To measure eye movement, pairs of electrodes are
typically placed either above and
below the eye or to the left and right of the eye. If the eye moves from
center position toward one of the two
electrodes, this electrode "sees" the positive side of the retina and the
opposite electrode "sees" the negative side
of the retina. Consequently, a potential difference occurs between the
electrodes. Assuming that the resting
potential is constant, the recorded potential is a measure of the eye's
position.
Electroolfactography (EOG) sensor module
[268] In some variations, the system 100 may further include one or more
Electro-olfactography or
electroolfactography (EGG) sensor modules for detecting a sense of smell of
the subject. The EOG sensor
module can detect changing electrical potentials of the olfactory epithelium,
in a way similar to how other forms
of electrography (such as ECG, EEG, and EMG) measure and record other
bioelectric activity. Electro-
olfactography is closely related to electroantennography, the electrography of
insect antennae olfaction.
Electroencephalographv (EEG) sensor module
[269] In some variations, the system 100 may further include one or more
electroencephalography (EEG)
sensor modules for electrophysiological detection of electrical activity of
the brain, or vibroacoustic sensor
modules placed onto the skull anechoic chamber to "listen" to the brain and
capture subtle pressure and pressure
gradient changes related to the speech processing circuitry. EEG is typically
noninvasive, with the electrodes
placed along the scalp, although invasive electrodes are sometimes used, as in
electrocorticography. . EEG
measures voltage fluctuations resulting from ionic current within the neurons
of the brain. Clinically, EEG refers
to the recording of the brain's spontaneous electrical activity over a period
of time, as recorded from multiple
electrodes placed on the scalp. Diagnostic applications generally focus either
on event-related potentials or on
the spectral content of EEG. The former investigates potential fluctuations
time locked to an event, such as
'stimulus onset' or 'button press'. The latter analyses the type of neural
oscillations (popularly called "brain
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waves") that can be observed in EEG signals in the frequency domain. EEG can
be used to diagnose epilepsy,
which causes abnormalities in EEG readings. It can also used to diagnose sleep
disorders, depth of anesthesia,
coma, encephalopathies, and brain death. EEG, as well as magnetic resonance
imaging (MRI) and computed
tomography (CT) can be used to diagnose tumors, stroke and other focal brain
disorders. Advantageously, EEG
is a mobile technique available and offers millisecond-range temporal
resolution which is not possible with CT,
PET or MRI. Derivatives of the EEG technique include evoked potentials (EP),
which involves averaging the
EEG activity time-locked to the presentation of a stimulus of some sort
(visual, somatosensory, or auditory).
Event-related potentials (ERPs) refer to averaged EEG responses that are time-
locked to more complex
processing of stimuli.
Ultra-wideband (UWB) sensor module
[270] In some variations, the system 100 may further include one or more ultra-
wideband sensor modules
(also known as UWB, ultra-wide band and ultraband). UWB is a radio technology
that can use a very low energy
level for short-range, high-bandwidth communications over a large portion of
the radio spectrum. UWB has
traditional applications in non-cooperative radar imaging. Most recent
applications target sensor data collection,
precision locating and tracking applications. A significant difference between
conventional radio transmissions
and UWB is that conventional systems transmit information by varying the power
level, frequency, and/or phase
of a sinusoidal wave. UWB transmissions transmit information by generating
radio energy at specific time
intervals and occupying a large bandwidth, thus enabling pulse-position or
time modulation. The information
can also be modulated on UWB signals (pulses) by encoding the polarity of the
pulse, its amplitude and/or by
using orthogonal pulses. UWB pulses can be sent sporadically at relatively low
pulse rates to support time or
position modulation, but can also be sent at rates up to the inverse of the
UWB pulse bandwidth. Pulse-UWB
systems have been demonstrated at channel pulse rates in excess of 1.3
gigapulses per second using a continuous
stream of UWB pulses (Continuous Pulse UWB or C-UWB), supporting forward error
correction encoded data
rates in excess of 675 Mbit/s.
[271] A valuable aspect of UWB technology is the ability for a UWB radio
system to determine the "time of
flight" of the transmission at various frequencies. This helps overcome
multipath propagation, as at least some
of the frequencies have a line-of-sight trajectory. With a cooperative
symmetric two-way metering technique,
distances can be measured to high resolution and accuracy by compensating for
local clock drift and stochastic
inaccuracy.
[272] Another feature of pulse-based UWB is that the pulses are very short
(less than 60 cm for a 500 MHz-
wide pulse, and less than 23 cm for a 1.3 GHz-bandwidth pulse) ¨ so most
signal reflections do not overlap the
original pulse, and there is no multipath fading of narrowband signals.
However, there is still multipath
propagation and inter-pulse interference to fast-pulse systems, which must be
mitigated by coding techniques.
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[273] Ultra-wideband is also used in "see-through-the-wall" precision radar-
imaging technology, precision
locating and tracking (using distance measurements between radios), and
precision time-of-arrival-based
localization approaches. It is efficient, with a spatial capacity of about
1013 bit/s/m2. UWB radar has been
proposed as the active sensor component in an Automatic Target Recognition
application, designed to detect
humans or objects that have fallen onto subway tracks.
[274] Ultra-wideband pulse Doppler radars can also be used to monitor vital
signs of the human body, such
as heart rate and respiration signals as well as human gait analysis and fall
detection. Advantageously, UWB
has less power consumption and a high-resolution range profile compared to
continuous-wave radar systems.
However, its low signal-to-noise ratio has made it vulnerable to errors.
[275] In the USA, ultra-wideband refers to radio technology with a bandwidth
exceeding the lesser of 500
MHz or 20% of the arithmetic center frequency, according to the U.S. Federal
Communications Commission
(FCC). A February 14, 2002 FCC Report and Order authorized the unlicensed use
of UWB in the frequency
range from 3.1 to 10.6 GHz. The FCC power spectral density emission limit for
UWB transmitters is ¨41.3
dBm/MHz. This limit also applies to unintentional emitters in the UWB band
(the "Part 15" limit). However,
the emission limit for UWB emitters may be significantly lower (as low as ¨75
dBm/MHz) in other segments
of the spectrum. Deliberations in the International Telecommunication Union
Radiocommunication Sector
(ITU-R) resulted in a Report and Recommendation on UWB in November 2005. UK
regulator Ofcom
announced a similar decision on 9 August 2007. More than four dozen devices
have been certified under the
FCC LTWB rules, the vast majority of which are radar, imaging or locating
systems.
[276] There has been concern over interference between narrowband and UWB
signals that share the same
spectrum. Earlier, the only radio technology that used pulses were spark-gap
transmitters, which international
treaties banned because they interfere with medium-wave receivers. UWB,
however, uses lower power. The
subject was extensively covered in the proceedings that led to the adoption of
the FCC rules in the US. and in
the meetings relating to UWB of the ITU-R leading to its Report and
Recommendations on UWB technology.
Commonly used electrical appliances emit impulsive noise (for example, hair
drycrs) and proponents
successfully argued that the noise floor would not be raised excessively by
wider deployment of low power
wideband transmitters.
Seismocardiography (SCG) sensor module
[277] In some variations, the system 100 may further include one or more
seismocardiography (SCG) sensor
modules for non-invasive measurement of cardiac vibrations transmitted to the
chest wall by the heart during
its movement. SCG was first introduced around the mid 20th century. Some
promising clinical applications
were suggested. These include the observation of changes in the SCG signal due
to ischemia and the use of SCG
in cardiac stress monitoring. The origin of SCG can be traced back to the 19th
century when scientists reported
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observing a heartbeat while standing on a scale. Although SCG in general has
not been deployed in the clinical
enviromnent, some promising applications have been suggested. For instance,
SCG has been proposed to be of
value in assessing the timing of different events in the cardiac cycle. Using
these events, assessing, for example,
myocardial contractility might be possible. SCG has also been proposed to be
capable of providing enough
information to compute heart rate variability estimates. A more complex
application of cardiac cycle timings
and SCG waveform amplitudes is the computing of respiratory information from
the SCG.
Intracardiac electrogram (EGM) sensor module
[278[ In some variations, the system 100 may further include one or more
intracardiac electrogram (EGM)
sensor modules for non-invasive measurement of cardiac electrical activity
generated by the heart during its
movement. It provides a record of changes in the electric potentials of
specific cardiac loci as measured by
electrodes placed within the heart via cardiac catheters; it is used for loci
that cannot be assessed by body surface
electrodes, such as the bundle of His or other regions within the cardiac
conducting system.
Pulse Plethysmograph (PPG) sensor module
[279] In some variations, the system 100 may further include one or more pulse
plethysmograph (PPG) sensor
modules for non-invasive measurement of the dynamics of blood vessel
engorgement. The module may use a
single wavelength of light, or multiple wavelengths of light, including far
infrared, near infrared, visible or UV.
For UV light, the wavelengths used are between about 315 mu and 400 tun and
the module is intended to deliver
less than 8 milliwatt-hours per square centimeter per day to the subject
during its operation.
Galvanic Skin Response (GSR) sensor module
[280] In some variations, the system 100 may further include one or galvanic
skin response (GSR) sensor
modules. These modules may utilize either wet (gel), dry, or non-contact
electrodes as described herein.
Volatile Organic Compounds (VOC) sensor module
[281] In some variations, the system 100 may further include one or more
volatile organic compounds (VOC)
sensor modules for detecting VOC or semi-VOCs in exhaled breath of the
subject. The potential of exhaled
breath analysis is huge, with applications in many fields including, but not
limited to, the diagnosis and
monitoring of disease. Certain VOCs are linked to biological processes in the
human body. For instance,
dimethylsulfide is exhaled as a result of fetor hepaticus and acetone is
excreted via the lungs during ketoacidosis
in diabetes. Typically, VOC Excretion or Semi-VOC excretion can be measured
using plasmon surface
resonance, mass spectroscopy, enzymatic based, semiconductor based or
imprinted polymer-based detectors.
Vocal Tone Inflection (VTI) sensor module
[282] In some variations, the system 100 may further include one or more vocal
tone inflection (VTI) sensor
modules. VTI analysis can be indicative of an array of mental and physical
conditions that make the subject slur
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words, elongate sounds, or speak in a more nasal tone. They may even make the
subject's voice creak or jitter
so briefly that it's not detectable to the human ear. Furthermore, vocal tone
changes can also be indicative of
upper or lower respiratoly conditions, as well as cardiovascular conditions.
Developers have found that VTI
analysis can be used for early diagnosis of certain respiratory conditions
from a Covid-19 infection (see
Examples 7 and 8).
Capacitive sensor module
[283] In some variations, the system 100 may further include one or more
capacitive/Non-contact sensor
modules. Such sensor modules may include non-contact electrodes. These
electrodes were developed since the
absence of impedance adaptation substances could make the skin-electrode
contact instable over time. This
difficulty was addressed by avoiding physical contact with the scalp through
non-conductive materials (i.e., a
small dielectric between the skin and the electrode itself): despite the
extraordinary increase of electrode
impedance (>200 MOhm), in this way it will be quantifiable and stable over
time.
[284] A particular type of dry electrode, is known as a capacitive or
insulated electrode. These electrodes
require no ohmic contact with the body since it acts as a simple capacitor
placed in series with the skin, so that
the signal is capacitively coupled. The received signal can be connected to an
operational amplifier and then to
standard instrumentation.
[285] The use of a dielectric material in good contact to the skin results in
a fairly large coupling capacitance,
ranging from 300 pF to several nano-farads. As a result, a system with reduced
noise and appropriate frequency
response is readily achievable using standard high-impedance FET (field-effect
transistor) amplifiers.
[286] While wet and dry electrodes require physical contact with the skin to
function, capacitive electrodes
can be used without contact, through an insulating layer such as hair,
clothing or air. These contaetless electrodes
have been described generally as simple capacitive electrodes, but in reality
there is also a small resistive
element, since the insulation also has a non-negligible resistance.
[287] The capacitive sensor modules can be used to measure heart signals, such
as heart rate, in subjects via
either direct skin contact or through one and two layers of clothing with no
dielectric gel and no grounding
electrode, and to monitor respiratory rate. High impedance electric potential
sensors can also be used to measure
breathing and heart signals.
Capacitive plates sensor module
[288] In some variations, the system 100 may further include one or more
capacitive plate sensor modules.
Surprisingly, Developers discovered that the resistive properties of the human
body may also be interrogated
using the changes in dielectric properties of the human body that come with
difference in hydration, electrolyte,
and perspiration levels. In this variation, the sensing device may comprise
two parallel capacitive plates which
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are positionable on either side of the body or body part to be interrogated. A
specific time varying potential is
applied to the plates, and the instantaneous current required to maintain the
specific potential is measured and
used as input into the machine learning system to correlate the physiological
states to the data. As the dielectric
properties of the body or body part changes with resistance, the changes are
reflected in the current required to
maintain the potential profile. In certain variations, a target bodily
condition can be screened using such a
capacitive plate and permitting interrogation of the subject standing on the
capacitive plate.
[289] From certain aspects, there may be thus be provided a system for
screening for a target condition in a
subject. the system comprising: a device comprising: a first portion having a
first sensor incorporated therein,
the first sensor arranged to capture physiological data from the subject,
wherein the first sensor comprises
comprises two capacitive plates positionable on either side of a body of the
subject or a body part of the subject.
In certain embodiments, the first portion is arranged to be supported by a
support surface such as a wall, a floor
or a ceiling in use. In certain embodiments, the device further comprises a
second portion which is a top unit
extending orthogonally to the two capacitive plates. In certain embodiments,
the top unit is arranged to face a
head of the subject in use. In certain embodiments, a surface of at least one
of the capacitive plates is mirrored.
In certain embodiments, there is further provided a computing system,
communicatively coupled to the first
sensor and the second sensor and arranged to execute a method, the method
comprising, obtaining the captured
physiological data from one or both of the first sensor and the second sensor,
and feeding the obtained
physiological data to an MLA, the MLA being arranged to determine a likelihood
of the subject having the
target condition based on the obtained physiological data.
Machine vision sensor module
[290] In some variations, the system 100 may further include one or more
machine vision sensor modules
comprising one or more optical sensors such as cameras for capturing the
motion of the subject, or parts of the
subject, as they stand or move (e.g. walking, running, playing a sport,
balancing etc.). In this manner,
physiological states that affect kinesthetic movements such as balance and
gait patterns, tremors, swaying or
favoring a body part can be detected and correlated with the other data
obtained from the other sensors in the
apparatus such as center of mass positioning. Machine vision allows skin
motion amplification to accurately
measure physiological parameters such as blood pressure, heart rate, and
respiratory rate. For example,
heart/breath rate, heart/breath rate variability, and lengths of heart/breath
beats can be estimated from
measurements of subtle head motions caused in reaction to blood being pumped
into the head, from hemoglobin
information via observed skin color, and from periodicities observed in the
light reflected from skin close to the
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arteries or facial regions. Aspects of pulmonary health can be assessed from
movement patterns of chest, nostrils
and ribs.
[291] A wide range of motion analysis systems allow movement to be captured in
a variety of settings, which
can broadly be categorized into direct (devices affixed to the body, e.g.
accelerometry) and indirect (vision-
based, e.g. video or optoelectronic) techniques. Direct methods allow
kinematic information to be captured in
diverse environments. For example, inertial sensors have been used as tools to
provide insight into the execution
of various movements (walking gait, discus, dressage and swimming). Sensor
drift, which influences the
accuracy of inertial sensor data, can be reduced during processing; however,
this is yet to be fully resolved and
capture periods remain limited. Additionally, it has been recognized that
motion analysis systems for
biomechanical applications should fulfil the following criteria: they should
be capable of collecting accurate
kinematic information, ideally in a timely manner, without encumbering the
performer or influencing their
natural movement. As such, indirect techniques can be distinguished as more
appropriate in many settings
compared with direct methods, as data are captured remotely from the
participant imparting minimal
interference to their movement. Indirect methods were also the only possible
approach for biomechanical
analyses previously conducted during sports competition. Over the past few
decades, the indirect, vision-based
methods available to biomechanists have dramatically progressed towards more
accurate, automated systems.
However, there is yet to be a tool developed which entirely satisfies the
aforementioned important attributes of
motion analysis systems. Thus, these analyses may be used in coaching and
physical therapy in dancing,
running, tennis, golf, archery, shooting biomechanics and other sporting and
physical activities. Other uses
include ergonomic training for occupations that subject persons to the dangers
of repetitive stress disorders and
other physical stressors related to motion and posture. The data can also be
used in the design of furniture, self-
training, tools, and equipment design.
12921 The machine vision module may include one or more digital camera sensors
for imaging one or more
of pupil dilation, scleral erythrema, changes in skin color, flushing, and/or
erratic movements of a subject, for
example. Other optical sensors may be used that operate with coherent light,
or use a time of flight operation.
In certain variants, the machine vision module comprises a 3D camera such
Astra Embedded S by Orrbec.
Thermal sensor module
[293] In some variations, the system 100 may further include one or more
thermal sensor modules including
an infrared sensor, a thermometer, or the like. The thermal sensor module may
be incorporated with the sensing
device or be separate thereto. The thermal sensor may be used to perform
temperature measurements of one or
more of a lacrimal lake and/or an exterior of tear ducts of the subject. In
some variations, the thermal sensor
module may comprise a thermopile on a gimbal, such as but not limited to a
thermopile comprising an integrated
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infrared thermometer, 3V, single sensor (not array), gradient compensated,
medical +-0.2 to +-0.3 degree
kelvin/Centigrade, 5 degree viewing angle (Field of view - FOV)
Strain gage sensor module
[294] In some variations, the system may comprise strain gauge sensors that
may be used to measure the
subject's weight. In other variations these sensors may be used to acquire
seismocardiograms or
ballistocardiograms. These sensors, without limitations, may be resistive or
piezo-electric strain gauges.
Sensor module combinations
[295] Any combination of the abovementioned sensor modules can be used in
variants of the present system
100. The sensor module combinations may be housed within a single device or
multiple devices. A relative
positioning of the sensor module combinations is selected to ensure that data
is captured from the subject along
the most appropriate plane. In certain variants, two sensor modules are
positioned orthogonally to one another
to capture data from the subject along different planes. For example, the
sensor module combination may
include: the capacitive plate sensor module positioned substantially
horizontally and configured for the subject
to stand on, and a vibroacoustic sensor module positioned substantially and
configured to capture vibroacoustic
signals from the subject.
Sensor Data
[296_1 In typical applications, each modular system described above
implemented individually would require
the attachment of "markers" or "beacons" to the subject to allow for accurate
signal chain tracking and surface
motion amplification. By using sensor fusion, the current technology provides
for methods to track limb and
body motion without the need to attach a separate displacement sensor or
beacon to the subject.
[297] In certain variations, the sensor modules used with the system 100 may
each capture data as catenated
raw amplitude sequences or as combined short-time Fourier transform spectra.
In certain variations, the data
from the sensor modules is captured from the subject in less than 15 seconds
per subject, and preferably in less
than 10 seconds per subject.
[298] In certain embodiments, the collected or monitored data may comprise one
or more of optical;
electromagnetic and vibroacoustic monitored parameters. This may be referred
to as biometric or biofield data.
12991 The biometric data may be collected by any suitable device or system
such as one or more of the sensors
described herein.
[300] in certain embodiments, biometric data is collected or monitored by one
or more sensors, such as but
not limited to: vibroacoustic sensor, electric potential sensor, volatile
organic compound sensor and wide
frequency bandwidth terahertz sensor (used to generate and detect
electromagnetic waves at the terahertz
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frequencies), microphone, volatile organic compound sensor, altitude sensor,
ambient temp sensor, barometric
pressure sensor, and air quality sensor.
[301_1 In certain embodiments, the biometric data may comprise a single data
parameter which is collected
and/or monitored. In certain other embodiments, the biometric data comprises
two or more data parameters
which are collected and/or monitored.
[302] In certain embodiments, biometric data is collected and/or monitored in
one or both of a baseline phase
and a base-line update phase. This may correct for physiological drift.
[303] In the baseline phase, biometric data may be collected and/or monitored
over 1 to 5 days, 1 to 4 days,
Ito 3 days, Ito 2 days, 2 to 5 days, 3 to 5 days, 4 to 5 days, 1 to 3 days, 2
to 3 days. Data collection may be
continuous or in data segments.
[304] In the update phase, biometric data may be collected and/or monitored
for 1 to 25 seconds, 5 to 25
seconds, 10 to 25 seconds, 15 to 25 seconds, 20 to 25 seconds, 1 to 20
seconds, 1 to 15 seconds, 1 to 10 seconds,
to 10 seconds, 5 to 15 seconds.
[305] In certain embodiments, the biometric data is acquired in data segments
of about 15 s to about 20 s in
length, or about 10 to about 25 s, or any other data segment length which
satisfies data quality and data quantity
requirements.
[306] in certain embodiments, data is collected about 2 days to about 4 days
for continuous health
characterization and baselining.
[307] In certain embodiments, updates using baselined data requires a shorter
confirmatory data read or top-
up from about 5 seconds to about 10 seconds.
[308] In certain embodiments, the method comprises acquiring biometric data of
a subject at a first point in
time, and storing in a database ("pre-screening step). The method further
comprises, at the second point in time,
acquiring additional biometric data and using the stored data for monitoring
or diagnosis.
[309] The pre-screening process may be carried out over a period of about 1 to
5 days.
[310] In certain embodiments, the baseline data is ephemeral (can be deleted,
over written, or loses validity).
[311] In certain embodiments, the method may comprise collecting and/or
monitoring the data with sampling
rates from about 0.01Hz to about 20THz, more than about 10 THz, about 10 THz
to about 100 THz; about
0 01Hz to about 100THz. In certain embodiments, this can result in improved
data quality and quality meaning.
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These sampling rates may be considered as "high resolution" compared to
conventional data sampling. In the
Terahertz range, the date may be passively or actively captured.
[312] In certain embodiments, the data from the sensors is captured from the
subject in less than 15 seconds
per subject, and preferably in less than 10 seconds per subject.
[313] In certain embodiments, high resolution biometric/biofield/biosignature
data is processed using cross-
frequency coupling and cross-phase signal coupling methods to abstract
biosignature data
[314] In relation to the current technology, cross-frequency coupling (CFC)
methods comprise mean vector
length or modulation index, phase-locking value, envelope-to-signal
correlation, analysis of amplitude spectra,
analysis of coherence between amplitude and signal, analysis of coherence
between the time course of power
and signal, and eigen decomposition of multichannel covariance matrices. These
methods analyze how the
frequency changes of a first signal influence the frequency of a second
signal.
[315] Cross-frequency coupling (CFC) also include analysis of phase-amplitude
coupling (PAC), a form of
cross-frequency coupling where the amplitude of a first frequency signal is
modulated by the phase of a second
frequency signal. They also include the analysis of phase-phase coupling
(PPC), where the phase of one
frequency signal influences the phase of a second frequency signal and
amplitude-amplitude coupling (AAC),
where the amplitude of a first signal influences the amplitude of a second
frequency signal.
p16] In still another embodiment, the processing comprises the performance of
the following steps: Sampling
the data streams from the sensor or sensors; Sample signal
acceptance/rejection; Sample signal enhancement;
Sample signal normalization; Feature extraction; Cross frequency coupling and
signal aggregation and
abstraction; and Comparison of the biometric sample with all stored samples in
database.
1.d. Electronics system
[317] In some variations, the sensing device may further include an
electronics system. In the variation
illustrated in FIG. 3B, the sensing device 300 includes the electronics system
340 including various electronics
components for supporting operation of the sensing device 300. In the
variation illustrated in FIG. 4B, the
sensing device 400 includes the electronics system 440 including various
electronics components for supporting
operation of the sensing device 400. For example, at least a portion of the
electronics system 340, 440 may
include a circuit board arranged in the housing 310, 410 of the vibroacoustic
sensing device 300, 400 in a
modular fashion. The electronics system 340, 440 may be configured to perform
signal conditioning, data
analysis, power management, communication, and/or other suitable
functionalities of the device. The electronics
system 340, 440 may be in communication with other components of the sensing
device such as the
vibroacoustic sensor module 320, 420 contextual sensor module 330, 430, power
source 342, 442 (e.g., battery),
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and/or display 330. Accordingly, the electronics system 340, 440 may, in some
variations, function as a
microcontroller unit module for the sensing device 300, 400.
[318] In some variations as shown in FIG. 23, an electronics system 2300 of a
sensing device may include at
least one processor 2310, at least one memory device 2320, suitable signal
processing circuity 2330, at least one
communication module 2340, and/or at least one power management module 2360.
One or more of these
components or modules may be arranged one or more electronic circuit boards
(e.g., PCB) which in turn may
be mounted within a housing of the sensing device. In some variations, the
electronics system may also include
a microphone and/or speaker for enabling further functionality such as voice
or data recording (e.g., permitting
recitation of medical notes for an electronic health record, etc.).
[319] The processor 2310 (e.g., CPU) and/or memory device 2320 (which can
include one or more computer-
readable storage mediums) may cooperate to provide a controller for operating
the system. For example, the
processor 2310 may be configured to set and/or adjust sampling frequency for
any of the various sensors in the
vibroacoustic sensor module 320, 420 and/or the contextual sensor module 330,
430. As another example, the
processor 2310 may receive sensor data (e.g., before and/or or after sensor
signal conditions) and the sensor
data may be stored in one or more memory devices 2320. In some variations,
some or all of the data stored on
the memory device 2320 may be encrypted using a suitable encryption protocol
(e.g., for HIPAA-compliant
security). In some variations, the processor 2310 and memory device 2320 may
be implemented on a single
chip, while in other variations they may be implemented on separate chips.
[320] The communication module 2340 may be configured to communicate sensor
data, analysis data, and/or
other information to an external computing device. Additionally, or
alternatively, the communication module
2340 may communicate with external sources for microcontroller programming and
software updates. The
external computing device may be, for example, a mobile computing device
(e.g., mobile telephone, tablet,
smart watch), laptop, desktop, medical equipment, or other suitable computing
device. The external computing
device may be executing an application for presenting sensor data (and/or the
results of analysis thereof) through
a user interface to a user.
[321] Additionally, or alternatively, the communication module 2340 may be
configured to communicate data
to one or more networked devices, such as a hub paired with the system 100, a
server, a cloud network, etc. In
some variations, the communication module 2340 may be configured to
communicate information in an
encrypted manner. While in some variations the communication module 2340 may
be separate from the
processor(s) as a separate device, in variations at least a portion of the
communication module may be integrated
with the processor 2340 (e.g., the processor may include encryption hardware,
such as advanced encryption
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standard (AES) hardware accelerator (e.g., 128/256-bit key) or HASH (e.g., SHA-
256)). Additional aspects of
the communication scheme are described in further detail below with respect to
the signal processing system.
[322] The communication module 2340 may communicate via a wired connection
(e.g., including a physical
connection such as a cable with a suitable connection interface such as USB,
mini-USB, etc.) and/or a wireless
network (e.g., through NFC, Bluetooth, WiFi, RFID, or any type of digital
network that is not connected by
cables). For example, devices may directly communicate with each other in
pairwise connection (1:1
relationship), or in a hub-spoke or broadcasting connection ("one to many- or
1:m relationship). As another
example, the devices may communicate with each other through mesh networking
connections (e.g., "many to
many", or tn:m relationships), such as through Bluetooth mesh networking.
Wireless communication may use
any of a plurality of communication standards, protocols, and technologies,
including but not limited to, Global
System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE),
high-speed downlink
packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution,
Data- Only (EV-D0), HSPA,
HSPA+, Dual-Cell HSPA (DC-HSPDA), long term evolution (LTE), near field
communication (NFC),
wideband code division multiple access (W-CDMA), code division multiple access
(CDMA), time division
multiple access (TDMA), Bluetooth, Wireless Fidelity (WiFi) (e.g., IEEE
802.11a, IEEE 802.11b, IEEE
802.11g, IEEE 802.11n, and the like), or any other suitable communication
protocol. Some wireless network
deployments may combine networks from multiple cellular networks (e.g., 3G,
4G, 5G) and/or use a mix of
cellular, WiFi, and satellite communication.
[323] In some variations, the communication module 2340 (e.g., used as input
and function manipulation,
and/or tactile feedback) may include multiple data communication streams or
channels to help ensure broad
spectrum data transfer (e.g., Opus 20 kHz with minimal delay codec). Such
multiple data communication
streams are an improvement over typical wireless data transmission codecs. For
example, most wireless data
transmission codecs (e.g., G.711) use a bandpass filter to only encode the
optimal range of human speech, 300
Hz to 3,400 Hz (this is commonly referred to as a narrowband codec). As
another example, some wireless data
transmission codecs (e.g., G.722) encodes the range from 300 Hz to 7,000 Hz
(this is commonly referred to as
a wideband codec). However, most of the energy is concentrated below 1,000 Hz
and there is virtually no
audible sound above 5,000 Hz, while there is a measurable amount of energy
above the 3,400 Hz cutoff of most
codecs. The data throughput requirements for both G.711 and G.722 are the same
because the modulation used
in G.722 is a modified version of the PCM called Adaptive Differential Pulse
Code Modulation (ADPCM).
When this kind of complexity is added to a codec and process power remains
constant, this will add latency. As
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such, G.711 will introduce latency well below just one millisecond but G.722
could introduce tens of
milliseconds of delay- which is an unacceptably long delay in vibroacoustics.
[324] The power management module 2360 may be configured to manage power from
one or more power
sources and distribute power to the processor, communication module, sensors,
and/or any other electrical
components as appropriate. For example, the power source may include one or
more batteries (e.g., lithium ion
battery) arranged in the housing of the sensing device as described above. In
some variations, the power source
may be rechargeable such as through wireless charging methods (e.g., inductive
charging, RF coupling, etc.) or
by harnessing kinetic and/or thermal energy such as that generated through
motion (e.g., when the user walks
while wearing the garment, including harvesting thermal energy from the body
or by using energy gathering,
amplifying, and storing cells that collect light and convert it to electrical
signals, and/or cells that convert
temperature or temperature gradients directly to electricity). In some
variations, the power management module
2360 may be connected to the power source through a suitable charge
controller.
[325] In some variations, the power management module 2300 may include
electronic components to convert
the power to predetermined voltage outputs suitable for the other components
(e.g., processor and/or memory
devices, signal processing system, etc.) in the sensing device. For example.
the power management module
2300 may include buck-boost converters to output 3.3 V and 5 V, and an on-
board universal serial bus (e.g.,
USB-C) that can be used to charge the module and/or power source with an
external charger (e.g., mobile
charger, power outlet, etc.).
1.e. Signal processing system
[326] Various analog and digital processes may condition sensor data for
extracting useful signal from noise
and communicate suitable data to one or more external host devices (e.g.,
computing device such as mobile
device, one or more storage devices, medical equipment, etc.). At least a
portion of the signal processing chain
may occur on-board a circuit board in one or more sensor modules (e.g.,
flexible or rigid circuit board in the
vibroacoustic sensor module, the contextual sensor module, and/or any other
sensor module). Additionally or
alternatively, at least a portion of the signal processing system may occur
outside of the sensor modules (e.g.,
electronics system 340, 440 or microcontroller unit module).
[327] In some variations, a signal processing chain for handling data, such as
the vibroacoustic sensor data,
ECG data, the contextual data, thermal data, optical data, etc. may be
configured to provide an output signal
with low noise (high signal-to-noise ratio (SNR), provide sufficient
amplification to allow proper digitization
of the analog signal, and function in a manner that keeps the overall signal
fidelity sufficiently high. The signal
processing chain may also be configured to (i) overcome signal attenuation and
loss of strength of a signal as it
propagates over a medium or a plurality of media, and/or (ii) to move
digitized data sufficiently quickly through
the various components of the sensing device to as to avoid significant signal
and/or data loss. In some
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variations, the signal processing chain may include a programmable gain stage
to adjust gain in real- time during
operation of the sensing device in order to optimize signal range for analog-
to-digital converters. The frequency
and bandwidth requirements of the signal processing chain may vary depending
specific applications, but in
some variations the signal processing chain may have a sufficient bandwidth to
sample frequencies up to about
160 kHz or up to about 320 kHz, and have a low frequency response of about 0.1
Hz or lower.
[328] High-precision signal control may be important in biofield and other
vibroacoustic active and passive
sensing to minimize signal and/or data loss. However, the difficulty to obtain
model parameters is one of the
main obstacles to obtain high-precision tracking control of biofield signals
using a model-dependent method.
The vibroacoustic system with uncertain parameters can defend against signal
and/or data loss by having high
precision of the system output information. In some variations, an adaptive
output feedback control scheme may
be implemented with an inline servo system with uncertain parameters and
unmeasurable states instantiated
with controller and parameter adaptation algorithms to guarantee that the
biofield signal tracking error is
uniformly bounded. This method may be combined with a traditional
proportional¨integral¨derivative (PID)
control method with optimal parameters (e.g., obtained using a genetic
algorithm), a sliding mode control based
on exponential reaching law, and/or adaptive control methods and adaptive
backstepping sliding mode control,
to achieve higher tracking accuracy. The vibroacoustic system also may have
better anti-interference ability
with respect to signal load change.
[329] Vibroacoustic signal control, which may be termed active vibro-acoustic
control, can be achieved in
some variations with multiple servo motors, actuators and sensors and fully-
coupled feeclforward or feedback
controllers. For example, in some variations, feedback may be achieved using
multiple miniature cross-axis
inertial sensors (e.g., accelerometers) together with either collocated force
actuators or piezoceramic actuators
placed under each sensor. Collocated actuator/sensor pairs and decentralized
(local) feedback may be optimized
over the bandwidth of interest to ensure stability of multiple local feedback
loops. For example, the control
system may include an array of actuator/sensor pairs (e.g., n x n array of
such actuator/sensor pairs, such as 4 x
4 or greater), which may be connected together with n2 local feedback control
loops. Using force actuators,
significant frequency-averaged reductions up to lkHz in both the kinetic
energy (e.g., 20- 100dB) and
transmitted sound power (e.g., 10-60dB) can be obtained with an appropriate
feedback gain in each loop.
[330] FIG. 24 depicts an exemplary signal processing chain for manipulating
vibroacoustic sensor data from
one or more sensors 2402 in the vibroacoustic sensor module. As shown in FIG.
24, a first set 2410 of analog
signal processing steps may be performed by analog circuitry on one or more
printed circuit boards (PCB), a
second set 2420 of analog signal processing steps may be performed by analog
circuitry within a m icrocontroller
unit module, and a third set 2430 of digital signal processing steps may be
performed by digital circuitry within
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the microcontroller unit module. However, it should be understood that these
steps may be performed by analog
and/or digital components located in any suitable location on or in the
sensing device (e.g., electronics system).
[331_1 The analog portion of the signal chain 2410, 2420 may be optimized for
low noise and high SNR signal
acquisition of vibroacoustic sensor signals. In addition to low noise
components, the PCB itself may be designed
and optimized for low noise operation. For example, the PCB may include
multiple layers (e.g., 4 layers),
including an entire layer dedicated as a ground plane, preventing ground
loops, offering low resistance ground
and acting as a shield between signal lines on the remaining layers. In some
variations, as further described
below, the signal chain may include low pass filtering of at least second to
fourth order to help prevent aliasing.
[332] The raw signals from the sensor 2402 may, in some variations, typically
range from 100 V to 1 mV,
but can be up to 10 mV for high SNR sensors in the sensing device. A first
stage amplifier 2412 is of particular
low noise input optimization and may have a gain of between about 50 and about
200, depending on the specific
sensor. The first stage 2412 may also include a first order low pass filter
with cutoff frequency at about 15 kHz-
20 kHz. The signal may then be fed to an active filter stage 2413 of first
order or second order with cutoff
frequency at about 15 kHz-20 kHz. In some variations, this active filter stage
may be a second order filter
realized with a Sallen- Key Topology. The signal from the first stage may be
fed to a second stage amplifier
2414, which may, in some variations, have a gain of between about 1 and about
10-100 with another low pass
filter with cutoff at about 0.01 Hz to about 120 kHz (e.g., from about 0.01 Hz
to at least about 50 kHz, from
about 0.01 Hz to at least about 60 kHz, from about 0.01 Hz to at least about
70 kHz, from about 0.01 Hz to at
least about 80 kHz, from about 0.01 Hz to at least about 90 kHz, from about
0.01 Hz to at least about 100 kHz,
from about 0.01 Hz to at least about 110 kHz, from about 0.01 Hz to at least
about 120 kHz, from about 0.01
Hz to at least about 130 kHz, from about 0.01 Hz to at least about 140 kHz,
from about 0.01 Hz to at least about
150 kHz, from about 0.01 Hz to at least about 160 kHz, from about 0.01 Hz to
more than about 160 kHz). In
some variations, the signal may additionally be fed through another low
frequency, high pass filter or AC
coupling (1615) with cutoff at about 0.01 Hz.
[333] The above-described filters (in 2412, 2413, 2414, 2415) may combine to
form a second to fourth order
filter with an overall cutoff frequency of between about10 kHz and about
20kHz, which serves as an antialiasing
filter for the Sigma-Delta ADC downstream in the signal processing chain. At
20 kHz, the attenuation of the
second order filter is about -15 dB, which can easily be compensated for in
the digital domain. In some
variations, the internal ADC sampling rate is about 3 MHz, so sufficient
attenuation is needed at the Nyquist
frequency of 1.5 MHz. The second order filter achieves greater than -100 dB at
this frequency.
[334] The signal from the second stage amplifier and low pass filter (2414)
may be raised by an offset voltage
(2416) between about 0.5 V and about 5 V in certain variations. In certain
variations, the offset voltage may be
between 0.5 V and about 2 V, or about 1 V and about 2 V. The offset may depend
on the actual configured ADC
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range (e.g., the offset may be about 0.5 V at an ADC range of 0 V to 1 V).
This offset may, for example,
accommodate an ADC that only supports positive voltages for conversion. This
stage also may incorporate an
AC coupling capacitor with a cutoff frequency of about 0.01 Hz to 0.1 Hz
(e.g., about 0.05 Hz), which may
facilitate low frequency response and/or blocking DC offsets.
P351 FIG. 25A illustrates transfer functions for the example signal processing
circuitry of FIG. 24. FIG. 25B
illustrates the transfer function of the analog circuitry performing the first
set 2410 of analog signal processing
steps, using the above-described parameters. FIG. 25C illustrates the transfer
function of another analog
circuitry.
[336] Following the offset 2416, the signal may pass into the second set 2420
of analog signal processing
steps. As shown in FIG. 24, the first stage within the MCU may include a
Programmable Gain Amplifier (PGA),
which represents the third gain stage in the signal processing chain and
offers the flexibility of on-the-fly
adjustments of gain to optimize for ADC range. The general equation for
amplification is shown in Equation
5:
Vo.t= (Vh,¨ VRq) x Cain (5)
[3371 Accordingly, to amplify the dynamic signal, the offset added previously
in circuitry (2416) need to only
be Vi. As shown in the schematic of FIG. 26, a Digital-to-Analog converter
(DAC) 2620 may connected to the
VR,ipin of the PGA 2610, in order to achieve on-the-fly adjustments of the
value of VR,j. However, the DAC
2620 may add considerable noise to the amplifier beyond of what is acceptable.
To address this, a set of
capacitors 2630 may be added between the DAC signal to ground. Since the DAC
signal is generally static,
there is no concern on the dynamic behavior due to this addition ¨ except for
a short time period when voltages
changed.
[338] hi addition to enabling on-the-fly adjustments of gain, the PGA may
advantageously mitigate variation
of the offset voltage created by the upstream circuitry. This variation is,
for example, due to tolerances in
electronic components and can amount to up to +/- 20% variance on the offset
signal (in 1616). The PGA can
further be used to compensate for this offset and move the offset to half the
ADC reference voltage (e.g., of
2.048 V). Trying to move the offset to exactly half of this voltage, or 1.024
V, results in the following Equation
6 to determine proper V Ref:
JO24mV¨VIn xGain 1-Gain (6)
V
[339] Note that Equation 6 is only valid for gain greater or equal to 2.
Hence, in this example, the minimum
gain to be used is 2 rather than 1. Before calculation of this new VR,f, the
true offset present on each PCB must
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be known, which may be determined through calibration. For example,
determination of the true offset may be
achieved by recording the signal for some short period of time and determining
the offset value from the external
circuitry via forming the mean value. This can be either done on the MCU
directly or via the connected target
device, and the correction send back to the MCU.
[3401 Next on the signal chain is a Track-and-Hold component (2424), which
keeps the voltage constant upon
a trigger signal. The voltage is ideally constant for the duration the ADC
needs to sample a complete value; and
is important for accurate results. The trigger is fired at the end of the
previous ADC sample period, as the ADC
will immediately continue with the following sample.
[341] The Track-and-Hold voltage may be kept constant for a suitable
predetermined time, such as for about
5-50gs, before it is again released. The release allows the Track-and-Hold to
follow the current voltage for
another period of time (e.g., about 2 s) before the next trigger. When
sampling more than one sensor signal,
Track-and-Hold components may help ensure proper time synchronization among
the sensor signals, with
synchrony accuracy in the range of nanoseconds.
P421 The last component in the analog signal processing chain is the Sigma-
Delta ADC (2426). In some
variations, when internally running at about 3MHz the ADC utilizes
oversampling to achieve a signal of about
48-96kHz at 16 bits in a range of about 0 V to about 2.048 V. In some
variations, accuracy may be further
increased by referencing the ADC ground to the circuit board ground described
above.
P431 The analog signals entering the ADC may then be sampled into the digital
domain. Once analog signals
are sampled into the digital domain, they may be moved to a buffer location in
memory such as via fast DMA
transfers (2432). The signals may be further buffered within a ring buffer,
before assembled into packages
(2434) and transmitted to one or more external host devices (2436). These
packages may include a header and
the payload. The header may have a package/frame start ID and other
supplemental data that may help to keep
the data in order after transmission and help detect lost data points. The
payload is the sensor fusion data (e.g.,
vibroacoustic data, contextual data, etc.). In some variations, multi-modal
data points are transmitted in each
package via USB or wireless transmission (e.g., BLE, Bluetooth classic, Wi-Fi,
etc.) to one or more external
host devices 2404 (e.g., cloud, mobile computing device, etc.), such as for
analysis. However, it should be
understood that in other variations, other package sizes and/or other
communication modalities may additionally
or alternatively be incorporated. Additionally, or alternatively, analysis of
the vibroacoustic data may be
analyzed (e.g., using suitable machine learning models) locally on the sensing
device before the data and/or
analysis results may be similarly communicated to one or more external host
devices.
1.f. Encoding module
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PI Software-defined biotelephony is a software-intensive approach
to balance biosensing, communications
and digital health computing needs against those of a variety of networks with
which that user could operate.
This tradeoff includes the degree of flexibility that is created a-priori
(e.g. via a new protocol) versus the
restricted degree of autonomy permitted by existing radios and receivers.
P41 Encoding of audible/inaudible, seen/unseen, felt/unfelt,
contact/contactless, proximal/remote captured
data without loss of information such that any encoded signals will contain
and transfer the same breadth, depth,
quality and robust information whether be it via wireless or over wire is not
possible with existing CODECS.
Certain variants of the current technology's advancement of sensor module
combinations and sensor data fusion
also require improvements to methods and systems for data collection and data
communication. The proposed
technology contemplates sensing, processing, and transmitting vibroacoustic
and electrical, magnetic, and
electromagnetic signals having characteristic bandwidths from 0.01 Hz to over
1011 Hz (FIG. 1E), thus
appropriate hardware and associated software applications commonly called
CODECS
(compressors/decompressors) are required for enabling the operation of the
current technology.
[346] It is generally accepted that there are two general categories of
factors that affect fused encoded wide
bandwidth data streams which are output by a data stream (for example audio)
codec's encoder: in other words,
details about the source (e.g., audio's) format and contents, and the codec
and its configuration during the
encoding process. For each factor that affects the encoded data stream, there
is a simple rule that is nearly always
true: because the fidelity of digital data stream (for example audio) is
determined by the granularity and
precision of the samples taken to convert it into a data stream, the more data
used to represent the digital version
of the audio, the more closely the sampled sound will match the source
material.
P1 Variants of the current technology deal with both issues by
providing for highly efficient software based
ultra-high bandwidth coding, transmission, and decoding devices, methods, and
systems. Variants of the current
technology provide a transmitter-receiver system and methods configured to
receive and decode multi-modal
signals from multi-sensor data streams. Proposed signal transmitter-receiver
systems leverage "audio beacon"
data streams. Signal receivers of the present disclosure provide for accurate
signal decoding of a low-level
signal, even in the presence of significant noise, where the software
technology stack consumes very low power.
Also provided are systems that include the receivers, as well as methods of
using the same.
ihe effect of source audio fbrmat on encoded audio output
[348] There are several features that can be used to balance reproduction
quality and file size. Because
standard encoded radio data streams (e.g., audio, i.e., audible vibrations)
inherently use fewer bits to represent
each sample, the source audio format may actually have less impact on the
encoded audio size than one might
expect. However, a number of factors do still affect the encoded audio quality
and size. Table 1 shows key
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source audio file format factors considered and optimized in the present
technology and their accepted impact
on the encoded audio:
Table 1: The effect of source audio format and contents on the encoded audio
quality and size
Feature Effect on quality Effect on size
Each channel may substantially increase
Channel The number of channels affects only the perception
the encoded audio size, depending on
count of directionality, not the quality.
contents and encoder settings.
Unwanted background noise or hiss tends to
reduce audio quality both directly (by masking Hiss, static, or background
noise increases
Noise / details of the foreground audio) and indirectly (by the data stream
complexity, which
Hiss making the data stream waveform more generally reduces the
amount of
complicated and therefore difficult to reduce in compression possible.
size while maintaining precision).
The more samples available per second, the higher
Sample Increasing the sample rate increases the
the resulting encoded data stream fidelity is likely
rate encoded audio file's size.
to be.
Depends on the codec; codecs typically
have an internal sample format that may or
The larger the samples, the more detail each
Sample may not be the same as the original sample
sample can contain, resulting in more accurate
size size. But more source
detail may make the
representation of each sample.
encoded file larger; it will never make it
smaller.
[3491 The first, channel count, affects only the directionality or spatial
localization of the signal. Depending
on the content, the file size may be multiplied by the number of channels
encoded, or, in some schemes,
redundancies between the channels may be exploited to reduce the total file
size without a significant
degradation of the signals. Second, noise or hiss in the signal hiss tends to
reduce audio quality both directly
(by masking details of the foreground audio) and indirectly (by making the
data stream waveform more
complicated and therefore difficult to reduce in size while maintaining
precision. Thus, hiss, static, or
background noise increases the data stream complexity, which generally reduces
the amount of compression
possible. Third, the higher the sample rate, affects the quality the more
samples are available per second, and
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the higher the resulting encoded data stream fidelity is likely to be.
However, this comes at a cost of the encoded
file's size, or encoded stream's bit rate.
[350] Finally, the sample size affects the detail available in each sample,
this depends on the codec; codecs
typically have an internal sample format that may or may not be the same as
the original sample size. However,
more source detail may make the encoded file larger; it will never make it
smaller.
[351] The effects detailed above can be altered by decisions made during
encoding the data stream. For
example, if the encoder is configured to reduce the sample rate, the sample
rate's effect on the output file will
be reduced in kind.
[352] The current technology's codecs, in certain variations, employ software-
defmed hardware and firmware
algorithms to take source structural health and physiological health fused
data streams and compress them to
take substantially less space in memory or network bandwidth while not
sacrificing information or data quality.
In certain variations of encoder configuration, the encoder may be adjusted
using parameters that choose specific
algorithms, tune those algorithms, and specify how many passes to apply while
encoding.
[353] The current technology's Infrasound-to-Terahertz over wireless/IP
differs from traditional audio
CODECs by evolving and optimizing certain aspects for low frequency, low
amplitude biometric data
transmission: smart scalable switching (many more ports and easier to add just
what is needed), breaking the
barriers of distance, improved ratio of inputs to outputs, individual, fused
and multiplexed data stream standards
that extend beyond the local facility, convergence of low frequency, low
amplitude biometric data and radio
communications, and new options in local, edge and cloud processing.
[354] Hardwired, circuit-based switching is basically a point-to-point
technology. Wide-bandwidth data
stream matrix switchers are intelligent "destination- and at "source-
simultaneously. All the combinations of
transmitters to receivers are resolved inside the matrix switch and it is
possible match, allocate and optimally
use any source at any destination according to the number of signal
transmission and reception ports available
on the data stream matrix switch. For example, an 8x8 matrix switch allows
eight sources to be used at any of
eight destinations.
13551 Devices and systems of the current technology can perform local, edge
and back-end handshake
processing operations. Instead of just making any input available on any
output, for example, it is possible to
show any input on any¨as well as many¨outputs. Hence, a biometric data
transmission from a broad-band
biometric device, and data visualization can be a source that gets routed from
a device transmitter box to a data
visualization matrix switcher and then the switcher can be wired to multiple
devices that can simultaneously be
showing the biometric data stream in real time.
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[356] The wireless/IP (and packet-based switching) number of sources attached
to the wireless/IP switch is
unlimited. When physical ports run out, multiple wireless/IP switches can be
connected to expand. The number
of ports can be scaled to satisfy needs much more conveniently. It is possible
to keep adding sources and
destinations without a substantial overhaul of the data stream matrix switcher
centerpiece being a major limiting
factor.
[357] The ratio of inputs to outputs can also be tailored. It is possible to
have many inputs but only a few
outputs, or only a few inputs but many outputs. Or you can have many of both
and in widely different quantities.
[358] In certain variations, current technology's Infrasound-to-Terahertz over
wireless/IP significantly
increases flexibility by overcoming limits to number of sources and
destinations as well as by conquering
distance limits.
[359] In certain variations, the current technology's Infrasound-to-Terahertz
over wireless/IP devices use
standards-based packetization for transmission on wireless/IP networks and
compatibility with wireless/IP
switches, and some use proprietary packetization schemes which also work on
wireless/IP networks and
standard wireless/IP switches but which do not work with other products in the
market.
[360] In general, standards-based schemes provide the potential for
interoperability between products from
different vendors.
[361] In certain variations, the current technology's standards-based and
proprietary packetization schemas
do not alone determine interoperability and also do not establish whether a
product is more, or less, secure.
What provides data safety and security is current variations of the Infrasound-
to-Terahertz over wireless/IP
encoders and decoders that are tightly coupled. One reason for this tight
coupling is to provide guaranteed
specifications and performance. This also allows for a very controlled out-of-
the-box ease of set up and ease-
of-use experience.
P621 Encryption technologies exist for several aspects of the current
technology's Infrasound-to-Terahertz
over wireless/IP products, and they address multiple components of data stream
system design.
[363] The current technology's devices provide encryption on the command-and-
control signaling to encoder
and decoder devices. This offers security against hacking the actions of the
boxes¨including turning streaming
on or off, or switching what source is being displayed. Another security
aspect is the ability to encrypt the data
streams themselves. This ensures that if the data stream is intercepted; it
cannot be simply decoded and viewed.
[364] In other embodiments, the current technology's products provide support
for third-party devices using
digital key exchanges or encryption. Leveraging learning from consumer
examples, the overwhelming majority
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of AV customers are concerned with the most straightforward case¨which is High-
bandwidth Digital Content
Protection (HDCP). The purpose of HDCP is to protect digital copyrighted
content as it travels between devices.
For instance, a cable or satellite receiver box, or a media player with HDMI
outputs, might play content in HD
or 4K that is protected content. Such content is locked and can only be viewed
by HDCP-compatible products
once they arc properly authenticated. Similarly, the current technology's data
streams have distributed ledger
(e.g., blockchain) provenance, records, security and restrictions on how
protected content can be extended,
multiplied, altered, or viewed.
Piggybacking data transfer protocols and other CODECs to transfer Infrasound-
to-Terahertz over wireless/IF
[365] The telephone Touch-Tone protocol is probably the most ubiquitous
audible data transmission heard
daily. Wherein, multi-frequency tones arc used to dial numbers over the voice-
frequency band. Similarly,
infrasound, ultrasound and terahertz data streams can be overlaid onto audible
sounds for faithful broadband
data stream communications. Structural and physiological gray and standard
health data collected by the current
technology's sensor fusion and data fusion platform of data should are encoded
onto an inaudible, near-
ultrasound layer placed on top of normal, audible sounds and or onto an
inaudible, near-infrasound layer placed
on just below normal, audible sounds to cover broad-bandwidth data
transmission. The near-infrasound and/or
near-ultrasound layer overlay, turns any acoustic stethoscope, any smariphone
any microphone and speaker,
IoT device, etc., into a data-transfer device that then could be used for
health data transfer, health insurance
payments transfers, user authentication, and smart city applications such as
digital locks, mass-transit turnstiles,
etc.
[366] A generic interoperable infrasound-to-Terahertz over wireless/IP
platform takes advantage of the lack
of a common universal protocol to connect Internet of Things and leverages the
greater power, performance,
intelligence, etc of smart phones, smart speakers, IoT watched and
any/everywhere digital solutions
proliferating around us to perform connections.
[367] The current technology weaves infrasound-to-Terahertz data streams into
common vehicles of audible
sounds, such as Vail), streaming music, etc., public announcements. Infrasound
and Ultrasound is the type of
vibration/sound that the human ear does not register, but specialized
equipment can pick up.
[368] Smartphones, or any microphone, then, could be used to receive the
generated audio pulses and decode
the data. In turn, a smartphone speaker within proximity could send a
cataloged data stream frequency tag to
any receiver, such as one embedded in turning on the technology of the system
100. Indeed, any specific action
could be triggered, including a purchase or communicating with a automated
call center.
[369] In certain variations, patients entering urgent care could be
identified, greeted, registered and processed
via targeting/beaconing using a combination of legacy stored and real-time
collected infrasound-to-Terahertz
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data streams using bring-your-own smart devices and in situ speakers. The
infrasound-to-Terahertz over
wireless/IP solution communicates even when smartphones are in Airplane Mode
and data is turned off, for use
in high security environments and the transportation vertical. Traditional
networks, such as wireless, can
overload when important information needs communicating ¨ such as during a
public safety incident. The
intelligent system manages and optimizes congestion issues that might occur in
a large crowd-gatherings, such
as at a stadium. Additionally, leveraging "audio" smart phone/speaker beacons
requires less battery -intensive
than Bluetooth.
[370] In certain other variations, the WLAN (Wireless Local Area Networks)
that originated in 1985
controlled by the United States Federal Communications Commission (FCC). the
unlicensed spectrum in three
different regions to be used in Industry (902-928 MHz), Science (2400-2483.5
MHz) and Medicine (5725-5850
MHz), provides the ability to he Infrasound-to-Terahertz over wireless/IP
solution to take advantage of the
multi-vertical freedoms across a cooperative spectrum broad frequency network.
1.g. Artificial intelligence module
[371] Without the right algorithms to refine data, the real value of high-
resolution sensor data fusion will
remain hidden. Popular approaches such as neural nets model correlation, not
causal relationships, and do not
support extrapolation from the data. In contrast, Developers have developed a
novel Structural Machine
Learning (SML) platform, which is a natural feedforward and feedback platform,
where data exploration and
exploitation can be achieved faster and more accurately. Automatic expression
synthesis tools build
generalizable and evolving models, distilling the sensor data into human-
interpretable form, yielding the true
value of fused data in an intelligent, agile, networked, and autonomous
sensing/exploitation system.
[372] hi this respect, some variations, the system 10 includes an artificial
intelligence module which is
configured to use machine learning and other forms of adaptation (e.g.,
Bayesian probabilistic adaptation) to
optimize analytical software including data-driven feedback loops, for
purposes of analyzing the vibroacoustic
and/or other sensor data. The training of such machine learning models for
analyzing data from the sensing
device may begin with human- derived prior knowledge, or "soft knowledge"
artefacts. These "soft knowledge"
artefacts are advantageously generally much more expressible than off-the-
shelf ML models like neural nets or
decision trees. Furthermore, in contrast to mainstream machine learning
scenarios that have clearly delineated
training and test phases, analytical software for analyzing data from the
sensing device may involve learning
and optimizing software inline. In other words, the notion here is to embed an
"inline learning" algorithm within
an artificial intelligence (Al) software system, allowing the Al system to
learn adaptively as the system
processes new data. Such inline (and real-time) adaptation typically leads to
more performant software Al
systems with respect to various functional and nonfunctional properties or
metrics, at least because (i) the Al
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system can correct for the suboptimal biases introduced by human designers and
(ii) respond swiftly to changing
characteristics operating conditions (mostly to variation in data being
processed).
[373] With respect to analyzing specifically vibroacoustic data, the
vibroacoustic biofield harvested from
patients may be saved as audio (way) files. Custom cross frequency coupling
methodology, in combination
with averaging wavelets such as Daubechies and Haar wavelet approaches, may be
used to analyze the
infrasound data as static images within set time windows. The Haar wavelet is
the first and simplest orthonormal
wavelet basis. Since the Daubechies wavelet averages over more data points, it
is smoother than the Haar
wavelet and may be more suitable for some applications. Typically, the audio
scenes are of complex content,
including background noise mixed with rich foreground having audible and
inaudible vibrations and their
context. In general, both background noise and foreground sounds can be used
to characterize a "diagnostic
scene" for use in characterizing a subject. Other data like contextual data
could be converted into a visual 2D
representation and attached to the static infrasound images to create a new
image. Such new image is then
analyzed as a whole to increase the performance of the algorithm.
[374] However, foreground sounds typically occur in an arbitrary order,
thereby making hidden sequential
patterns hard to uncover. Thus, the ability to recognize and "unmask'. a
surrounding diagnosis environment by
isolating and identifying contextualized audible and inaudible vibration
signals has potential for many
diagnostic applications. One approach to accomplish this is to shift from
conventional classification techniques
to modern deep neural networks (DNNs), and rand convolutional neural network
(CNNs). However, despite
their top performance, these network variants may not be sufficiently capable
of modeling sequences in certain
applications. Thus, in some variations the Al system may incorporate combined
deep, symbolic, hybrid
recurrent and convolutional neural network R/CNNs. Furthermore, in some
variations, a separate DNN may
generate and propose a -crisp" (symbolic) program, where feedback from
execution of such a program may be
used to tune/train the above DNNs and/or CNNs in a hybrid symbolic-subsymbolic
approach.
[3751 in some variations, sensitivity of the sensing platform may be increased
by using biophysiologically
precise simulated patient entities for machine learning algorithm training
purposes. For example, such simulated
entities may be uploaded and modified in a training environment using high
precision clinical data (e.g., heart
rate, pulse rate, breathing rate, heart rate variability, breathing rate
variability, pulse delay, core temperature,
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upper and lower respiratory temperature gradients, etc.) collected from well-
characterized clinical patients to
create a large, realistic training dataset.
[376] In certain variations, the machine learning module is configured to (i)
design a Covid-19 biosignature
in a training phase using variations of the sensing devices and systems
described herein, and/or (ii) apply the
Covid-19 biosignature using variations of the sensing devices and systems
described herein.
P771 Novel aspects of methods executed by the machine learning module comprise
posing a machine
learning problem (here: designing of a COVID-19 biosignature) as a task of
program synthesis. To that aim, a
domain-specific language (DSL) was designed to express various designs of a
biosignature as programs in that
language. In certain variations, inputs to the DSL comprise raw time series
(detected frequency signals) as well
as various types of features extracted from the series, like FFT spectrum,
STFT spectrograms, MFCCs, vibe-
scale features, peak locations, and more. These correspond to specific data
types in the bespoke DSL. The DSL
is equipped with functions (instructions) that can process inputs and
variables of particular types. The DSL
functions are based on domain specific knowledge. For instance, DSL functions
we use now routinely include:
convolution, peak finding, parameterizable low-pass and high-pass filters,
arithmetic of time series, and more.
[378] Importantly, these building blocks are defined on a much higher
abstraction level than the typical
vocabulary of SOTA ML techniques, where for instance deep learning models are
essentially always nested
compositions of dot products with nonlinearities. Secondly, they build upon
the available body of knowledge
that proved useful in signal processing and analysis in several past decades.
Thirdly, the grammar of the DSL
permits only operations that make sense in the context of signature
identification, and can be used to convey
experts' knowledge about the problem.
p791 Expressing the models as programs can benefit from a wealth of
theoretical and practical knowledge
concerning the design and semantics of programming languages. Concerning data
representation, we can rely
on the formalized approach of type systems, which allow us to reason about
data pieces, their relationship and
their processing in a principled and sound way. To that aim, we rely on the
fundamental formalism of algebraic
data types, which allows systematic creation of new data types by aggregation
and composition of existing
types. In some variants (e.g. so-called dependent types), we can 'propagate'
the properties of data through
functions and so constrain their output types. Next, the actual processing of
data can be conveniently phrased
using recursion schemes, which provide a universal framework for aggregation
and disaggregation of
information for arbitrary, variable-size data structures (e.g. time series).
Last but not least, the DSL is designed
in a way that is compatible with the structure characteristic of a problem.
p801 For applications of systems, methods and sensing devices of the present
technology to detect Covid-I9
infection in subjects (see, Example 8, for example), the snucture stems from
the matched case-control setup,
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where observations (recordings) span multiple "dimensions" related to the
location of auscultation point,
patient's position, age, sex, etc. These observable factoring variables can be
explicitly built into the DSL. Unlike
deep learning approaches, this facilitates the discrimination between
correlation and cause, by filtering out of
other, confounding variables. This allows the capture and exploitation of
various structures on several levels,
among others intra-recording (by aggregating multiple alternative feature
extraction techniques), and inter-
recording, by exploiting the structure endowed by the matched case-control
(MCC) study design.
[381] The above mechanisms can "regularize- the process of program synthesis
and make it more likely to
find a solution (program) that is plausible for a given problem, and in
particular which does not overfit to the
available training data, making valid generalization more likely. This makes
it possible to synthesize robust
signatures, classifiers and regression models from limited numbers of training
examples.
1.h. Other features of the system
[382] In some variations, full-spectrum vibroacoustic sensing may be
selectable by enabling or disabling
vibroacoustic sensing features based on a software-as-a-service subscription
model. The one or more sensing
devices may, for example, transition between a base or minimum functionality
state, in which no vibroacoustic
sensing is performed. In variations in which the sensing device is a
customized piece of medical equipment such
as that described below (e.g., stethoscope), the base functionality state may
be a mode in which the voice coil
is active via standard air tubes, akin to the traditional acoustic
stethoscope. Functionality may then be scaled to
one or more intermediate functionality or maximum functionality levels. At
intermediate levels, certain features
may be partially enabled or provided at a degraded level, while at a maximum
functionality level, all
vibroacoustic sensing features are functional. Furthermore, in some
variations, these functionality modes may
additionally or alternatively be intentionally selected by the user as
different operating modes of the sensing
device (e.g., the user may disable sensing of inaudible frequencies if such
signals are not of interest in a
particular application). Additionally, or alternatively, in some variations, a
control mechanism may be hard-
wired or coded via software programming to the power control to prevent
tampering.
[383] in some variations, an internal controller may control the functions of
the sensing device based on the
level of service available to the user (e.g., as a subscription service). The
controller also may authenticate parts
of the sensing device (e.g., any disposable components such as interchangeable
modules), and license data,
serial numbers, and/or other data structure, which may allow the subscription
to be identified. Additionally, or
alternatively, the controller may store levels of service, permissions,
subscriptions, and/or any other relevant
data to determine the level of service at any given time. The license, serial
number, clock and/or calendar data
is stored in non-volatile memory so that even under conditions of loss of
power, significance subscription-
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relevant information is not lost. The controller may be triggered by the
reception of a key. The key may set the
level of service, the duration of service, and/or the number of times a
service may be peifonned, for example.
[384] Additionally or alternatively, the key may securely link the sensing
device to local and/or cloud-based
health record data management solutions. A subscriber may, for example, link a
permissioned computing
device, such as a smart watch, cell phone, tablet, or computer, directly to
the sensing device (e.g., using a
keypad, a wireless technique such as NFC, and/or optical techniques such as
reading an image such as a QR
code) and this process may provide the key to the device. In some variations,
the computing device may become
a tether to the sensing device that communicates and connects the device via
cables or wirelessly to the cloud,
other external devices, etc. using wireless and/or wired communication modes
such as those described above.
In some variations, the information entered into the computing device may be
combined with encrypted license
data, serial numbers, and/or other data structure on the vibroacoustic sensing
device and relayed to a cloud-
based server, which may verify the information and then send the operational
subscription key combining starts
and end date of subscription and/or other details.
[385] Furthermore, in some variations, subscription data may be combined with
device usage data (as
described above) to support and/or control device functionality in academic or
professional settings, for
institutional policy monitoring, and/or behavior change support in home use,
etc.
1.1. Sensing device variations
[3561 As described above, the sensing device may incorporate various
components in a modular fashion and
may have any various suitable form factors.
Integrated handheld devices
[387] For example, in some variations, the sensing device may include a
handheld housing. As described
above with reference to FIGS. 3A and 3B, and 4A and 4B in some variations the
housing may be standalone
and integrated into the handheld sensing device 300, 400. The sensing device
300, 400 may be used, for
example, as a point-of-care device for assessing one or more bodily conditions
of a subject. The sensing device
300, 400 may have a wide bandwidth capable of detecting a full spectrum of
vibroacoustic signals (e.g., between
about 0.01 Hz to about 160 kHz) associated with the subject. In some
variations, the sensing device 300, 400
may be used as part of a telemedicine platform, for example. It should also be
understood that the stackup shown
in FIG. 3B, 4B is exemplary only, and components may be packaged in other
suitable configurations within the
housing.
p881 FIGS. 27A and 27B depict an exemplary variation of a sensing device 2700
including a handheld
housing as part of an integrated handheld device. Like the sensing device 300,
the sensing device 2700 may
include a handheld housing 2710 with a base 2702, where the housing 2710
substantially- surrounds one or more
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of the modules and other various components as described above (e.g.,
vibroacoustic sensor module 2720,
electronics system 2740, at least one power source 2742, impedance matching
diaphragm 2750). In some
variations, the housing 2710 may be assembled from multiple components that
couple together via one or more
fasteners or through mechanical interlocking features (e.g., mating features),
etc. For example, as shown in FIG.
27B, thc housing 2710 may include a housing body 2711 (which may, for example,
include a power port 2714)
that couples to a top cover 2712 and a bottom cover 2713 so as to enclose the
components of the sensing device
2700. In some variations the sensing device 2700 may further include a
contextual sensor module similar to that
described above. In contrast to the sensing device 300 shown in FIG. 3B and
4B, the sensing device 2700 is
more cuboidal and omits a display. The sensing device 2700 may be used, for
example, as a point-of-care
wideband scanner device for assessing one or more conditions of a subject,
where the sensing device 2700 has
wide bandwidth capable of detecting a full spectrum of vibroacoustic signals)
e.g., between about 0.01 Hz to
about 160 kHz) associated with the subject. Like the sensing device 300, in
some variations the sensing device
2700 may be used as part of a telemedicine platform, for example. It should
also be understood that the stackup
shown in FIG. 27B is exemplary only, and components may be packaged in other
suitable configurations within
the housing.
[389] FIGS. 28A and 28B depict an exemplary variation of a sensing device 2800
including an ergonomic
handheld housing as part of an integrated handheld device. The sensing device
2800 may be similar to the
sensing devices 300, 400 and 2700 described above, except that the housing
2810 in the sensing device may be
molded and contoured for a more ergonomic handheld grip. In some variations,
the sensing device 2800 may
designed to be held in a left hand, or designed to be held in a right hand, or
designed to be comfortably held in
either the left hand or right hand of a user. In some variations, as shown in
FIG. 28B, the housing 2810 may be
assembled from multiple components that couple together via one or more
fasteners or through mechanical
interlocking features (e.g., mating features), etc. For example, as shown in
FIG. 28B, the housing may include
a housing body with couplable body portions 2811a and 2811b. The housing body
may further couple to a top
cover 2812 and a bottom cover 2813. Furthermore, the housing 2810 may be
coupled to a base 2802 and
configured to substantially surround one or more of the modules and other
various components as described
above (e.g., vibroacoustic sensor module 2828, electronics system 2840, at
least one power source 2842,
impedance matching diaphragm 2850). In some variations the sensing device 2800
may further include a
contextual sensor module similar to that described above. The housing 2810 may
also include a power port 2814
for recharging the power source 2842, for example. It should also be
understood that the stackup shown in FIG.
28B is exemplary only, and components may be packaged in other suitable
configurations within the housing.
Wearable devices
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[390] In some variations, the sensing device may include a wearable housing.
The wearable housing may, for
example, be coupled to an adhesive patch configured for attachment to a
surface (e.g., skin) of a subject in a
suitable body location (e.g., chest, stomach, etc.). As another example, the
wearable housing may be coupled to
a suitable garment (e.g., clothing such as a shirt or jacket, a chest strap, a
belly band, arm band, etc.) for detecting
vibroacoustic signals from a subject wearing the garment. In other
embodiments, the wearable housing may
comprise a sleeve, cuff, harness or collar. Accordingly, in such variations
the sensing device may enable
continuous monitoring of the subject for one or more bodily conditions.
1_391] FIG. 29A depicts an exemplary variation of a sensing device 2900
configured as a wearable device. For
example, the sensing device 2900 may include a housing coupled to an adhesive
patch for attached to a user.
The housing may include a top cover 2912 couplable to a bottom cover 2913
(e.g., through mechanical
interlocking features, fasteners, etc.) so as to substantially surround
internal components of the sensing device.
Similar to that described above, the sensing device 2900 may include a
vibroacoustic sensor module 2920, at
least one power source 2942, and an electronics system 2940. The sensing
device 2900 may have a wide
bandwidth capable of detecting a full spectrum of vibroacoustic signals (e.g.,
between about 0.01 Hz to about
160 kHz) associated with the subject. Furthermore, in some variations the
sensing device 2900 may include an
impedance matching diaphragm (not shown) and/or a contextual sensor module
(not shown in FIG. 29A)
providing additional sensor data for use in analysis. For example, in some
variations, the contextual sensor
module may include supplementary sensors such as a microphone and/or a 9-axis
inertial measurement unit
(e.g., including a tri-axis accelerometer, tri-axis gyroscope, and tri-axis
magnetometer). FIG. 43 illustrates
example data from such an example variation of a contextual sensor module. In
the arrangement shown in FIG.
29A, a continuous opening from a surface of the user to the vibroacoustic
sensor module 2920 may be provided
by aligned openings in an attachment backing 2902, the lower cover 2913,
and/or the electronics system 2940.
For example, the attachment backing 2902 may include an adhesive patch. It
should also be understood that the
stackup shown in FIG. 29A is exemplary only, and components may be packaged in
other suitable
configurations within the housing.
13921 In some variations, a sensing device similar to sensing device 2900 may
be coupled to a garment, so as
to detect and measure vibroacoustic data and/or other sensors when the garment
is worn by the subject. For
example, the attachment backing 2902 may include an adhesive patch may
attached to an outer or inner surface
of a garment. As another example, the sensing device may be attached to the
garment by securing the housing
(e.g., lower cover 2913) to the attachment backing 2902 placed on an opposite
surface of the garment, such that
a layer of the garment may be sandwiched between the backing and the housing.
For example, the attachment
backing 2902 may be placed adjacent an inner surface of the garment, the
housing may be placed on an outer
surface of the garment, and the attachment backing and housing may be coupled
together via one or more
fasteners (e.g., adhesive, mechanical fasteners, magnets, etc.), and/or
interlocking parts (e.g., threads, snap fit
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mating features, latches, etc.). As yet another example, the housing of the
sensing device 2900 may be sewn to
the garment.
[393] In another variation, and referring to FIG. 29B, there is provided a
wearable sensing device 2950 which
is configured to monitor blood pressure of the subject non-invasively and
whilst permitting the subject to be
mobile such as ambulatory.
P941 Conventionally, when measuring blood pressure, a cuff is applied to the
upper arm and inflated such
that blood flow through the brachial artery, or other blood vessel ,is
restricted. When pressure is released, blood
is again able to flow. During this time, a clinician listens, using a
stethoscope, to blood pressure sounds (known
as Korotkoff sounds) in the blood vessel. As pressure increase or decreases,
different phases can be heard,
ultimately concluding with phase V when no sound is audible. This method is
still considered the gold standard
for noninvasive blood pressure measurement. While there have been advancements
in the technique for upper
arm constriction, the quality of stethoscopes. and most recently fully
automatic blood pressure devices ¨ the
overall process has not changed significantly. However, this method does not
allow for cuffless monitoring
blood pressure monitoring¨for that, a needle must be inserted into an artery.
Present technology permits non-
invasive and possibly cuffless blood pressure monitoring. Therefore,
monitoring over longer time periods is
possible.
[395] Korotkoff sounds are broken down into five distinct phases, each with a
distinct sound and waveform
associated with the phase. The first sound appears as the pressure approaches
systolic blood pressure and the
diastolic blood pressure measurement is by the disappearance of sound.
Korotkoff himself described three, and
later, five phases to the arterial sounds: appearance, softening, sharpening,
muffling, and disappearance.
Korotkoff suspected the net transmural pressure oscillating from positive to
negative was responsible for the
different phases of sound. This technique has come to be known as the
auscultatory method. Phase I has a clear
tapping tone. Phase II is associated with a softening of the tapping and a
swishing element. Phase III sounds are
similar to Phase I but with distinct sharpening. Phase TV is noted to have
abrupt muffling of the sounds, followed
by Phase V which is the cessation of all sounds. The Phases of arterial sounds
occur during the indirect
measurement of blood pressure using an air-filled cuff, usually placed around
the upper arm and inflated initially
to above the maximal or systolic blood pressure. As cuff pressure is slowly
released, arterial sounds can be
heard through a stethoscope placed over the artery distal to the cuff or by a
microphone placed inside the cuff.
Sounds appear as cuff pressure approaches systolic pressure, increase in
amplitude, then generally diminish,
and finally disappear at a cuff pressure close to the minimal or diastolic
blood pressure.
[396] Referring to FIG. 29B, the wearable sensing device 2950 may include a
wearable housing 2952
configured to be positioned directly on a skin of the subject, or indirectly
through clothing. The wearable sensing
device may have any appropriate form factor such as, but not limited to, a
patch, a band-aid, a sleeve to be worn
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around a limb, a compression bandage, etc. In other embodiments, the wearable
sensing device system may be
embodied in a hand-held device such as those illustrated in FIGS. 3-17.
[397[ The sensing device 2950 may include a vibroacoustic sensor module 2954
as described herein, for
example with reference to FIGS. 16 -18 and FIG. 41. The vibroacoustic sensor
module may be configured to
capture acoustic signals with ranges selected from one or more of: about 0.01
Hz to about 20 kHz, about 0.01
Hz to about 50 Hz, less than about 50Hz, about 4000 Hz to about 20 kHz, and
more than about 4000 Hz.
Detecting acoustic signals beyond the human range of audibility for blood
pressure determination, can provide
for more precise and continuous measurement of blood pressure and allow better
clinical decision making.
[398] The sensing device 2950 may also include a pressure module 2956 housed
in the wearable housing
2952 and configured to apply pressure to the skin of the subject. More
specifically, the pressure module 2956
may be configured to have pulsatile fluid flow that causes bladder expansion
and /or contraction to apply
pressure to a blood vessel of the subject through the skin when the wearable
sensing device 2950 is applied to
the skin.
[399] In certain embodiments, the pressure module 2950 comprises: a fluid
channel network configured to
selectively permit fluid flow therewith to selectively apply a pressure to the
skin of the subject; optionally a
fluid reservoir in fluid communication with the fluid channel network for
supplying fluid to and/or from the
fluid channel network, and at least one pump for causing the fluid to flow
through the fluid channel network.
The fluid channel network may be a in icrofluidic channel network. The fluid
channel network may comprise a
plurality of channels that are configured to permit fluid flow therethrough.
The channels may be modulatable
between an expanded and a contracted state, such that when they are positioned
next to the skin, modulation
between the expanded and contracted states causes application of pressure to
the skin. The pressure module
2950 is a closed loop system.
[400] More specifically, in certain embodiments, the wearable sensing device
2950 is a wired/wireless,
powered/battery-free opto/vibro-fluidic cuff system comprising six subsystems:
(i) a low-modulus (-3 MPa),
elastomeric housing for contact with the skin and interfacing with large and
small arteries; (ii) a thin microfluidic
channel structure (one, two to as many as 20 channels each with total cross-
sectional areas of about 60 tun by
about 60 tun; total thickness, about 200 gm) that terminates at the housing
for targeted response to stimuli at
the housing-skin interface; (iii) a high-efficiency, microscale inorganic
light-emitting diode (g-ILED; about 270
gm by about 220 gm by about 50 gm) that also resides in the housing for
delivering light at the target location;
(iv) a fluid reservoir (radius, about 5 mm; thickness, about 4 mm) that
contains fluid, programmable pumping
microsystems, and hardware for wireless power harvesting, control, and
management; (v) a mechanically
compliant, serpentine electronic interconnect joining the g-ILED to the base
station; and (vi) a collection of
external hardware and software systems for independent, wireless control over
the g-ILED and microfluidics
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In the device described here, four miniaturized electrochemical microptunps,
selected because of their low
power consumption and negligible heat generation, couple to a corresponding
set of reservoirs to initiate micro-
pressure generation and sensing. The small size and light weight (about 0.3 g)
of this integrated system allow
for complete closed-loop operation.
[401] In certain embodiments, the applied pressure to the skin has a
predetermined pressure profile, the
processor being configured to cause the pressure module to create the
predetermined pressure profile. The
predetermined pressure profile may be configured to induce Korotkoff sounds in
the subject's blood vessel. The
vibroacoustic sensor module may be configured to detect Korotkoff sounds in
response to the predetermined
pressure profile being applied. The predetermined pressure profile may
comprise that required to restrict flow
in a blood vessel.
[402] Unlike conventional methods of blood pressure monitoring, in embodiments
of the present technology,
the pressure module is configured such that pressure is applied to at least
one target area on the skin, wherein
the at least one target area does not extend all the way around a limb of the
subject. In other words, the
pressurizing cuffs of the prior art are avoided. In this respect, the wearable
housing of the wearable sensing
device 2950 is configured to contact the at least one target area on the skin,
wherein the at least one target area
on the skin does not extend all the way around the limb of the subject. The
target area may comprise a portion
of the skin under which lies the brachial artery, for example. In other words,
the applied pressure is targeted.
[403] This may be useful in the monitoring of chronic disease, management of
patients in critical conditions,
as well as those under anesthesia. Currently, cuffless accurate blood pressure
monitoring requires insertion of a
catheter into the radial artery. Additionally, hypertension is a pervasive
chronic disease affecting approximately
65 million adults in the United States, and a significant cause of morbidity
and mortality. Antihypertensives are
widely prescribed due to their effectiveness in lowering blood pressure,
thereby reducing the risk of
cardiovascular events. However, the phenomenon of the "white coat effect" may
be a complicating factor in the
diagnosis and management of hypertensive patients. It is well established that
a considerable number of people
experience an elevation of their blood pressure in the office setting, and
particularly when measured by a
physician_ The cause of this white coat hypertension, as well as its
implications in the prognosis and treatment
of hypertension, is still controversial. In both these use cases (and more)
cuffless noninvasive arterial blood
pressure monitoring would be ideal.
[404] Furthermore, embodiments of the present technology can also reduce or
eliminate practitioner errors
introduced during the conventional blood pressure measurement. Conventionally,
a practitioner taking the blood
pressure of a subject determines the maximum inflation pressure before they
take blood pressure. The maximum
inflation pressure is the number on the sphygmomanometer that the cuff is
inflated to when measuring blood
pressure. To determine the maximum inflation pressure, the brachial or radial
pulse is manually palpated while
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inflating the cuff The cuff is inflated 30 mm Hg past the obliteration point
of the pulse (ie., the pulse is no
longer felt). Auscultation is initiated while the pulse cannot be felt. This
no pulse value is the maximum inflation
pressure number. If maximum pressure inflation is not determined, an
auscultatoiy gap could go unrecognized,
and as a result the blood pressure could be underestimated (lower than the
actual value). An auscultatory gap is
a silent interval when the Korotkoff sounds go absent and then reappear while
you arc deflating the cuff during
blood pressure measurement. This gap is an abnormal finding and can occur due
to arterial stiffness and
arteriosclerotic disease. It is typically observed in people with a history of
hypertension who have been treated
with prolonged antihypertensive medication. Thereby, embodiments of the
present technology permit blood
pressure measurement to be performed continuously during rest, activity, and
in any setting.
[405] There may be provided a plurality of pressure modules and a plurality of
vibroacoustic sensor modules.
These may be embodied in one wearable housing or in different wearable
housings such as different patches.
[406] The wearable sensing device 2950 may further include one or more
sensors, such as: an electric sensor
for measuring electric potential of the skin or blood vessels; one or more
MEMS microphones; a sensor for
measuring bioimpedance, skin conductance, galvanic skin response,
electrodermal response, or elcctrodermal
activity; an optical sensor for obtaining optical data relating to the skin or
blood vessels under the skin; an
environmental sensor for obtaining data relating to an environment of the
subject, comprising one or more
selected from: ambient temperature, ambient humidity, ambient radiation;
barometric pressure, altitude, ambient
noise, and ambient light; IMU; GP S; a thermometer for measuring body
temperature.
[407] Any of the pressure module 2956, the vibroacoustic sensor module or any
of the above-described
sensors may be communicatively connected to a processor 2958 of a computing
system. For example, the
vibroacoustic sensor module 2954 may be communicatively connected to the
processor 2958 such that the
processor is configured to receive acoustic data from the vibroacoustic sensor
module 2954. The computing
system may have a memory storing executable instructions that, when executed
by the processor 2958, cause
the processor 2958 to process received data. The processor may also be
configured to cause the pressure module
to apply the pressure to the skin. The processor may be at least partially
housed in the wearable housing 2952
or remote therefrom. The processor is configured to receive the acoustic data
an optionally other data from the
sensors and to execute a method for determining the blood pressure of the
subject from the acoustic data and
optionally the applied pressure. The processor may execute a trained algorithm
in the method. The processor
may be configured to amplify the acoustic signal detected by the
vibroacoustic. Alternatively, or in addition to,
there may also be provided an amplifier component for amplifying the acoustic
signal.
[408] There may also be provided a haptic device associated with a user of the
system, the haptic device
communicatively coupled to the processor, the processor is configured to cause
the haptic device to vibrate with
a vibration pattern corresponding to the determined blood pressure of the
subject. The haptic device may be
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configured to reproduce a haptic signal in three dimensions. The haptic device
may be in the form of at least
one patch.
[409[ Referring now to FIG. 29C in which is shown another sensing device 2950'
for determining blood
pressure and which uses sound and light. As before, the sensing device 2950'
comprises a housing 2952'
configured to be positioned directly on a skin of the subject, or indirectly
through clothing. The sensing device
2950' may have any appropriate form factor such as, but not limited to, a
patch, a band-aid, a sleeve to be worn
around a limb, a compression bandage, etc. In other embodiments, the sensing
device may be embodied in a
hand-held device such as those illustrated in FIGS. 3-17.
[410] The housing 2952' is configured to house a vibroacoustic sensor module
2954' as described herein, for
example with reference to FIGS. 16 -18 and FIG. 41. The vibroacoustic sensor
module may be configured to
capture acoustic signals with ranges selected from one or more of: about 0.01
Hz to about 20 kHz, about 0.01
Hz to about 50 Hz, less than about 50Hz, about 4000 Hz to about 20 kHz, and
more than about 4000 Hz.
Detecting acoustic signals beyond the human range of audibility for blood
pressure determination, can provide
for more precise and continuous measurement of blood pressure and allow better
clinical decision making. In
certain embodiments, the vibroacoustic sensor module provides 16-bit data
samples at a data rate of 48 kHz
without compression. In other embodiments, the vibroacoustic sensor module may
have a piezoelectric
transducer.
[411] The sensing device 2950' may also include a pulse and plethysmography
sensor for measuring electric
impedance of the skin for impedance plethysmography (IPG) determination of
changing tissue volumes in the
body. In certain embodiments, the pulse and plethysmography sensor provides 12-
bit data at a rate of about 100
Hz. In certain embodiments, the pulse and plethysmography sensor may be
connected to an indicator such as a
green LED light source.
[412] The sensing device 2950' may also house an electric potential sensor
(EPS) 2959' which is an active
ultrahigh impedance capacitively coupled sensor. The absence of 1/f noise
makes the EPS ideal for use with
signal frequencies of ¨10 Hz or less. EPS can be used to measure both standard
electrocardiogram and galvanic
skin response.
[413] In certain embodiments, the sensing device 2950' may include a dry
electrode bioelectric sensor. In
certain embodiments, the sensing device may be similar in structure to that
described in FIG. 4A-4E and
including a plurality of bioelectric sensors. See example 11.
[414] The sensing device 2950' may further include one or more sensors, such
as: an electric sensor for
measuring electric potential of the skin or blood vessels; a time of flight
sensor, a MEMS microphone; a sensor
for measuring bioimpedance, skin conductance, galvanic skin response,
electrodermal response, or
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electrodermal activity; an optical sensor for obtaining optical data relating
to the skin or blood vessels under the
skin; an environmental sensor for obtaining data relating to an environment of
the subject, comprising one or
more selected from: ambient temperature, ambient humidity, ambient radiation;
barometric pressure, altitude,
ambient noise, and ambient light; IMU; GPS, a thermometer for measuring body
temperature.
[415] In certain embodiments, when present, the bioimpedance/electrodermal
activity sensor comprises an
Analog Devices front-end chip utilizing a serial peripheral (SPI) interface.
AC bioimpedance/electrodermal
activity.
[416] In certain embodiments, when present, the GPS provides
longitude/latitude precision at 64 bits/sample.
In another embodiment, the GP S system is interrogated from about 0.0167 to
about 1 Hz. In certain
embodiments, the GPS system provides the time and date. In certain
embodiments, when present, the IMU is a
9-axis IMU which can provide 16-bit samples at a rate from about 10 to about
100 Hz when triggered. In another
embodiment, the IMU provides data only when it is triggered. In still another
embodiment, the IMU provides
data at a rate of less than about 10 Hz when in "sleep" mode. In certain
embodiments, when present, the humidity
sensor provides 8-bit data at about 0.1 Hz. In certain embodiments, whcn
present, the barometric pressure
sensors provides 24 bit samples at about 50 Hz when active and at less than
about 50 Hz when in "coast" mode.
In certain embodiments, when present, the temperature sensor may be built into
the barometric pressure sensor,
and can provide continuous 8-bit samples resulting in about 0.5 deg.
Fahrenheit resolution at about 0.1 Hz. In
certain embodiments, when present, the MEMS microphone is an omnidirectional
MEMS microphone. The
MEMS microphone can provide a 48 kHz sample rate with no compression, or be
operating in the background
at a lower sampling rate when collecting infrasound-to-ultrasound
vibroacoustic data. The MEMS microphone
may provide an acoustic response up to 80kHz. In certain embodiments, when
present, the ambient light sensor
provides log-scale 8-bit data at a continuous rate of about 0.1 Hz. In another
embodiment, the ambient light
sensor has a spectral response corresponding to normal human vision. In still
another embodiment, the ambient
light sensor is a single band sensor. In certain embodiments, when present,
the ionizing radiation sensor provides
log-scale 8-bit data at a continuous rate of about 0.1 Hz. In certain
embodiments, the ionizing radiation sensor
is a Csl:TI seintillator type personal dosimeter. In other embodiments, the
ionizing radiation sensor is a quartz
fiber type personal dosimeter.
[417] The processor may rely on either PAT- or PTT-based estimates of blood
pressure. In both cases, the
hardware selection of proximal/distal pulse waveform sensors and additional
integration of
contextual/environmental sensors improve the long-term accuracy of blood
pressure estimates. In another
aspect, the processor may contextual ize the PAT or PTT data by additionally
estimating parameters/coyariates
that (1) affect PAT or PTT and (2) may change independently from blood
pressure. In one embodiment, the
blood pressure monitoring system of the disclosure comprises continuous and
real-time model updates to
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remove the variability that results in previous approaches that require more
frequent re-calibrations with a blood
pressure cuff
[418[ Any of the vibroacoustic sensor module 2954' or any of the above-
described sensors may be
communicatively connected to a processor of a computing system. For example,
the vibroacoustic sensor
module 2954' may be communicatively connected to the processor such that the
processor is configured to
receive acoustic data from the vibroacoustic sensor module 2954'. The
computing system may have a memory
storing executable instructions that, when executed by the processor, cause
the processor to process received
data. The processor may be at least partially housed in the housing 2952' or
remote therefrom. The processor is
configured to receive the acoustic data an optionally other data from the
sensors and to execute a method for
determining the blood pressure of the subject from the acoustic data. The
processor may execute a trained
algorithm in the method. The processor may be configured to amplify the
acoustic signal detected by the
vibroacoustic. Alternatively, or in addition to, there may also be provided an
amplifier component for
amplifying the acoustic signal.
[419] In certain embodiments, in which the sensing device 2950 or 2950' is
worn for a prolonged time by the
subject. the processor is configured to receive data from one or more of the
sensors for predetermined time
intervals, such as for 1, 5, 10, 15, 30 or 45 minutes in every hour. This can
help the sensing device 2950, 2950'
to conserve power. Alternatively, the one or more sensors may be configured to
obtain data in the predetermined
time intervals. In other embodiments, the processor or one or more of the
sensors may be configured to obtain
the data responsive to a trigger.
[420] In another embodiment, the blood pressure monitoring system of the
disclosure can perform real-time
calibrations by using accelerometers to estimate limb positioning and
leveraging hydrostatic blood pressure
changes arising differences in limb positions.
[421] In another embodiment, the blood pressure monitoring system of the
disclosure can provide models
relating collected data to blood pressure without requiring an external blood
pressure cuff by, for example,
utilizing arm movement to a vertical overhead position that changes the distal
sensor height by h and confirming
that a decrease in blood pressure pgh, where p is the blood density and g is
the acceleration due to gravity has
occurred.
[422] In yet other embodiments, there may be provided two or more sensing
devices positioned at different
locations and permitting triangulation of the data received therefrom.
[423] There may also be provided a haptic device associated with a user of the
system, the haptic device
communicatively coupled to the processor, the processor is configured to cause
the haptic device to vibrate with
a vibration pattern corresponding to the determined blood pressure of the
subject using either of the sensing
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devices 2950, 2950'. The haptic device may be configured to reproduce a haptic
signal in three dimensions. The
haptic device may be in the forin of at least one patch.
[424] In certain embodiments, the haptic device may comprise a multi-axis
transducer (multi-axis (>3 -axis)
haptic feedback system). In one embodiment, the haptic device may comprise a
three axis capable playback
transducer and charging station for the purpose of multi-axis phenomenological
replay of physiologic
movements facilitated by recordings made using a full-spectrum infrasound-to-
ultrasound electronic
stethoscope. This data would be reproduced in both the audible acoustic and
inaudible infrasonic-to-ultrasonic
realm to offer bio-feedback access and insight into whole body mechano-
acoustic and vibration bio-signatures
collected by wide-bandwidth electronic stethoscopes or equivalent
technologies. In another embodiment, the
haptic device is a novel multi-dimensional haptic perceptron system
incorporating at least three degrees of
freedom (>3-D0F) for clinical and virtual environments that mates with the
data collection devices and
processing systems of the blood pressure sensing device. The multi-axis (>3-
axis) haptic device can operate as
a standalone transducer for clinicians to review and analyze cardiopulmonary
audible sounds in addition to
inaudible movements in 3-axis freedom of movement.
[425] In certain embodiments of the blood pressure sensing devices, one or
more of the following effects may
be achieved: real time monitoring of blood pressure; real time calibration of
blood pressure data; "hands-free"
operation for obtaining blood pressure (for example, in certain embodiments,
the patient is not required to use
or manipulate the limb carrying the device during use); provides for a
measurement model that is invariant with
respect to heart rate (due in part to the bioelectric sensor data that can
provide heart cycle information).
[426] In certain embodiments, the blood pressure sensing devices can be used
for continuous ambulatory
blood pressure monitoring in the monitoring of chronic disease, management of
patients in critical conditions,
as well as those under anesthesia; can be used for one or more of: cuffless
ambulatory blood pressure monitoring
in the monitoring of chronic disease, management of patients in critical
conditions, as well as those under
anesthesia; can be used for abdomen examination for evidence of an aortic
aneurysm; accurate simultaneous
blood pressure measurement in both arms and/or both legs; patients with
atherosclerotic subclavian or axillary
arterial disease; auscultation for bruits at the neck and over the clavicles,
abdomen, and femoral pulses;
providing accurate information in patients with noncompressible vessels to
establish the initial diagnosis, assess
the location and severity of lower extremity PAD as well as to follow the
progression after a revascularization
procedure; screening for clinical suspicion for peripheral artery disease
(PAD), including diagnostic referral to
the vascular laboratory; identifying patients at risk for critical leg
ischemia as well as cardiovascular morbidity
and mortality subsequent to revascularization and can also be used to assess
disease progression after vascular
surgery; noninvasive diagnostic assessment of the location and severity of the
arterial disease, following disease
progression, and measuring response to medical treatment or revascularization;
identifying patients at risk for
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subsequent critical leg ischemia as well as cardiovascular morbidity and
mortality and can also be used to assess
disease progression after vascular surgery; providing accurate information
even in patients with
noncompressible vessels, to establish the initial diagnosis, assess the
location and severity of lower extremity
PAD as well as to follow disease progression after a revascularization
procedure; screening for clinical suspicion
for peripheral artery disease (PAD), including diagnostic referral to the
vascular laboratory; noninvasive and
accurate ankle-brachial index (ABI) initial screening test in a patient with
suspected PAD; screen targeted
patients at risk for lower extremity PAD, including individuals with diabetes
and one or more other risk factors
(e.g., individual 50 years or younger with history of diabetes and one other
risk factor; those 50 to 69 years with
history of smoking or diabetes; those 70 years and older; and those with
abnormal pulse examination or known
atherosclerotic disease in other vascular beds patients at risk for vascular
disease; ABI measurement in
conjunction with segmental pressure measurements with plethysm graphic cuffs
placed sequentially along the
limb at various locations to accurately determine the location of individual
artery stenosis; obtaining accurate
ABI and segmental pressure analysis in individuals with noncompressible
arteries due to medial calcification,
such as patients with long-standing diabetes, elderly patients and those with
end-stage renal disease on dialysis;
pulse volume recording (PVR), documentation and sequential graphing along
limbs to accurately correlate the
magnitude of the pulse upstroke and pulse volume (amplitude) with blood flow
and accurate mapping of
sequential decrease to determine the presence of a flow-limiting lesion in
proximal arterial segments, i.e., low
resolution imaging; obtaining segmental velocity waveforms and systolic blood
pressure measurements along
the upper or lower extremities, i.e., more accurate peak-to-peak pulsatility
index, defined as the peak systolic
velocity minus the minimum or most reversed diastolic velocity, divided by the
mean blood flow velocity;
arterial segment localizing information to indicate an occlusion proximal to
that segment; accurate pulsatility
index estimation to reduce aortoiliac disease false positive false alarms as a
result of superficial femoral artery
disease; Treadmill Exercise Testing with and without ABI; Continuous blood
pressure monitoring during
exercise testing in establishing the diagnosis of PAD when there is a high
index of suspicion and the resting
ABI measurements are normal; noninvasive imaging technique to provide low
resolution vascular imaging and
flow velocity information to diagnose the location and severity of lower
extremity PAD with high sensitivity
and specificity, even for the iliac arteries in the presence of bowel gas or
tortuosity as well as if there is dense
calcification or multiple stenoses; Quantitative criteria to diagnose stenoses
based on peak systolic velocity and
peak systolic velocity ratios within or beyond the stenosis compared with the
adjacent proximal arterial segment,
the presence or absence of turbulence and preservation of pulsatility;
noninvasive imaging technique to enable
excellent noninvasive definition of the vascular anatomy to diagnose the
location and degree of stenosis in PAD;
ABI measurement in conjunction with segmental pressure measurements with
plethy smographic cuffs placed
sequentially along the limb at various locations to accurately determine the
location of individual artery stenosis;
fast imaging of the entire lower extremity and abdomen in one breath hold;
patients with pacemakers and
defibrillators, with metallic clips, stents or prostheses where the foreign
bodies interfere with computed
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tomographic angiography and magnetic resonance angiography; evaluation of
eccentric stenoses and
visualization of all collateral vessels as well as surrounding tissues.
[427] In some embodiments, the sensing device for blood pressure monitoring
can operate through clothing.
For example, the system can operate through a distance of about 1 mm, 2 mm, 1
cm, 5 cm, 10 cm, 15 cm, 20
cm, 25 cm, 30 cm, 40 cm, 50 cm, 60 cm, 70 cm, 80 cm, 90 cm, or 100cm.
[428] In one example, impedance plethysmography (IPG), (voice-coil, barometric
pressure. MEMS
microphone, PDVF printed circuit) vibroacoustic sensors, and EPS were combined
to demonstrate the feasibility
of leveraging light and sound detection of pulse transit time (PTT) and
accurate estimation of blood pressure
(BP). The IPG sensor was placed on the wrist while the photoplethysmography
sensor was attached to the index
finger to measure the PTT. With a cuff-based BP monitoring system placed on
the upper arm as a reference.
Ten young, healthy human subjects leveraging handgrip exercises to manipulate
BP/PTT were compared to
several conventional PTT models to assess the efficacy of PTT/BP detections.
Measurement of arterial
impedance via IPG, vibroacoustics. and EPS methods were determined to comprise
a beat-to-beat indicator to
estimate real time BP more accurately than conventional PTT methods. One or
more of the measured parameters
were used to train a Machine Learning Algorithm. During the training, improved
sensitivity ranges were
observed. In certain embodiments, in use, sensitivity ranges of: more than
90%, more than 92.5%, more than
95%, more than 97.5% were obtained.
Specialized equipment
[429] The sensing device and/or other parts of the system 100 may be
incorporated into other suitable medical
diagnostic equipment, such as a stethoscope. For example, a stethoscope
including a sensing device may be
used by a clinician to examine a subject and collect data including audible
and inaudible vibroacoustic signals
from the heart, lungs, gut, etc.
Stethoscope
[430] For example, as shown in FIG. 30, a stethoscope device 3000 may include
a sensing device including a
handheld housing 3010 (e.g., chest-piece) having a vibroacoustic sensor module
3020. The vibroacoustic sensor
module 3020 may be similar to any of the variations of vibroacoustic sensor
modules described above. For
example, as described above, the vibroacoustic sensor module 3020 may include
at least one deflecting structure
(e.g., one or more flexure arms, a membrane, spider etc.) and one or more
suitable sensors configured to
interface with the deflecting structure to detect and measure vibroacoustic
signals. In some variations, the
vibroacoustic sensor module comprises a voice coil. In some variations, tubing
of the stethoscope leading to
earpieces 3060 may be detachably coupled to the vibroacoustic sensor module
3020 (e.g., with mating
connectors, magnets, etc.). In some variations, the vibroacoustic sensor
module 3020 (or a suitable component
thereof, such as the impedance diaphragm as described above) may be
manufactured separately and be
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configured to replace one or more components (e.g., dome or diaphragm) of an
existing stethoscope (e.g.,
conventional acoustic stethoscope). In this respect, some components of the
sensing device, such as the sensing
device 400, may be adapted to be retrofit to a conventional stethoscope.
[431] Vibroacoustic signals from the vibroacoustic sensor module 3020 may be
communicated to an
electronics system which may be located in at least one junction box 3040
along tubing of the stethoscope device
3000 or in any suitable location for processing the signals. At least
vibroacoustic signals in the audible frequency
range may traverse through the tubing and heard by a user via earpieces 3060.
Additionally or alternatively, the
junction box 3040 may include one or more connectors enabling at least one
peripheral device (e.g., headphones)
to be connected to the stethoscope in a wired manner, though in some
variations acoustic data may be
communicated wirelessly to a peripheral device via a communication module such
as that described above (e.g.,
over WiFi, cellular network, Bluetooth, etc.). The junction box may also
include one or more connection ports
such that speakers, headphones and/or air tubes may be connected to the
vibroacoustic sensing device.
Furthermore, in variations in which the electronics system includes a
communication module with one or more
antennas for wireless transmission, the antenna(s) may be included within the
tubing to allow for optimization
toward range and/or data rates. In some variations, the antenna(s) may be
separated a suitable distance from
other electronics to as to reduce interference and lead to improved
transmission quality.
[432] In certain variations, the sensing device may function as a stethoscope
by coupling it with a smartphone
or other device.
Panels
[433] Referring to FIGS. 31A-31C, in certain variations, there is provided a
sensing device 3100 having a
panel-like form (hereinafter referred to as "panel 3100" or "panel unit
3100"). The panel 3100 may be mountable
to a support surface such as a wall, a ceiling, a doorway, etc., or be free
standing. The panel 3100 may be
installed in rooms, corridors, vehicles, entryways, checkpoints, doorways,
vehicles, and other areas to detect
sensor signals from subjects for diagnosing certain bodily conditions of the
subjects. The sensing device 3100
can operate 1 cm, 5 cm, 10 cm, 25 cm, 50 cm, 100 cm, 150 cm, 200 cm, 250cm, or
300 cm away from the
subject or a clothing of the subject. The panel 3100 may be camouflaged as not
to be apparent to the subject. A
thickness of the panel unit 3100 may be less than 1 mm, 2 min, 3 mm, 4 mm, 5
mm, 7.5 mm, 10 mm, 15 mm,
20 mm, 25 mm, 30 mm, 40 mm, 50 mm, or 75 mm thick.
[434] The panel 3100 comprises a frame 3110 defining an aperture 3120, and a
membrane 3130 extending at
least partially across the aperture 3120 and supported by the frame 3110. A
vibroacoustic sensor assembly 3140
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is coupled to the frame 3110 such as by support members 3150 and configured to
convert vibrations of the
diaphragm 3130, such as to an analog or digital signal.
Vibroacoustic sensor assembly of the panel
[435] In certain variations, the vibroacoustic sensor assembly 3140 may be
based on a voice coil type
transducer, such as the vibroacoustic transducer 1600 described in relation to
FIG. 16 and FIG. 17 or FIG. 4J In
this respect, the vibroacoustic sensor assembly 3140 may include a conductive
coil with a stationary magnet
setup connected to the frame 3110. The vibroacoustic transducer may be
attached to the frame 3110 by the
support members 3150. The vibroacoustic transducer may be attached centrally,
or asymmetrically in
relationship to the frame 3110, selection of which will be described below.
[436] In certain other variations, the vibroacoustic sensor assembly 3140 may
be any type of sensor-read out
element, or combinations of sensor-read out elements, such as but not limited
to:
= Voice coil with extremely compliant or entirely absent spider for
sensitive membrane bending pickup.
A compliant spider can further be shaped as a flexure to increase compliance
and reduce out of plane
movements. In case of an entirely absent spider the previously added spring
constant of the spider is removed
from the moving system. Hence, either the voice coil or magnet is integrated
in the bending membrane;
whichever is of lower inertia due to mass and hence less restrictive in
membrane movement.
= Electric Potential sensors (EPS) can pick up subtle movement of nearby
objects due to the disturbance
of static electric fields they cause. An EPS close to the membrane is hence
able to sense the motion of the
vibrating membrane. In contrast to the voice coil, such a system might not add
any mass or additional spring
constant to the system and hence keeps the original compliance of the
membrane.
= Capacitive pickup similar to capacitive microphones is a direct
alternative approach to the EPS pickup,
however with the need of a layer on top of the membrane with the ability to
create a charge. A fixed metal plate
is provided behind the membrane in close proximity to complete the two
components of a capacitor with the air
gap in between acting as the dielectric. The metal plate could have any size
from very small to the entire size of
the membrane. Further, the layer on top of the membrane can either be a
conductive material that is polarized
through an applied voltage (commonly known as Phantom Voltage) or could be an
electret material that offers
a quasi-permanent electric charge or dipole polarisation. In either case, the
added layer adds mass to the
vibrating membrane and hence inertia.
= Magnetic field disturbance sensors are voice coil sensors, but without
integration of any voice coil
component within the membrane. The magnetic field of the sensor is routed
through a ferroelectric layer on the
membrane. Membrane vibrations modulate the magnetic field that hence induces a
current in the voice coil
winding resulting in a signal.
= Light source (such as laser) and photodetcctor positioned behind the
membrane. The light source is
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positioned to direct an energy beam to the membrane and a photodetector is
positioned to detect the energy
beam reflected from the membrane and to measure a change in angle of the
reflected energy beam (reflected of
membrane movement). The reflection angle may depend on local bending of
membrane, which in turn vibrates
with incoming pressure waves. The photodetector may comprise a photodiode
array from which the reflection
angle is determined by the specific photodiodc in the array, which captures
the majority of the reflected signal
intensity.
= Strain sensor(s) can be positioned directly on the membrane surface at
strategic locations to detect
movement of the membrane, e.g. layers of PVDF.
= Acoustic Echo Dopplers target a high frequency acoustic signal to the
backside of the membrane, which
is reflected into a detector. Membrane vibrations are frequency modulated into
the Doppler carrier frequency,
and demodulation results in a membrane vibration pickup. Acoustic Doppler
could either operate in Pulsed
Wave or Continuous Wave mode.
= Light Time of Flight (TOF) sensing using a light source emitting pulses
and a sensor measuring the
time to arrive of the reflected signal.
= Laser Doppler interferometers or self-mixing interferometers utilize the
doppler effect and interference.
In contrast to the Acoustic Echo Doppler this light-based approach results in
higher SNR and amplitude
resolution.
Instead of using laser light, a setup could contain a Time-of-Flight radar,
radar doppler or any other commonly
known radar sensing technology such as Ultra-Wideband-Radar (UWB)
[437] In addition to laser and radar, the vibration pickup could be based on
any frequency of electromagnetic
waves and combined with the same fundamental methodologies such as TOF and
Doppler effect.
Positioning of the vibroacoustic sensor assembly relative to the membrane
[438] The vibroacoustic sensor assembly 3140 or other sensor read-out element
can be positioned at any
appropriate position with respect to edges of the membrane 3130. In certain
variants, as illustrated, the
vibroacoustic transducer is positioned centrally with respect to the edges of
the membrane 3130. However, in
other variants, the vibroacoustic transducer does not necessarily need to be
in the center of the membrane 3130.
Particularly if considering the membrane 3130 could be excited at higher
eigemnodes there is a benefit of
placing the vibroacoustic transducer off-center in any appropriate position.
For example, if the voice coil
transducer is placed in the center and a higher eigenmode has a node at the
center, there will be no displacement
at the center and no signal measured, where in reality the membrane is indeed
vibrating.
[439] For example, consider the membrane 3130 having a plurality of eigenmodes
based on its geometry
which will create nodes (points at which there is no displacement) on the
membrane 3130. For example, if the
membrane 3130 has four eigenmodes with a 2x2 configuration, there will be a
node at the center of the
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membrane 3130. This is also the case when the membrane 3130 has two eigenmodes
which also create a node
(no displacement) at a central portion of the membrane 3130. In these cases,
and other eigenmode situations not
described, a centrally positioned vibroacoustic transducer 3140 is not
optimally positioned for detecting
vibrations in the membrane 3130. Accordingly, a positioning of the transducer
relative to the membrane 3130
can bc selected by considering the cigenmodes of the membrane 3130. In
variants of the panel 3100 in which
the vibroacoustic sensor assembly 3140 includes an EPIC electric potential
sensor and/or a capacitive sensor,
the electrodes of such sensors can be sized to cover the size of the membrane,
which can minimize the localized
effects of eigenmodes such as no bending/displacement of the membrane at the
node. In certain other variants,
the vibroacoustic sensor assembly 3140 may be configured to not sense beyond
the first membrane resonance
caused by the first eigenmode, which may also minimize or make redundant an
effect of eigenmodes.
Frame of the panel
[440] The frame 3110 may be of any suitable size or shape, the dimensions and
configuration of which are
selected based on the desired use and the desired frequency range of
detection. The frame 3110 may be
constructed from any suitable material such as plastic, wood, metal,
composite, glass, ceramic, or any other
suitable material that can withstand the tension of the attached membrane 3130
and/or support the attached
membrane 3130. Although illustrated as rectangular, the frame 3110 can be
circular, oval, trapezoidal, regular
polygonal, or non-regular polygonal. In certain variants, the frame 3110 is
subdivided to define more than one
aperture for coupling with separate membranes 3130.
Membrane of the panel
[441] The membrane 3130 is attached to a first side 3152 of the panel, a back
cover 3153 may be provided
on a second side 3155 of the panel 3100, thereby defining a cavity 3156
between the membrane 3130 and the
cover 3153. The membrane 3130 is configured to vibrate at frequencies relating
to a desired detection frequency
range, such as the vibroacoustic range of the subject. One or more of the
parameters of the material, weight,
size and tension of the membrane 3130, as well as the shape or size of the
cavity 3156 behind the membrane
3130, may be tailored to achieve the desired frequency range.
[442] Larger membranes 3130 with low stiffnesses tend to pick up low
frequencies well, whereas stiffer
membranes pick up higher frequencies but attenuate lower ones. The weight of
the membrane 3130 itself or
anything connected to the membrane in general causes inertia during
vibrations, which oppose and attenuate
incoming vibroacoustic signals (and might cause increased reflection of the
acoustic wave). A voice coil
transducer connected to the membrane 3130 also means that the spider component
represents an additional
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spring in the system; which adds to the membrane stiffness and decreases the
compliance of the sensor pickup.
The attached voice coil portion may also add inertia to the membrane.
[443] For example, more compliant membranes give good signal-to-noise ratio
favoring low frequencies (e.g.
0-100 Hz only). Similarly, larger membranes favor lower frequencies as well.
Smaller membranes 3130 can
detect high bandwidth or higher frequencies. Thicker membranes 3130 can detect
high bandwidth, higher
frequencies due to generally higher membrane bending stiffness. Thinner
membranes 3130 can detect lower
frequencies as they tend to be more compliant if all other parameters equal.
Higher tension membranes can
detect high bandwidth, less deflection which may lead to lower sensor
amplitudes and hence signal-to-noise
ratio. Lower tension membranes 3130 can detect lower bandwidth as more
compliant, high deflection caused
by same incoming acoustic wave (good signal-to-noise ratio).
[444] Generally, a tradeoff is required between different values of the
bending stiffness and hence ability to
pick up low amplitude waves. Low bending stiffness results in a compliant
membrane able to pick up waves of
very low amplitudes (e.g. when < 20Hz). However, the resonance frequency and
subsequent roll-off of a very
compliant membrane is very low and hence obstructing the ability to pick up
higher frequencies, particularly
above some threshold frequencies, e.g. >100Hz. High bending stiffness in
contrast results in higher resonance
modes of the membrane giving the ability to pick up higher frequencies at the
expense of small amplitude lower
frequencies.
[445] in certain variants, as an alternative to finding a trade-off for an
overall frequency range, the panel 3100
can be divided into smaller sub-panels 3156 (FIG. 31C), each sub-panel 3156
having the same or differing
membrane 3130 stiffnesses and a respective transducer, for a particular
optimum frequency range. In addition,
the sub-panels 3156 can be of different sizes, e.g. the membrane 3130 for
<20Hz pickup may be larger in surface
area than the membrane 3130 for detecting >100Hz. It will be appreciated that
panels 3100 without sub-panels
as well as panels 3100 with sub-panels 3156 are within the scope of the
present technology, according to certain
variations.
[446] In this manner, by using sub-panels 3156, a broader overall frequency
range may be detected. In certain
variations, the sub-panels may be separate from one another. In other
variations, the configuration of the sub-
panels illustrated in FIG. 31C may differ from the configuration as
illustrated, in a manner known by persons
skilled in the art. In certain variations, the panel 3100 may be considered to
comprise multiple transducers
operating on the same or different modes of operation. The multiple
transducers may be arranged as an array.
[447] In certain variations, the membrane 3130 is a compliant material such as
a thermoplastic or thermoset
elastomer. In other variations, the membrane 3130 may comprise metal,
inorganic material such as silica,
alumina or mica, textile, fiberglass, Kevlar', cellulose, carbon fiber or
combinations and composites thereof.
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In certain variations, the membrane 3130 is provided with a protective layer
which may comprise an acoustically
transparent layer, such as foam, positioned on an outer facing side of the
membrane 3130 at a distance of about
1 mm to about 100 mm.
[448] The membrane 3130 may be attached to the frame 3110 in any manner, such
as by adhesive. A profile
of the membrane 3130 when attached to the frame 3110 may be planar, convex or
concave. If the membrane
3130 is under tension, it may be attached to the frame 3110 in a manner to
apply a homogenous tension or
different tensions along different orthogonal axes. The membrane 3130 may be a
stretched sheet. The membrane
3130 may, in certain variations, be self-supporting or under compression
instead of under tension. A damping
material may be provided to dampen movement of the membrane.
[449] With respect to the cavity 3156, certain variants of the panel 3100
provide differing extents of sealing
of the cavity 3156 by the back cover 3154. For example, in certain variants,
the back cover 3154 may be omitted.
In this case, pressure on either side of the membrane 3130 can equalize
quickly. However, a membrane 3130
can generally only bend/vibrate if there is a difference in pressure between
the two sides. Since particularly at
low frequencies the air has plenty of time to continuously equalize the
pressure on the sides of the membrane
3130 upon the incoming pressure wave it is impossible to measure such low
signals. It is then also obvious that
static pressure cannot be measured with an open back setup.
[450_1 In certain other variants, in which the back cover 3154 is included on
the panel 3110, the back cover
3154 may function to seal the cavity 3156 to different extents. At one
extreme, the back cover 3154 may
comprise a solid piece which seals the cavity 3156. This can be considered
like a pressure sensor which
measures static pressure against the inside reference pressure. It measures
down to DC (static pressure), but the
static pressure opposes membrane 3130 movement to AC signals particularly the
higher the input vibration
amplitude. In addition, a completely sealed cavity causes the membrane 3130 to
bend outwards or inwards when
outside pressure is not equal to inside pressure, e.g. changing altitude.
Result may be low Signal-to-Noise Ratio
(SNR) at dynamic (AC) measurements at higher frequencies and larger
amplitudes, depending on the volume
of the cavity.
[451] In certain other variants, the back cover 3154 includes openings 3162
for permitting air flow
therethrough to the cavity 3156. The size, count and location of these
openings 3162 can be optimized according
to the desired frequency detection range and acceptable signal-to-noise
ratios, and can be also seen as a cavity
impedance optimization with the cavity volume itself. For low frequency
detection (less than 20 Hz), the low
frequency pressure waves give plenty of time for creating an equilibrium on
either side of the membrane 3130.
So the configuration of the openings 3162 need to take into account a tradeoff
between letting air in/out
(depending on positive or negative pressure waves) from inside the cavity 3156
to reduce pressure, and delaying
the equilibrium process long enough to catch very low frequency pressure
waves. Hence, the pressure on either
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side of the membrane 3130 will equalize at some time constant and vibrations
at frequencies corresponding to
a time period below that equilibrium time constant can be measured. In certain
variants, dimensions of the panel
are about 7 inches (width), about 9.75 inches (height), and about 0.5 inches
(depth). Experimental data obtained
with this variant sensing device is presented in Example 9.
[452] The openings 3162 can have any shape (round, square, rectangular) and
size and count. The openings
can be of structure instead of simple opening, such as tubes of various
diameter and lengths like commonly
present in acoustic subwoofers. Structures as opening can be anything that
allows flow of air between the cavity
and outside environment, son not only limited to tubes. In an example
embodiment the back cover 3154 could
have a single small tube to equalize for inside DC pressure in a low frequency
optimized panel with a large
cavity.
[453] In certain other variants, the cavity 3156 inside the panel 3100 can be
divided into two lateral sections.
The divider between the two cavities is perforated based on design needs to
allow for air exchange between the
two cavities. In one variation the cavity close to the membrane 3130 is a
smaller one and the cavity towards the
back is the bigger one, serving as an air 'reservoir'. The overall unit is
sealed off from the environment entirely,
or sealed with a small hole or tube to allow pressure equalization with the
environment in case of slow and
nearly DC type of pressure changes due to e.g. altitude change. The dual
cavity setup is particularly important
if a capacitive or Electric Potential sensing method is used. For example, in
the capacitive sensing approach the
conductive plate behind the membrane 3130 needed to form the capacitor may be
of similar size as the
membrane to maximize sensitivity. As this plate should be close to the
membrane to maximize capacitance
between membrane and plate the cavity formed is small, causing air pressure to
rise under a vibrating membrane
when a plate without any perforation is used. Hence, perforation in the plate
connects the small cavity to the
bigger back cavity for reduced pressure.
[454] In summary, the vibroacoustic detection range of the sensing device 3100
when embodied as the panel
3100 can be considered as a function of various parameters relating to: the
membrane 3130 (e.g. stiffness,
material, surface area, etc.,), sensor clement reading the vibration (e.g.
voice coil, capacitive, optical, acoustic
(echo doppler), radar, etc.), pressure equalization based, for example, on
size of cavity 3156 and the openings
3162 of the back cover 3154.
Front cover of the panel
[455] Other variants of the sensing device 3100 having a panel-like form are
illustrated in FTG. 31D and FIG.
31E. A front cover 3159 is provided at the first side 3152 of the panel 3100.
The front cover 3159 may be more
rigid than the membrane 3130. The front cover 3159 may provide environmental
and mechanical protection of
the membrane 3130. The front cover 3159 may have any type of surface finish or
configuration. For example,
in certain variants, the front cover 3159 is highly reflective like a mirror.
In certain variants, the front cover
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3159 may include an output display unit 3170. The output display unit 3170 may
include any manner of
markings and indicators such as one or more of: the likelihood of the subject
having a given bodily condition
(e.g. displayed as a red or green light or other indicator), at least a
portion of the data obtained by the sensors
(e.g. physiological data of the subject such as ECG readings, environmental
data). In certain variants, the front
cover 3159 may be at least partially a mirror and at least partially an output
display such as the output display
unit 3170. The front cover 3159 may be configured to extend substantially
vertically when supported on a
support surface such as the wall or the floor. The front cover 3159 may be
perforated to permit sound pressure
come through without much attenuation, with the perforation down to micrometer
size.
Additional sensor modules
[456] The panel unit 3100 may incorporate one or more other sensor assemblies
based on non-contact
detection of signals associated with the subject or the environment, such as,
without limitation, one or more of
the echo doppler sensor module, the kinetic sensor module, temperature sensor
module, VOC sensor module,
machine vision sensor module, contextual sensor module, etc. The sensor
modules of the panel unit 3100 may
be configured to monitor or detect, for example, Covid-19 infection in the
subject by detecting signals related
to respiratory function; body temperature; gastrointestinal tract function;
bladder motility; water/fluid retention
(edema) in legs; peripheral vascular disease, etc.
[457] Thus, in certain aspects, there is provided a device for detecting
vibroacoustic signals relating to a
subject, the device comprising: a frame defining an aperture; a sheet
extending across the aperture and supported
by the frame, the sheet configured to vibrate at frequencies relating to a
biovibroacoustic range of the subject;
and a transducer for converting the vibration of the sheet to a data stream
including vibroacoustic data. In certain
embodiments, the frame is more rigid than the sheet. In certain embodiments,
the sheet is one or more of planar,
convex or concave when supported by the frame. In certain embodiments, the
transducer comprises one or more
of a voice coil, a piezoelectric element, a capacitive element, or a laser
microphone. In certain embodiments,
the data stream comprises one or both of an analog signal and a digital
signal. In certain embodiments, the frame
defines a perimeter of the sheet. In certain embodiments, the frame is
configured to support the sheet in one or
more of a stretched state, a neutral state and a compressed state across the
aperture. In certain embodiments,
the sheet is supported by the frame such that a first tension of the sheet
along a first axis is different than a
second tension along a second axis. In certain embodiments, there is further
provided a damping element to
damp a movement of the sheet. In certain embodiments, the sheet is connected
to the transducer, or is integral
with the transducer. In certain embodiments, the transducer comprises multiple
transducers operating on the
same or different modes of operation. In certain embodiments, there is further
provided one or more optical
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sensors for capturing optical data relating to the subject, the data stream
including the optical data from the one
or more optical sensors and the vibroacoustic data from the transducer.
Base unit
[458] Turning now to FIGS. 32A and B, in addition to a panel-like sensing
device 3200 (also referred to as
"panel unit 3200") which can correspond to the panel unit 3100, there is
provided a base unit 3210 incorporating
one or more sensor modules. The one or more sensor modules may be any one or
more of the sensor modules
as described herein such as the vibroacoustic sensor module, the bioelectric
sensor module, the capacitive sensor
module, etc. The panel-like sensing device 3200 and the base unit 3210 may be
an integrated single unit (FIG.
32A), or may comprise separate units spaced from one another (FIG. 32B). The
panel unit 3200 and the base
unit 3210 may be positioned orthogonally with respect to each other.
Advantageously, this orientation may
enable the sensor modules associated with the panel unit 3200 and the base
unit 3210 to detect physiological
parameters along different planes of the subject's body, providing an ability
to obtain complementary data sets
for the bodily condition determination.
[459] The base unit 3210 may be adapted to support a body part of the subject,
such as a foot, a leg, an arm,
a back, a chest, a head, etc. It will be appreciated that in these cases, the
system 100 provides both a contactless
signal detection (from the panel unit 3210) and a contact-based signal
detection (from the base unit 3210),
whether direct skin contact or indirect contact through clothing and/or
footwear.
[460] The base unit 3210 may comprise a platform arranged to be supported on a
support surface such as the
ground in use and having an upper surface 3220 for the subject to stand on.
Markings may be provided on the
upper surface 3220 to indicate where the subject is to place its feet. As seen
in the figures, the base unit 3210
may be relatively flat or have a stepped structure. The one or more sensor
assemblies contained in the base unit
3210 may be arranged to obtain data from the subject while the subject is
wearing footwear such as shoes or
socks_ In certain variations, the base unit includes a bio-electric sensor
assembly_ Other sensor assemblies may
include those that detect vascularization, heat, weight, etc. The base unit
3210 may also be arranged to emit one
or more signals to the subject. For example, the base unit 3210 may be
arranged to vibrate in order to detect a
physiological response of the subject to the vibration. The base unit 3210 may
include a BCG sensor module_
[461] In certain variations, the sensing device 3200 comprises the panel unit
3100 embodied with the
configuration of FIG. 32A or FIG. 32B and optionally including the base unit
3210. The panel unit 3100 includes
a vibroacoustic sensor module, an echo doppler sensor (continuous wave),
optionally a heat sensor module (e.g.
including a thermopile with an accuracy of mKelvin to 1Kelvin, and optionally
a black body reference to
calibrate the temperature readings based on environmental temperature); a 3-D
machine vision camera;
optionally one or more environmental sensors (e.g. one or more of: ambient
temperature, GPS, barometric
pressure, altitude, ambient noise, light, etc.); optionally a MEMS microphone.
The panel unit and the sensor
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modules are configured such that the panel unit can be positioned
substantially vertically so that the subject can
stand in front of it. The inclusion of an Echo doppler sensor module with the
voice coil sensor module can
improve a signal to noise ratio of the detected vibroacoustic signal.
[462] The base unit 3210 includes a marker on an outer surface indicating
where the subject should stand. In
certain variations, the subject is invited to stand with his/her chest facing
the upright unit 3325. The marker may
be an image of feet. Optionally, the base unit 3310 may also include the
capacitive sensor module (for example
to measure galvanic skin response), and optionally a BCG sensor module.
[463] In certain variants, an adjustment mechanism is provided within the
panel unit to adjust a position of at
least a portion of one or both of the Echo Doppler sensor module and the
vibroacoustic sensor module (e.g. one
or both of the transmitter and the receiver of the Echo Doppler sensor module)
to optimise a height of the sensor
modules for optimal or adequate signal detection. In certain variants, the
adjustment mechanism permits an up-
down position adjustment. In certain variants, the adjustment mechanism may
also permit a side-to-side position
adjustment. The adjustment mechanism may comprise a linear motion system (not
shown). The linear motion
system may comprise an elongate shaft and a movable member mounted to the
elongate shaft. The at least a
portion of one or both of the Echo Doppler sensor module and the vibroacoustic
sensor module may be attached
to the movable member. A controller may be provided for controlling the
movement of the movable member.
A motor may be provided for powering the movement of the movable member.
[464] Additional sensor modules (such a 3D camera) may be included to detect a
height of the subject or a
height of a predetermined body part of the subject, and automatically adjust
the height of one or both of the
Echo Doppler sensor module and the vibroacoustic sensor module. The system 10
may be configured to obtain
data from the 3D camera (machine vision sensor module) to detect a height of
an eye of the subject, and to
estimate a height of the torso of the subject. If one or both of the Echo
Doppler sensor module and the
vibroacoustic sensor module are not aligned with the torso height of the
subject, the system 10 may be
configured to adjust the height of one or both of the Echo Doppler sensor
module and the vibroacoustic sensor
module using the linear motion system. Optionally, the sensing device may be
provided with a heat sensor
module for detecting a temperature of the subject, in communication with the
3D camera for detecting a location
of a tear duct of the subject. A light, such as in the form of a ring, may be
provided to illuminate the subject.
Illuminating the tear duct of the subject can facilitate locating the tear
duct and measuring the temperature
thereof. In certain variants, the heat sensor module may be configured to move
to target the located tear duct.
In other variants, the system 10 may be configured to receive data regarding
the chest height of the subject, or
otherwise a desired height of the Echo Doppler sensor module and/or the
vibroacoustic sensor module, and to
cause the adjustment mechanism to move the Echo Doppler sensor module and/or
the vibroacoustic sensor
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module in response. Adequate signal detection from the subject can be obtained
in about 5 seconds to about 15
seconds, and in some variations, 10 seconds.
C ateways/Kiosk/w alkthrou2h
[465] A yet further variation of the form-factor of the sensing device is
illustrated in FIG. 33A-C, in which
there is provided a sensing device 3300, such as the sensing device 3100 or
3200, incorporated within a gateway
or arch-like configuration. This is also referred to as a "kiosk"
configuration. The gateway configuration may
comprise a housing which has an arch-like configuration, for example including
a base unit 3310 (such as the
base unit 3210), a top unit 3320, and an upright unit 3325. Other support
structures may be provided. The
sensing device 3300 is configured for non-contact measurement of vibroacoustic
data of the subject proximate
the sensing device 3300, as well as other sensor data. The top unit 3320 may
be arranged to be positioned
proximate the subject's head, such as above the head. The top unit 3320 may
include sensors such as those
associated with EEG. The top unit 3320 may have an adjustable height from the
floor or from the base unit 3310
to accommodate subjects with different height. The sensing device 3300 may be
configured to permit the
subject walk through the arch-like housing, and to obtain sensor data
regarding the subject as the subject walks
through the arch-like housing.
[466] In certain variations, the upright unit 3325 is configured to house one
or more sensor modules, such as
one or more of: a vibroacoustic sensor module based, for example, based on the
voice coil transducer 1600 of
FIG. 16; a continuous Echo Doppler sensor module (alternatively can also be
pulsed wave); a heat sensor
module with an accuracy of mKelvin to 1Kelvin (such as a thermopile heat
sensor module), and optionally a
black body reference to calibrate the temperature readings based on
environmental temperature; a MEMS
microphone (optional); environmental sensors (optionally one or more of:
ambient temperature, GPS,
barometric pressure, altitude, ambient noise, light, etc.); 3-D machine vision
depth camera; and optionally a
capacitive sensor module, such as a charge plate, to measure galvanic skin
response. This can be embodied as
the base unit for the subject to stand on.
[467] in the case of variants including the echo doppler sensor module, the
echo doppler sensor module may
comprise any combination of emitter and receiver components, such as one
emitter and one receiver (FIG. 33D),
two emitters and one receiver (FIG. 33E), one emitter and two receivers (FIG.
33F), two emitters and two
receivers (FIG. 33G). In variants with dual emitters, an interference pattern
that concentrates on the plane
spanned by the chest of a person may be achieved and reflection of an
amplified signal from that area.
Surrounding walls, on the other hand, may reflect an unamplified signal to
increase a signal-to-noise ratio. In
variants with dual receivers, a dual receiver may allow to add a directional
preference to the incoming signal
such that the signal from the person's chest is amplified over incoming
signals from the surrounding area, similar
to directional microphone arrays. The echo doppler sensor modules can be
functioning as any one of CWD,
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PWD or just Time-Of-Flight. FIGS. 33D-33G demonstrate the signal
directionality when the echo doppler
sensor module is positioned in a substantially vertical unit, such as the
panel unit component of the gateway.
[468] In certain variants, the signal-to-noise ratio may be adjusted by
optimizing the ultrasound carrier
frequency. There is a range of feasible ultrasound frequencies with frequency
dependent attenuation
characteristics. Overall, the attenuation of ultrasound waves is exponential
over distance, but also exponential
at increasing frequencies. By choosing a higher ultrasound carrier frequency,
the attenuation of reflected signals
of a wall further away than the subject will be exponentially higher than at a
lower frequency. As reflected
signals are undesired and considered noise, the reduced impact improves the
signal-to-noise-ratio of the desired
signal which is reflected off the subject.
[469] For example, when a subject is sitting 50 cm away from the Echo Doppler
sensor module, there is a
total ultrasonic signal path of 1 m (twice the distance). A wall behind the
subject is 2 m away from the Echo
Doppler sensor module with a total signal path of 4m.
[470] Referring to FIG. 33H, a 50 kHz carrier signal attenuates at about 2dB/m
at room temperature. This
results in about 2dB attenuation for the signal reflected of the subject, and
about 8dB attenuation for the signal
reflected off the wall. Hence, when the signals combine again in the
ultrasound receiver the difference between
the two is 6dB, meaning the wall reflected signal is 50% of the amplitude (or
25% of the power) of the subject's
signal, which is a very significant disturbance on the signal.
[471] In contrast, when choosing a 200 kHz carrier the attenuation is about 9
dB/m at room temperature,
resulting in about 9dB attenuation for the signal reflected of the subject,
and about 36dB attenuation for the
signal reflected off the wall. The difference between the two once combined is
27dB, meaning the wall reflected
signal is 4.5% of the amplitude (or 0.2% of the power) of the subject's
signal. Since the subject's signal is
attenuated by 9 dB, which corresponds to about 30% of the original amplitude ¨
or 10% of original power ¨
either the transmitter signal could be further amplified, or amplification
added after receiving the signal.
However, since amplification is a linear operation on the entire signal the
improved signal-to-noise ratio due to
exponential loss remains.
[472] By way of background. the emitted ultrasound signal (Carrier signal) can
be defined as:
Se(t) = Accos (coat),
with A, the carrier magnitude, co, the carrier angular frequency based on a),
= 27f, and se the emitted signal.
The emitter signal is frequency modulated by the chest vibrations and the
received signal including Doppler
shift results in:
s1(t) = Accos (coat +
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where c is the velocity of sound in the medium used, such as about 345 m/s in
air at room temperature, and d(t)
the displacement of the skin on the body location targeted. Demodulation of
the received signal by the
ultrasound carrier se (t) results in the demodulated signal.
sd = A, ')2c d(t).
Solving for the chest displacement hence leads to:
d (t) = ________ s (t) .
Sensor module positioning
14731 In certain variants, the Echo Doppler sensor module and the
vibroacoustic sensor module are both
included in the upright unit of the gateway sensing device 3300 or the sensing
device 3200 or the sensing device
3100. Both sensor modules are positioned at about chest height of an average
subject. In certain variants, an
adjustment mechanism is provided within the upright unit to adjust a position
of one or both of the Echo Doppler
sensor module and the vibroacoustic sensor module. In certain variants, the
adjustment mechanism permits an
up-down position adjustment. In certain variants, the adjustment mechanism may
also permit a side-to-side
position adjustment. The adjustment mechanism may comprise a linear motion
system (not shown). Additional
sensor modules (such a 3D camera) may be included to detect a height of the
subject, and automatically adjust
the height of one or both of the Echo Doppler sensor module and the
vibroacoustic sensor module. The system
may be configured to obtain data from the 3D camera to detect a height of an
eye of the subject, and to
estimate a height of the torso of the subject. If one or both of the Echo
Doppler sensor module and the
vibroacoustic sensor module arc not aligned with the torso height of the
subject, the system 10 may be
configured to adjust the height of one or both of the Echo Doppler sensor
module and the vibroacoustic sensor
module using the linear motion system. In other variants, the system 10 may be
configured to receive data
regarding the chest height of the subject, or otherwise a desired height of
the Echo Doppler sensor module
and/or the vibroacoustic sensor module, and to cause the adjustment mechanism
to move the Echo Doppler
sensor module and/or the vibroacoustic sensor module in response.
[474] In certain variants, the receiver and emitter of the echo doppler sensor
module each have specific signal
characteristics depending on angle. In certain variants, the echo doppler can
function within a range of about
to +90 to -90 degrees. In some other variants, the echo doppler can function
within a range of about 360 degrees.
In other variants, the echo doppler sensor module is configured to function
within a range of about +- 45 degrees
to both focus the signal energy on a smaller volume as well as reduce
reflections all around.
[475] In certain variants, the echo doppler sensor module comprises a receiver
component such as an
ultrasound microphone, such as avisoft-bioacoustics, CM16/CMPA, or a MEMS
microphone such as
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invensense ics-41352/. In certain variants, the echo doppler sensor module
comprises an emitter component,
such as Prowave 400EP250, or Prowave 400st-R160.
Modularity
[476] In variants of the gateway -like form factor of the sensing device, the
units of the gateway (upright, top
and base units) may be configured as modular allowing for components to be
flat-packed or otherwise
compacted for ease of mobility and transportation in between uses (FIGS. 33A -
C). To this end, the one or more
parts of the gateway set up may reflect a tessellation pattern that naturally
allows for the efficient folding and
unfolding of the components.
[477] One such folding pattern, known as the Miura-ori, which is a periodic
way to tile a plane using a simplest
mountain-valley fold in origami, is used as a basis of the tesselated pattern
of the gateway components. A
folded Miura can be packed into a flat, compact shape and unfolded in one
continuous motion, making it ideal
for packing rigid structures like solar panels. It also occurs in nature in a
variety of situations. such as in insect
wings and certain leaves. One or more of the panel unit, base unit and top
unit may implement the tessellation
pattern.
[478] In certain variations, one or more accessories may be provided, such as
beacons or transducing patches,
which can be fitted to the subject, and be in communication with the
processor. A beacon is a device which is
attached to a part of the subject' s body that facilitates the sensing of a
particular state, such as a state of motion
or pose. Over the last decades, state-of-the-art techniques and algorithms
have been developed for cooperative
and uncooperative pose determination by electro-optical (EO) sensors. EO
sensors have a low power
consumption and can be used to estimate all pose parameters. Consequently,
such sensors are the preferred
instruments for this application. In general, EO sensor systems can be
classified as passive systems, systems
consisting of single (monocular) or multiple (stereo) cameras, and active
light detection and ranging (LIDAR)
systems. Among these systems, monocular vision systems have the lowest
hardware complexity and cost and
can be used for remote monitoring. A stereo vision system uses more than one
camera, enabling it to acquire
three-dimensional (3D) information about the target. However, monocular and
stereo vision systems suffer from
the same handicaps as all vision systems¨sensitivity to illumination
conditions and difficulty segmenting
objects from complex backgrounds. in contrast, LIDAR is robust to differences
in illumination and can obtain
both position and intensity data in 3D; however, a LIDAR system consumes more
energy and exhibits poorer
real-time performance due to its enormous computational burden and high
complexity. Thus, after weighing the
pros and cons of the various methods, many research institutions and scholars
have chosen to focus on pose
determination based on monocular vision.
[479] A typical pose determination method usually relies on artificial beacons
that are accurately mounted on
the target. One proximity operation sensor (PXS) consists of a camera and an
array of light-emitting diodes
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(LEDs) on the chaser and a set of passive markers on the target. The LEDs emit
pulsed visible light within a
cone of 300 to illuminate the markers. Simultaneously, the camera captures
images that contain the markers.
Then, the data processing unit calculates the relative pose using a complex
image processing algorithm. The
experimental results represent the advanced performance of the present method,
i.e., the measurement frequency
of the PXS is 2 Hz, with centimeter-scale accuracy in the relative position
and one-tenth-of-a-degree-scale
accuracy in the relative attitude. Similar to the PXS, the advanced video
guidance sensor (AVGS) designed by
the Marshall Space Flight Center and the visual based system (VBS) designed by
the Technical University of
Denmark both require artificial beacons, which are either passive markers
(reflectors) or active markers (LEDs).
[480] Bluetooth Low-Energy (BLE) beacons-based indoor positioning is a
promising method for indoor
positioning, especially in applications of position-based services (PbS). It
has low deployment cost and it is
suitable for a wide range of mobile devices. Existing BLE beacon-based
positioning methods can be categorized
as range-based methods and fingerprinting-based methods. For range-based
methods, the positions of the
beacons should be known before positioning. For fingerprinting-based methods,
a pre-requisite is the reference
fingerprinting map (RFM). Many existing methods focus on how to perform the
positioning assuming the
beacon positions or RFM are known. However, in practical applications,
determining the beacon positions or
RFM in the indoor environment is normally a difficult task. This paper
proposed an efficient and graph
optimization-based way for estimating the beacon positions and the RFM, which
combines the range-based
method and the fingerprinting-based method. The method exists without need for
any dedicated surveying
instruments. A user equipped with a BLE-enabled mobile device walks in the
region collecting inertial readings
and BLE received signal strength indication (RS SI) readings. The inertial
measurements are processed through
the pedestrian dead reckoning (PDR) method to generate the constraints at
adjacent poses. In addition, the BLE
fingerprints are adopted to generate constraints between poses (with similar
fingerprints) and the RSSTs are
adopted to generate distance constraints between the poses and the beacon
positions (according to a pre-defined
path-loss model). The constraints are then adopted to form a cost function
with a least square structure. By
minimizing the cost function, the optimal user poses at different times and
the beacon positions are estimated.
In addition, the RFM can be generated through the pose estimations.
Experiments are carried out, which
validates that the proposed method for estimating the pre-requisites
(including beacon positions and the RFM).
These estimated pre-requisites are of sufficient quality for both range-based
and fingerprinting-based
positioning.
[481] The beacon can be arranged to reflect vibroacoustics directly back to a
receiver/transmitter source with
minimal dispersion. For example, a vibroacoustic retroreflector (sometimes
called a retroflector or cataphote)
device or surface that reflects vibroacoustic radiation back to its source
with minimum scattering. This works
by optimizing a specific angle of incidence relative to distance (unlike a
planar mirror, which does this only if
the mirror is exactly perpendicular to the wave front, having a zero angle of
incidence). Being directed, the
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retroflector's reflection could be higher/lower energy brighter than that of a
diffuse reflector. Reflector design
is based on light reflectors e.g., corner reflectors, and cat's eye
reflectors.
[482[ In certain variations, an output display unit 3330 is provided which is
separate to the panel unit and the
base unit, but communicatively coupled thereto. The output display unit 3330
may be embodied as a standalone
screen or in a mobile device such as a smartphone or tablet. The output
display unit 3330 may be arranged to
cause display of a virtual representation of the subject, in the form of an
avatar for example. Depending on the
context, the avatar may be a simple outline of a human figure or a detailed
photo-realistic image. The avatar
may be used to present data, such as the location of detected objects on the
subject's body to security personnel,
or to provide cues or instructions to the subject as to what pose to present,
or what motions to perform. This
feature may be used to enhance the performance of the system by eliminating
blind spots, or to provide guidance
for the performance of exercises or physical therapy movements.
[483] The computing system / processor may be incorporated, at least in part,
within one or a combination of
the base unit, the panel unit and the output system. The computing system may
be incorporated, at least in part,
in a server.
[484] A barrier (not shown), associated with one or more of the panel unit and
the base unit, may also be
provided, for delimiting the progress of the subject. On determination of the
subject not having a given bodily
condition, the computing system can cause the opening of the barrier to allow
the subject to physically away.
[485] In addition, there may be further provided a transductivc patch that may
be applied to a body surface
and comprise have conductive electrodes on the inner surface that are
connected via a thin inductive pattern that
is present on the patch and/or capacitive elements. Thus, when the subject is
proximate one or more of the panel
unit, base unit and/or top unit, an alternating electromagnetic field may be
used to induce a potential in the thin
inductive pattern that is conducted to the skin electrodes creating an LRC
circuit, whose electrical response
properties may be remotely monitored. The patches may be made of paper/plastic
laminates, using conductive
ink or other printed circuit technologies. The patch could serve a second
purpose of identifying persons that
have already been successfully screened.
[486] In this manner, a whole host of measurements may be made remotely that
otherwise would require
intimate contact and the opportunity to spread infection. Moreover, by
allowing subjects to apply the patches
themselves, issues of modesty are resolved when the ideal measurement surface
is in the groin or chest area. In
other variants, if the transductive patches or beacons are relatively
expensive, a reusable version which attaches
with a reusable, or replaceable adhesive system may be used. The device would
be given out before the subject
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enters the apparatus, and removed after use, sanitized and prepared for re-
use, such as is done with 3-d glasses
in movie theatres.
[487] According to certain aspects of the present technology, there is thus
provided a system for screening for
a target condition in a subject, the system comprising: a device comprising: a
first portion having a first sensor
incorporated therein, the first sensor arranged to capture physiological data
from the subject, and a second
portion having a second sensor incorporated therein, the second sensor
arranged to capture physiological data
from the subject; wherein the first and second sensors are positioned relative
to each other to capture
physiological data along different planes extending through the subject. In
certain embodiments, the first portion
and second portion may be positioned orthogonally with respect to each other.
In certain embodiments, one or
both of the first portion and the second portion are arranged to be supported
by a support surface such as a wall,
a floor or a ceiling in use. In certain embodiments, the first portion of the
device is a platform arranged such
that the subject can stand on the platform in use. In certain embodiments, the
first sensor is a bioelectric sensor
in the platform. In certain embodiments, the second portion of the device is a
panel which is substantially vertical
and arranged relative to the first portion such that a front face of the panel
faces a face of the subject when the
subject is standing on the platform. The first and second sensors may comprise
a bio-electric sensor and a vibro-
acoustic sensor, respectively. The bio-electric sensor may be positioned in a
portion of the device which is
relatively horizontal and permits contact with a body part of the subject,
such as the foot. The vibro-acoustic or
other sensor may be positioned in a portion of the device which is
substantially vertical and having a panel face.
The device may be arranged such that when the user stands on the portion of
the device with the bio-electric
sensor, a face of the subject faces the panel face.
[488] In certain embodiments, there is provided a computing system,
communicatively coupled to the first
sensor and the second sensor and arranged to execute a method, the method
comprising, obtaining the captured
physiological data from one or both of the first sensor and the second sensor,
and feeding the obtained
physiological data to an MLA, the MLA being arranged to determine a likelihood
of the subject having the
target condition based on the obtained physiological data.
[489] Developers have identified that certain inaccuracies may be present
in detected physiological
parameters using sensors through footwear donned by different subjects i.e.
having different weights,
movement of the subject during data acquisition. Accordingly, embodiments of
the present technology describe
the discovery that fusion of data from sensors orthogonal in orientation or
theory of operation to relative to a
docking position (for example the floor) based electrical or electromagnetic
sensors can allow for the
disambiguation of the electrical or electromagnetic sensor data to correlate
the electrical or electromagnetic
sensor data to the presence of a target condition. The sensors may also
include electromechanical,
electrochemical and electromagnetic sensors. Even more remarkably, the very
motions and subject presentation
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variations that were thought to create unacceptable noise in the signal from
these sensors can be used to probe
the subject's response to various environmental or purposefully applied
stimuli and thus increase the accuracy
and specificity of the measurement.
Animal gate
[490] With reference to FIG. 60, embodiments of the sensing devices of the
present technology and associated
methods may be used to monitor or diagnose health status and conditions of
animals, such as livestock. In this
respect, the sensing device may be embodied as a panel (such as the upright
unit 3325 of FIG. 33) and
incorporated in a gate or holding assembly for the animal. As can be seen in
FIG. 60, the holding assembly for
the animal is a gated cage, having an entry gate and an exit gate for
permitting the animal to enter and exit,
respectively, the gated cage. The upright unit 3325 is mounted to an inside of
the gated cage and can collect
data from the animal held within the gated cage using the one or more sensors
described herein.
[491] Embodiments of the devices, methods and systems of the present
technology provide for the calculation
of optimal feed amounts, supplementation rates and nutrient ratios for one or
more of: maximizing growth rates;
maximizing meat quality (i.e. choice versus select, prime versus choice);
maximizing milk production;
preventing nutrient deficiencies; de-risking pregnancy; maximizing work
output; minimizing methane and other
greenhouse gas emissions; minimizing feed cost; preserving pasture quality;
and decreasing stress related
behavior.
[492] In other aspects, embodiments of the devices, methods and systems of the
present technology may
provide for the estimation of the phase of the reproductive cycles of animals
and for the early detection of
pregnancy to enhance the efficacy of reproductive management systems.
[493] In yet other aspects, embodiments of the devices, methods and systems of
the present technology may
provide for detection of certain conditions of the animal.
[494] In this respect, the gated cage may also be provided with one or more
robotic arms for administering a
treatment such as through transdermal injection.
Considerations during design of different form factors and choice of sensors
[495] It will be appreciated that in choosing a form factor and the one or
more sensors, consideration must be
given to the behavior of acoustic field at certain distances from the subject:
Near Field; Far Field; Free Field,
and Diffuse Field acoustics. Depending on how far away an observer / sensor is
from a vibration/sound emitting
object, the vibration/acoustic energy produced by the vibration/sound source
will behave quite differently.
Far field
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[496] The acoustic far field is defined as beginning at a distance of two
wavelengths away from the sound
source, and extends outward to infinity. As wavelength is a function of
frequency, the start of the far field is
also a function of frequency. In the far field, the source is far enough away
to essentially appear as a point in
the distance, with no discernable dimension or size. At this distance, the
spherical shape of the sound waves
grow to a large enough radius that one can reasonably approximate the wave
front as a plane-wave, with no
curvature. At this distance, sound pressure level is governed by the inverse
square law, and a single microphone
sound recording will give reliable & predictable results. For each doubling of
distance away from the source,
the sound pressure will drop 6 dB in the far field. In many acoustic
standards, measurements are often specified
at a distance of at least one meter from the sound emitting object to ensure
that the measurement is taken in the
far field for the most critical frequencies.
Near Field
[497] When close to a sound emitting object, the sound waves behave in a much
more complex fashion, and
there is no fixed relationship between pressure and distance. Very close to
the source, the sound energy
circulates back and forth with the vibrating surface of the source, never
escaping or propagating away. These
are sometimes called "evanescent- waves. As we move out away from the source,
some of the sound field
continues to circulate, and some propagates away from the object.
[498] This transition from circulating to propagating continues in an
unpredictable fashion until we reach the
threshold distance of two wavelengths, where the sound field strictly
propagates (the far field.) This mix of
circulating and propagating waves means that there is no fixed relationship
between distance and sound pressure
in the near field, and making measurements with a single microphone can be
troublesome and unrepeatable.
Acoustic arrays featuring many microphones must therefore be used close to a
source to accurately capture
sound energy in the near Field.
Free Field versus Diffuse Field
[499] When sound radiates from an object, it can reach an observer directly by
traveling in a straight line, or
indirectly via reflections. Reflected sound waves can bounce off surfaces such
as walls, the floor, ceiling, as
well as other objects in the area. Often when we experience sound, we are
receiving both direct and reflected
sound waves. Under carefully controlled circumstances, however, we can
experience the extreme ends of this
continuum: 1) an acoustic field where zero reflections are present; and only
the direct sound is observed, and 2)
the opposite acoustic field, where zero direct sound is observed, and only
reflected sound is present. The names
given to these two extreme acoustic environments are free field and dijiiise
field respectively. In an acoustic free
field there are no reflections; sound waves reach an observer directly from a
sound em itting object. The sound
wave passes the observer exactly once, and never returns. Two common examples
of acoustic free fields are:
(i) the sound source is far enough away that it appears as a single point
source, far in the distance. Visualize an
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airplane flying high overhead on a clear day. (ii) An anechoic chamber is a
special facility constructed to
approximate an acoustic free field by using materials to absorb sound waves
before they can be reflected.
2. Methods for characterizing a bodily condition
[500] As shown in FIG. 34, in some variations, a method 3400 for
characterizing a bodily condition may
include detecting a vibroacoustic signal with a vibroacoustic sensor module
3410 (or vibroacoustic sensor
module 420, 1600), extracting a vibroacoustic signal component from the
vibroacoustic signal 3420, and
characterizing a bodily condition of the subject 3430 based at least in part
on the extracted vibroacoustic signal
component using a machine learning model. In some variations, the method 3400
may comprise obtaining
vibroacoustic data from a vibroacoustic sensor, and characterizing a bodily
condition of the subject based at
least in part on the vibroacoustic data using a machine learning model. In
some variations, instead of, or in
addition to the vibroacoustic data, the method 3400 may comprise obtaining
data from any sensor module
described herein such as an optical sensor, a bioelectric sensor, a capacitive
sensor, a thermal sensor, etc. The
method may, at least in part, be executed by a processor of a computer system.
In certain variations, the bodily
condition is COVID-19, and the method comprises detecting a vibroacoustic
signal within a frequency range
of: about 0.01 Hz to at least about 160 kHz.
[501] The data may be obtained as a live stream. Alternatively, the obtained
data may be sampled from a total
volume of detected data by the one or more sensors. The data may be captured
as catenated raw amplitude
sequences or as combined short-time Fourier transform spectra. The data from
the sensors may be captured
from the subject in less than 15 seconds per subject, and preferably in less
than 10 seconds per subject.
[502] The method 3400 may comprise an optional prior step of causing the one
or more sensor modules to
start capturing the data based on a trigger. The trigger may be manual (e.g.
initiated by a user of the system) or
automatic and based on a predetermined trigger parameter. The trigger
parameter may be associated with a
proximity of the subject to the system 10, or a contact of a body part of the
subject with the device (such as
when the feet of the subject contact the base unit), or on detection of a
predetermined physiological parameter
such as an elevated body temperature.
[503] The processing of the data to determine a presence or absence of the
bodily condition may take less
than 15 seconds per subject, such as about 14 seconds, about 13 seconds, about
12 seconds, about 11 seconds,
about 10 seconds, about 9 seconds, about 8 seconds, about 7 seconds, about 6
seconds, about 5 seconds, or less
than 5 seconds. in certain variations, the vibroacoustic signal detected by
the system spans between 3 and 5
heart beats of the subject.
[504] Optionally, the method may comprise causing an output of the
determination of the bodily condition to,
for example, the output device 3330 described herein. The output may take any
form such as an audio output
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(e.g. a beep), a visual output (e.g. a flashing light), a haptic output (e.g.
a buzz), a mechanical output (e.g.
barriers being opened or closed). In certain variations, the output may be an
alert such as a green light indicating
absence of the target condition or a red light indicating presence of the
target condition. In other variations, the
output may comprise causing the physical retention of the subject through
control of a physical restraint member
such as a barrier.
[505] One or more of the sensor data, the determination and the output may be
stored, such as in a database
of the computing system. The stored data may be fed to a training MLA.
[506] The method 3400 may comprise causing the one or more sensor modules to
stop obtaining data based
on a manual or automatic trigger. The automatic trigger may comprise a
predetermined threshold such as a time
interval or the like.
[507] The processing the data or training the MLA comprises associating a
given target condition with
symptoms of the given target condition. The symptoms may include one or more
symptoms related to the
subject's throat, chest, constitution, gut, nasal system, eyes, and
vascularization. These symptoms may include,
but are not limited to a sore, painful, swollen, or scratchy throat, loss of
taste, or difficulty in swallowing. The
chest associated symptoms are trouble breathing, congestion, tightness, dry
cough, hacking cough, wet cough,
loose cough, mucous, phlegm or fibrosis. The constitutional symptoms may be
dyspnea, muscle spasms,
pyrexia, body aches, fatigue, malaise, general discomfort, fever, or chills.
The gut associated symptoms may be
loss of appetite, altered gut motility, stomachache, emesis, nausea, or
diarrhea. The nasal symptoms may be
rhinorrhea, redness of the nasal openings or congestion. The ocular symptoms
may be glassy eyes and
conjunctival injection. The vascularization symptoms may include clotting,
bruising, etc. For example, sore
throat, dry cough, shortness of breath, muscle spasm, chills, fever, gut
discomfort, brain fog and diarrhea are
key indicators of a possible coronaviridae (e.g. COVID-19) infection.
[508] These and other indicative symptoms that can be detected in a non-
invasive, contactless manner by
variants of the present technology are typically due to changes in tracheal
and lung thickness, respiratory
depression, local and systemic fluid accumulation (edema), oxygen
desaturation, hypercapnia, trauma, scarring,
tissue irritation, fibrotic changes, hypoventilation and hypertension.
Variants of the present technology can be
used to detect early and subtle changes in lung and upper respiratory airway
audible and inaudible wheezes,
crackles, and egophony ___ often caused by lung consolidation, diffuse
alveolar damage. vascular injury, and/or
fibrosis, with or without ECG.
[509] Other physiological states or levels of metabolites or environmental
toxins that can be detected by the
method 3400 include mechanical trauma and injury, elevated interleukin (IL) 6
and polymorphonuclear
inflammatory, cells and mediators, lymphoid hypertrophy and prominence of
adenoidal and tonsillar tissue,
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kinins, histamine, leukotrienes, prostaglandin D2, and TAME-esterase, ACE
inhibitor increase in pro-
inflammatory pharyngeal irritation, orophalyngeal mucositis, and the direct
effect of ozone on respiratory tract
cell membranes and fluid, lipid ozonation product activation of specific
lipases that trigger the release of
endogenous mediators of inflammation such as prostaglandin E, IL8, thromboxane
B2 and calcitonin gene-
related peptide.
[510] In some variations, the method 3400 may be performed with any of the
systems or sensing devices
described herein, which may have any suitable variation of a vibroacoustic
sensor module and/or other sensor
modules. The sensing device may have any form factor such as a hand-held,
stethoscope. panel, mirror, kiosk,
gateway. The method may, for example, utilize a vibroacoustic sensor module
with a plurality of MEMS or
other suitable sensors (e.g., accelerometer, pressure sensor, microphone,
voice coil transducer, piezoelectric
transducer, etc.). In certain variations, data from a vibracoustic sensor
module based on a voice coil transducer
is combined with data from an echo doppler sensor module. Such sensors may, in
some variations, interface
with one or more deflecting structures (e.g., flexure arms, membrane, etc.) as
described above. In other
variations, the method 3400 may use the sensing device 400 including the
vibroacoustic sensor module 420.
[511] In some variations, the extracted vibroacoustic signal component may
include a biological vibroacoustic
signal component, and the bodily condition characterized may include a health
condition based on the biological
vibroacoustic signal component. In this respect, the method may comprise
extracting the biological
vibroacoustic signal component. In certain variations, extracting the
biological vibroacoustic signal component
comprises passing the vibroacoustic signal through a first stage amplifier and
a first stage low pass filter, and a
second stage amplifier and a second stage low pass filter. The first stage low
pass filter and the second stage
low pass filter may form a second order low pass filter with anti-aliasing,
wherein the second order low pass
filter has a cutoff frequency of about 15 kHz to about 20 kHz. In certain
variations, the vibroacoustic signal is
also passed through a third stage amplifier comprising a programmable gain
amplifier configured to dynamically
amplify at least a portion of the vibroacoustic signal. In certain variations,
the extracting the biological
vibroacoustic signal component comprises digitizing the amplified portion of
the vibroacoustic signal and
providing at least a portion of the digitized vibroacoustic signal as a
digitized biological vibroacoustic signal
component.
[512] For example, the method 3400 may assist healthcare professionals in
collecting and intelligent analysis
of audible and inaudible signals associated with cardiac, lung, gut and other
internal organ functions, for rapid
and accurate diagnostics such as that relating to cardiopulmonary,
respiratory, and/or gastrointestinal function.
In certain variations, the method 3400 may assist in the diagnosis of a viral
infection, such as that of a
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coronaviridae or SARS virus. In certain variations, the method 3400 may assist
in monitoring efficacy of a
certain treatment, such as during a clinical trial.
[513] The method 3400 may include collecting data generated by the body
passively without imparting any
energy (e.g., current or voltage) to the body. For example, the sensing device
may be placed on the skin (e.g.,
at designated auscultation points, similar to a stethoscope), on the body over
clothing at designated auscultation
points, or pointed at the body (e.g., at designated auscultation points) to
passively harvest signals generated by
the body. Auscultation points may include one or more of the subject's neck,
chest, back and torso. As described
in further detail herein, the sensing device may collect and process audible
and inaudible signals passively
harvested from the body. The signals and/or analysis thereof may be
communicated to an external device (e.g.,
mobile computing device) in a wired or wireless manner. In some variations,
transmitted data may be encrypted
before being saved to personalized folders for secure storage and subsequent
playback in a mobile application
executed by a mobile computing device. The application may provide the ability
to save collected data within
designated Electronic Medical Records (EMR)/Electronic Health Record (EHR)
systems, share patient
recordings, and annotate notes on recorded audio, etc. (Data pre-processing)
[514] The sensing devices, sensor modules, systems, and methods of the current
technology may be useful in
detecting conditions, such as physiological states, in living organisms
including but not limited to: respiratory
illnesses and diseases such as coronaviridae (e.g. COVID-19, SARS, Digestive
illnesses and diseases, Cancer,
Neurological illnesses and diseases, Psychiatric illnesses and diseases,
Cardiac illnesses and diseases,
circulatory illnesses and diseases, lymphatic illnesses and diseases, kidney
illnesses and diseases, liver illnesses
and diseases, lung illnesses and diseases, Osteopathic illnesses and diseases,
Orthopedic illnesses and diseases,
sleep related illnesses and diseases, metabolic diseases, disorders, and
states, movement disorders, viral,
bacterial, fungal, parasitic, protozoal, and prion infections, substance use
disorders, behavioral disorders,
musculoskeletal illnesses and diseases, blood illnesses and diseases,
disfunction of internal organs, genital
illnesses and diseases, emotional disturbances, disorders or states,
alertness, fatigue, anxiety, depression,
delirium, disorientation, ataxia, insomnia, eating disorders, obesity, body
composition, and such.
[515] in certain aspects at least one of a key symptom of the coronoviradae is
determined from one or more
of the above described measurements. A physiological state may refer to, but
is not limited to, a viral infection
in a subject, a bacterial infection in a subject, presence of a foreign body
in the subject such as an implant or an
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improvised explosive device (TED). Examples of physiological states include
but are not limited to infections
of coronaviridae (e.g., COVID-19), SARS in the subject.
[516] In certain aspects, a measurement of a physiological parameter can be
made using one or a combination
of sensors.
[517] In certain aspects, the physiological state determination is subject to
type I errors less than 0.1%, 0.2%,
0.3%, 0.4%, 0.5%, 0.6%, 0.7%,0.8%, 0.9% or 1%. In certain aspects, the
physiological state determination is
subject to type II errors less than 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 0.6%,
0.7%,0.8%, 0.9% or 1%. In certain
aspects, the physiological state determination is subject to type I errors
less than 1.1%, 1.2%, 1.3%, 1.4%, 1.5%,
1.6%, 1.7%, 1.8%, 1.9% or 2%. In certain aspects, the physiological state
determination is subject to type II
errors less than 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%, 1.7%, 1.8%, 1.9% or 2%.
In certain aspects, the
physiological state determination is subject to type I errors less than 2.1%,
2.2%, 2.3%, 2.4%, 2.5%, 2.6%,
2.7%, 2.8%, 2.9% or 3%. In certain aspects, the physiological state
determination is subject to type II errors less
than 2.1%, 2.2%, 2.3%, 2.4%, 2.5%, 2.6%, 2.7%, 2.8%, 2.9% or 3%. In certain
aspects, the physiological state
determination is subject to type I errors less than 3.1%, 3.2%, 3.3%, 3.4%,
3.5%, 3.6%, 3.7%, 3.8%, 3.9% or
4%. In certain aspects, the physiological state determination is subject to
type II errors less than 3.1%, 3.2%,
3.3%, 3.4%, 3.5%, 3.6%, 3.7%, 3.8%, 3.9% or 4%. In certain aspects, the
physiological state determination is
subject to type I errors less than 4.1%, 4.2%, 4.3%, 4.4%, 4.5%, 4.6%, 4.7%,
4.8%, 4.9% or 5%. In certain
aspects, the physiological state determination is subject to type II errors
less than 4.1%, 4.2%, 4.3%, 4.4%,
4.5%, 4.6%, 4.7%, 4.8%, 4.9% or 5%. In certain aspects, the physiological
state determination is subject to type
I errors less than 6%, 7%, 8%, 9%, 10%, 15%, 16%, 17%, 18% or 19%. In certain
aspects, the physiological
state determination is subject to type II errors less than 6%, 7%, 8%, 9%,
10%, 15%, 16%, 17%, 18% or 19%.
[518] In certain aspects, above levels of accuracy are achieved with less than
2, 3, 4, 5, 6, or 7 sensors. In
certain aspects, a throughput of the system ranges from at least 100 subjects
scanned per hour to about 1,000
subjects scanned per hour. In certain embodiments, the throughput is about 500
subjects scanned per hour. In
some variations, the method 3400 for characterizing a bodily condition may
include detecting vibroacoustic
signals with active skin motion amplification methods in sensor module. The
vibroacoustic signal component
from the vibroacoustic signal may be extracted using active and energy
imparting technologies including
accelerometer-based vibroacoustic, common-path interferometric imaging,
ultrasonic vibrometry, and/or other
energy imparting technologies examples. Examples of active and/or energy
imparting methods may assist
healthcare professionals in collecting and intelligent analysis of skin
surface vibroacoustic signals associated
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with the physical human body to assess health. For example, cough transmission
through the body to the skin
surface, oral, and nasal cavities may signal many things by its length,
intensity, tone, frequency, etc.
[519] In some variations, an acoustic vibrometry active sensing module may be
added as an interoperable
subsystem for measuring low frequency, low amplitude mechanical, vibroacoustic
and skin surface mechanical
motion amplification properties of a subject including using an a wide
bandwidth acoustic transducer to apply
wide bandwidth vibration pulses to skin surface (face, neck, chest, gut,
bladder, uterus, or whole body, etc.).
The applied vibration pulses may occur in an on-off time sequence in order to
impart a harmonic motion at a
prescribed frequency to the subject, and when the vibration pulses are off,
the same (or other) transducer may
be used to apply acoustic detection pulses to a motion detection point and to
receive echo signals in order to
sense the harmonic motion on the subject at the motion detection point. From
the harmonic signal information,
a harmonic signal may be detected and a characteristic such as amplitude or
phase of the detected harmonic
signal may be measured. The skin motion mechanical property may be calculated
using the measured
characteristic using, for example, a wave speed dispersion method.
[520] In an exemplary variation, an acoustic vibromary active sensing module
may bc added as an
interoperable subsystem for measuring low frequency, low amplitude mechanical,
mechano- acoustic and skin
surface mechanical motion amplification properties of a subject including
using a multi-frequency ultrasonic
wave generator generating at least first and second ultrasonic waves. The
multi-frequency ultrasonic wave
generator may be arranged such that in operation, at least the first and
second ultrasonic waves mix in a
prescribed mixing zone to produce a difference-frequency acoustic wave.
Parametric and multi-transducer
variations have been tested. A receiver sensor may detect the difference-
frequency acoustic wave and produce
corresponding voltage-time or electromagnetic signals. The voltage-
time/electromagnetic signals may be
processed by a system processor and resulting signals may be indicative of
skin or surface motion. In some
variations, the ultrasonic waves may be focused to a small prescribed mixing
zone.
[521] in an exemplary variation, an ultra-wideband vibrometry active sensing
module may be added as an
interoperablc subsystem for measuring low frequency, low amplitude mechanical,
mcchano-acoustic and skin
surface mechanical motion amplification properties of a subject including
using an ultra-wideband monitoring
system and antenna. The subsystem for physiologic signal monitoring and
amplification may include a signal
generation/monitoring station and at least one sensor in communication with
the monitoring station. The sensor
may include an antenna system and an ultra-wideband radar system coupled to
the antenna system. The ultra-
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wideband subsystem may be configured to extract from the signal information
about physical or structural
mechanoivibroacoustic data in a sensing volume corresponding to the antenna
system volume.
[522] Signal processing and communications may be shared across the entire
vibroacoustic sensing module
and routed through a central microcontroller unit.
[523] In an exemplary variation, an optical vibrometry active sensing module
may be added as an
interoperable subsystem for measuring low frequency, low amplitude mechanical,
mechano- acoustic and skin
surface mechanical motion amplification properties and subsequent
classification. In one example, an active
optical source may generate and direct coherent light toward the subject. An
optical imaging system may collect
light reflected or transmitted from the physical subject including a scattered
component and a specular
component that is predominantly undiffracted by the sample. A variable phase
controlling system may be used
to adjust the relative phase of the scattered component and the specular
component so as to change the way they
interfere at the image plane.
[524] The resultant signal may be compared to a reference signal for the same
location on the sample location
and the difference may be translated into a distance to the image plane. The
process may be rapidly repeated in
high frequency to map the time-dependent movement of the focus point on the
image plane. This data may then
used to calculate an amplitude and phase between data sampling points, which
can be used for motion
amplification, detection, and classification. This method may detect much
smaller defects related to the
wavelength, amplitude and operational light frequency.
[525] In certain variations, the signal processing system further comprises a
second analog subsystem
comprising a programmable gain amplifier configured to dynamically amplify at
least the selected portion of
the vibroacoustic signal, and an analog-to-digital converter providing a
digitized biological vibroacoustic signal
component.
Examples
Example 1: Vibroacoustic data acquired using an accelerometer-based
vibroacoustic sensing module
[526] A sensing device was built as shown and described above with respect to
FIGS. 5A-5T, and included a
vibroacoustic sensing module having two flexure arms coupled to a central hub
interfacing with an
accelerometer. The sensing device was placed over a chest auscultation point
on a subject, and was used to
measure a vibroacoustic signal. The vibroacoustic signal was then conditioned
in a signal processing chain as
described above with respect to FIG. 24, to extract a biological vibroacoustic
signal component from the
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measured vibroacoustic signal. FIGS. 35A and 35B depict the resulting
extracted biological vibroacoustic signal
over the measurement period.
Example 2: Combined accelerometer, MEMS microphone, high fidelity barometric
pressure sensor
and voice-coil technology
[527] The combination of accelerometer, MEMS microphone, high fidelity
barometric pressure sensor and
voice-coil technology was arranged to detect vibroacoustic signals from
infrasound to high ultrasound (0.1 Hz
to 160 kHz). Implemented software-defined hardware was arranged in various
form-factors to passively and
discreetly, for example: detect and target drone/loitering munitions defense,
detect buried/implanted ordinance
(e.g., body cavity bomb detection), monitor structural health and track
efficiency of concrete and steel structures,
as well as rotating machines and equipment from turbines to generators, see
through walls to search for and
enable rescue of people in collapsed structures, detect footsteps and
vehicular / animal traffic, etc. at sensitive
borders, and/or the like. The combination of directional vibroacoustic and
mechano-acoustic sensor modalities
provide a unique set of low frequency, low amplitude vibrations and
fluctuating shear-wave fields heterogenous
degrees-of-freedom on which to optimize over.
[528] FIG. 44 depicts example vibroacoustic test data gathered for a consumer
drone with interchangeable
fixed wing and variable wing speed. The vibroacoustic data shown in FIG. 44
illustrates signal richness for
algorithm-driven reliable drone detection, tracking, and classification.
Accordingly, these test results
demonstrate that ability to capture data from which information associated
with a consumer drone may be
derived (e.g., drone characteristics such as fixed-wing or multi-rotor, size,
shape, payload, speed, etc.).
Example 3: Vibroacoustic data acquired using a voice coil-based vibroacoustic
sensor module
[529] Data was collected using exemplar variations in laboratory (using a
human manikin phantom) and
exploratory clinical tests. Specifically, as shown in FIGS. 37A-37D, signals
were applied to the phantom and
captured with the vibroacoustic system described above, more particularly the
sensing device 400 described in
FIG.4H. FIGS. 37A and 37B illustrate a 3 Hz time domain and its frequency
domain signal, respectively. FIGS.
37C and 37D illustrate a 10 Hz time domain and its frequency domain signal,
respectively. The study confirmed
that the phantom transmits signals accurately, well into the infrasound
frequency range, and that signals are
captured properly with the illustrative vibroacoustic system.
[530] Illustrative vibroacoustic system performance testing was performed
using human manikins, and in
clinical pilot studies to compare skin coupling vs. over clothes of different
types (e.g., thicknesses). One test
consideration compared performance consistency of the illustrative
vibroacoustic system on skin versus both
thin and heavy clothing on the manikin and live human being. Data was
collected from the same live human
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participant recovered from direct coupling on skin (FIGS. 38A-38B), through a
T-shirt (FIGS. 39A-39B), and
a thick wool sweater (FIGS. 30A- 30B). As shown in FIGS. 38A-38B, 39A-39B, and
40A-40B, correct capture
of vibroacoustic signals by the vibroacoustic system was achieved on skin and
through a variety of clothing
with minimal or no deterioration.
Example 4: Modeling and classification of fatigue states using novel
vibroacoustic data
[531] Vibroacoustic data from a test subject was acquired using a variant of a
sensing device according to the
present technology (the sensing device 400 of FIG. 4 including the ECG sensor
module) and used to assess a
segmentation algorithm and train and test a model for predicting fatigue
states based on vibroacoustic data.
Clinical data collection
[532] Vibroacoustic data was collected in a cold pressor test by having
subjects immerse the non-dominant
hand into an ice water bucket for one minute, and measuring changes in heart
rate. These changes relate to
vascular response and pulse excitability. Data was collected from healthy male
participants aged 36 to 49 during
rest and a cold ice water dip exercise aimed to simulate pain. Prior to the
data collection session, all participants
were encouraged to follow their normal daily routine including sleep, meals
and hydration. Data was recorded
around the intersections of the 2nd to 3rd intercostal spaces and the left
midclavicular line. This position was
chosen based on its proximity to the heart.
Data classification
[533] Many machine learning algorithms require large amounts of data before
they begin to give useful
results. The larger the architecture, the more data is needed to produce
viable results. To augment training data
for the ML/AI toolbox, vibroacoustic and mechano-acoustic data of aircraft
takeoffs and landings at SFO
International Airport and tracking traffic at neighborhood bridges in Alameda,
Santa Clara, and San Mateo, CA
counties was collected continuously. SFO and bridge sensor systems were
trained to real time flight, weather,
emissions and air quality databases available at hups://flightavvare.com/,
https://511.org/open-data/traffic and
haps ://www.arb.c a. gov/aqm i s 2/m etsel ect. php, respectively.
[534] Rest versus pain clinical vibroacoustic data classification was
initially approached following music
genre classification approaches. However, commercial music search algorithms
are only concerned with music
genres as a flat classification problem. The idea of using the hierarchy for
browsing and retrieval has been
explored in a limited number of existing tools for organizing music
collections. End-user systems based on the
use of multiple hierarchies to organize music collections incorporate user
feed-back in order to re-organize the
pre-existing class hierarchy as the users see fit. The latter approach of user-
defined creation of taxonomy creates
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new (meta-) classes on the fly on top of a pre-established taxonomy. In
principle, the vibroacoustic signal
hierarchical classification algorithm permits the creation of new classes,
which is related to clustering.
[535[ Therefore, in contextualized vibroacoustic hierarchical clustering, we
are interested in both hierarchical
classification (a type of supervised learning) and hierarchical clustering (a
type of unsupervised learning) in
order to resolve atomistic and ecological fallacies. By combining hierarchical
classification and hierarchical
clustering, individuation or identification (of the atom) is extreme
classification and identification/individuation,
segmentation, clustering, and hierarchical classification fall along a "IS-A-
continuum as asymmetric, anti-
reflexive, and transitive. The -1S- A" relation is asymmetric (e.g. all dogs
are animals, but not all animals are
dogs) and transitive (e.g., all pines are evergreens, and all evergreens are
trees; therefore, all pines are trees).
[536] A notion of contextualized vibroacoustic data hierarchical
classification is to use machine learning
(ML) and other forms of adaptation to optimize software. Compared to
mainstream ML, the difference is to
start with pre-established taxonomy and software artefacts (possibly very
imperfect software artefacts) produced
by 'domain experts.' Secondly, the software artefacts are in general much more
expressible than off-shelf ML
models like neural nets or decision trees. Thirdly, contrary to typical ML
scenarios with clearly delineated
training and test phases, learning and optimization is performed cinline.' In
other words, an cinline learning'
algorithm is embedded within a software system, allowing it to learn
adaptively as the system processes new
data. Such adaptation typically leads to more performant software systems
(with respect to various functional
and nonfunctional properties/metrics), because it (i) can correct for the
suboptimal biases introduced by human
designers and/or -domain experts," and (ii) responds swiftly to changing
characteristics and operating
conditions (mostly to variation in data being processed).
[537] Without the right algorithms to refine data, the real value of high-
resolution sensor data fusion will
remain hidden. Popular approaches such as neural nets model correlation, not
causal relationships, and do not
support extrapolation from the data In contrast, the proposed novel Structural
Machine Learning (SML)
platform, is a natural feedforward and feedback platform, where data
exploration and exploitation can be
achieved faster and more accurately.
[538] Optimization is one of the core components of machine learning. The
essence of most machine learning
algorithms is to build an optimization model and learn the parameters in the
objective function from the given
data. Variational inference is a useful approximation method which aims to
approximate the posterior
distributions in adaptive machine learning. Structural Machine Learning (SML)
were fitted to the full
bandwidth, high pass (HP)-filtered, and low pass (LP)-filtered contextualized
vibroacoustic data segments.
[539] Four exemplary program expressions (Programs A-D) for data
classifications are shown below.
Program A:
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autocorrelate (min J lter(moving avg(x, MovingAverage Window 0), WindowSize
1)) Constants A:
{ MovingAverage Window 0 ' : MovingAverage Window (data-3),
WindowSize]':
WindowSize(data-381))
Program B:
concat(lowpass butter(max_filte r(exponential m.ovi ng avg(x, Movi ngA
verageWindow 0),
WindowSize 0), CutqffRatio 0,SamplingRate 0,
FilterOrder0), autocorrelate (min .filter(x,
WindowSize])),)
Constants B: { MovingAverage Window 0 ' : MovingAverage Window (data= 7), '
Cut offRatio 0':
CutoffRatio(data- 0.99999), 'WindowSize0 ' : WindowSize(
data 220), 'WindowSize 1':
WindowSize (data= 262), 'FilterOrder0 Fi IterOrder(data =I ),
'SamplingRate 0 ':
SamplingRate(data= 1000. 0))
Program C:
time width (mu! vecs (exponential moving m,g(X,
MovingAverage Window 0), x)) Constants C:
MovingAverage Window 0 ' : MovingAverage Window (data- 3))
Program D:
concat(highpac,s butte r(x, CutolfRatio I,
SamplingRate 0, FilterOrder1),
dot product(min filter(min filter(X, WindowSize]),
WindowSize]), min filter(Moving avg(k,
MovingAverage Window]), WindowSize I )))
Constants D: MovingAverage Window 1 ': MovingAverage Window (data- 3), '
CutoffRatio 1 ':
Cutofflatio (data= O. 99999), ' WindowSize I ':
WindowSize( data= 169), FilterOrderl
FilterOrder (data= 1), 'SamplingRate 0 SainplingRate (data= 1000.0))"
[540] Score (fitness) is multidimensional generalization of ANOVA F-statistic.
It increases with between
group variance and decreases with increasing within group variance. Table 3
shows scores for the exemplary
Programs A-D.
Table 3. Scores for the Exemplary Programs A-D
Program Score (log(F))
Train Test
A 6.15 4.36
5.99 4.36
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5.50 4.06
6.13 4.47
[541] Program output visualization shows that some kind of clustering is
achieved. The goal is to look for
tight, homogenous groups of points that lie far from each other. Subjects and
data from training/test sets are
represented by different colors. A '*' means that group of points come from
the test set. Figures 31A-31E
illustrate outputs of programs on identification task.
[542] Two additional exemplary program expression (Programs E and F) for data
classifications are shown
below.
Program E:
lowpass butter(moving avg(minfilter(minjilter(rinjilter(x,
WindowSize 0), Window Size 1),
WindowSize0), MovingAverageWindow0), CutoffRatio0 SamplingRate0, FilterOrder0)
Constants E:
MovingAverageWindow0': MovingAverageWindow(data= 125), ' CutolfRatio0':
CutoffRatio(data=0 99999), 'WindowSize0': WindowSize( data=11),
'Wi ndowSize I ' :
WindowSize (data= 33), 'FilterOrder0' : FilterOrder(data= 1), 'SamplingRate0
SamplingR ate (data= 1000))
Program F:
lowpass butter(mul vecs(moving avg(div vecs( exponential
moving avg(x,
MovingAverageWindow0), medianjilter(x, WindowSize0)), MovingAverageWindow0),
exponential moving avg( moving avg(min_filter(x, WindowSize0),
MovingAverageWindow0),
MovingAverageWindow0)), CutoffRatiol, SamplingRate0, FilterOrderl)
Constants F: {MovingAverageWindow0': MovingAverageWindow(data=106),'
CutoffRatiol
CutoffRatio(data=0.99999), 'WindowSize0': WindowSize( data-54), 'FilterOrderl
FilterOrder(data=1),
'SamplingRate 0 ': S'amplingRate (data¨ 1000))
[543] Table 4 illustrates results of a segmentation task where score is mean
AUC of segmentation of a given
pattern on all data samples, for Programs E and F.
Table 4. Segmentation task for Programs E and F
Program Score (mean AUC)
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Test Test
Si S2
0.97 0.81
0.91 0.95
[544] Output visualization of Programs E and F is shown in FIGS. 42A and 42B.
Each program output
visualization consists of 3 plots: the top plot is the input ECG signal, the
middle plot is the Springer
Segmentation output, and the bottom plot is the program outputs given the
input ECG. The goal is to maximize
AUC, so we look for separation in output value whenever a pattern (S 1/S2) is
met. FIGS. 32A and 32B illustrate
outputs of programs on segmentation task.
Example 5: Classification examples using vibroacoustic data
[545] Vibroacoustic data from a test subject was acquired using a sensing
device according to a variant of the
present technology, such as the sensing device of FIG. 4, and used to assess a
segmentation algorithm and train
and test a model for predicting fatigue states based on vibroacoustic data.
The sensing device included the ECG
sensor module which was used to determine the heart beat of the subject, and
to use the heart beat to segment
the detected vibracoustic data.
Clinical data collection
[546] Multiple episode data was collected from a single individual over
monitoring before and after five
workout sessions over a 7-month period, while in two different functional
states: "at rest" and "stressed,"
achieved by aerobic exercise. Exertion was self-reported as "high" during the
aerobic activity, which included
running distances between 3 and 5 miles on each of five workout sessions. "At
rest" data were collected prior
to the workout. "Stressed/Fatigued" data were collected about 20 minutes
following aerobic activity cessation
during the recovery phase. Data was recorded around the intersections of the
2nd to 3rd intercostal spaces and
the left midclavicular line. This position was chosen based on its proximity
to the heart.
Table 5: Exercise activity included in analysis
Date Time Duration
(workout
start)
5/31/2019 4:30 PM 3.5 miles
6/04/2019 6:50 AM 2.9 miles
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6/07/2019 5:50 AM 3.0 miles
6/11/2019 5:40 AM 3.0 miles
1/03/2020 4:30 PM 5.0 miles
[547] The data from the first four data collection dates shown in Table 5 was
chosen to serve as the training
data, while the data from January 2020 was selected as the test data. This was
done intentionally, because the
last data collection session was about seven months after the others, and
anticipated as helpful to illustrate some
measure of vibroacoustic data stationarity over time.
Signal processing
[548] Vibroacoustic data was decimated from a 48 kHz sampling frequency to a 1
kHz sampling frequency
using an 8th order Chebyshev type I anti-aliasing filter, after which the data
was split into three datasets: (i) full
bandwidth (no additional filtering), (ii) HP-filtered (6th order high-pass
Butterworth filter with critical
frequency of 20 Hz), and (iii) LP-filtered (6th order high-pass Butterworth
filter with critical frequency of 20
Hz). Some overlap in the three datasets existed due to the non-ideal frequency
cutoffs for the filters (higher
filter orders would help alleviate this issue).
Vibroacoustic data segmentation
[549] Fixed-duration heart sounds, rather than the full vibroacoustic records
or individual heart cycles, were
chosen as inputs to the classifiers. One reason for this is that the fatigued
state has a higher heart rate (HR) and
lower heart rate variability (HRV) than the non-fatigued state. The higher HR
would have resulted in different
length heart cycle input data for the models, which would have been quite easy
to classify. If the full heart cycles
were rcsampled to homogenize the data lengths, the intra-sample time spacing,
and therefore the absolute
measures of frequencies, would be lost. Another reason for using fixed-
duration heart sounds as inputs to the
classifiers is that the relative location of the S2 sound is affected by HR,
providing another feature that would
make the classification almost trivial. Additionally, Si and S2 heart sounds
can be extracted with assumed
uniform durations using the Springer Segmentation Algorithm. For this
analysis, the first heart sound Si was
chosen, with a fixed duration of 100 milliseconds.
Classification models
[550] Three "deep learning- models with identical structures were fitted to
the full bandwidth, HP-filtered,
and LP-filtered Si data segments. The identical model structure chosen was a
neural network composed of two
convolutional layers followed by a dense layer. To help avoid overfitting,
dropout layers were also included.
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The full bandwidth, HP-filtered, and LP-filtered models were then tested with
full bandwidth, HP-filtered, and
LP-filtered Si segments from the test data, respectively (FIG. 36A).
[551[ Metrics were calculated from the test data and include loss (binary
cross-entropy), accuracy, sensitivity,
specificity, false positive rate, true positive rate, and AUC. Since model
fitting using the chosen tools is
stochastic, the model fitting and metric calculations were repeated 30 times.
All data processing and modeling
were done using Python and Keras/Tensorflow.
Results: Vibroacous tic data segmentation
[552] FIG. 36B shows an example of extracted Si heart sounds (including
filtering) from a vibroacoustic
waveform. Visual inspection suggested that the segmentation algorithm
performed as expected. Table 6 shows
the number of 51 segments extracted from each pre/post-workout session. As
expected, the number of Si
segments is quite small, which is the reason for the simple model structure
chosen in this analysis.
Table 6: Number of Si segments extracted from data records
Date Si Si segments,
segments, not fatigued/post-
fatigued/pre- workout (n)
workout (n)
5/31/2019 73 97
6/04/2019 124 175
6/07/2019 122 145
/11/2019 125 138
1/03/2020 125 180
[553] The total number of S1 segments pre/post-workout were randomly balanced
for both the training and
test sets and fixed for all subsequent model training/testing. There were a
total of 444 pairs (pre- and post-
workout Si segments, 888 total) of training data and 125 pairs (pre- and post-
workout Si segments, 250 total)
of test data.
Results: Model performance
[554] Mean metrics from the 30 model fits are shown in Table 7, which shows
high performance of the models
trained with data containing low frequencies.
Table 7: Mean metrics from 30 model fits calculated from test data set. It is
assumed that
"positive"=post-workout in these calculations.
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HP Full LP
model bandwidth model
model
Accuracy 0.503 0.706 0.823
Sensitivity 0.951 0.978 0.943
Specificity 0.055 0.434 0.703
AUC 0.705 0.934 0.941
[555] Similarly, graphical representations of model performance also show the
value of low frequencies. For
example, the ROC curve for the model fit closest (in the 2-norm sense) to the
mean AUC is shown in FIG. 36C.
[556] These results suggest that, for a given and fixed model structure, novel
low frequency vibroacoustic
data may generate more robust model predictions than higher frequency acoustic
data. This is supported by both
the models based on full-bandwidth and LP-filtered data outperforming the
model based on HP-filtered data in
most metrics listed in Table 7.
EXAMPLE 6 -design of voice coil sensor module
[557] Developers goal was to develop a novel voice coil-based sensor module
for human/animal physical
monitoring. Among the optimization parameters were:
= magnet size, shape and material for strong and uniform magnetic field;
= coil material, length, number of windings and number of layers for
maximum length while minimizing
resistance and weight;
= lightweight support structure e.g. flexure-based structure, or flexible
diaphragm holding windings;
= overall dimensions constrained because of the need to incorporate the
sensor module into lightweight
small wearable device or handheld device.
[558] Performance of candidate transducer designs was evaluated based on three
output variables: force
responsivity, receiving sensitivity, and frequency-response efficiency.
Force re sponsivity
[559] The actuating abilities of the transducers were evaluated by measuring
the force exerted by the
transducers as a function of frequency. A Dynamic Signal Analyzer (DSA) was
used to step through source
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frequencies in the range of 0.01 to 160,000 Hz and to calculate a frequency
response spectrum of the signal
from the force transducer measured for each source frequency.
Receiving sensitivity
[560] The DSA was used to step through a range of source frequencies and to
calculate a frequency response
spectrum of the receive signal from the test transducer, measured at each
source frequency.
Reciprocal concrete transmission efficiency
[561] To verify that it is indeed possible to collect and transmit infrasound
through to ultrasound mechano-
acoustic waves passively harvested from the human body using these test voice
coil transducers, measurements
were made from patients and on a physiologic manikin. Two identical
transducers were used for this experiment:
one for transmission and one for reception. The reciprocity in the
transmissions was investigated by repeating
each measurement with reversed transducer configuration, so that the
transducer that previously transmitted
acted as receiver and vice versa.
[562] The DSA source was used, via the power amplifier, to apply a sinusoidal
signal with stepped frequency
to the transducer that acted as a transmitter. The output of the power
amplifier was fed into Ch. 1 of the DSA
for reference. The output from the receiving transducer was fed into the DSA
(Ch. 2). By dividing Ch. 2 with
Ch. 1 the voltage transfer function was established. By then dividing by the
transducer complex impedance the
transmission efficiency was determined.
Table 8. Voice coil parameter ranges in ccrtain variants of the present
technology.
Parameter Present technology 1 Present technology 2
Conventional voice coil
Impedance 150 ohms w2% 150 ohms w2% 4 ohms
DC Resistance (Re) 150 ohms w2.% 150 ohms 2% 4.3 ohms
Voice Coil Inductance (Le) 7.5 mH at 1 kHz / 2.5 8.46 mH at 1 kHz / 2.7 0.27
mH at lkHz / 0.12
mH at 10 kHz mH at 10 kHz mH at 10
kHz
Coil Resonant Frequency 80-170Hz 90 Hz 2% 224 Hz
(Fs)
Total Q (Qts) inverse of 0.25 to 0.65 0.85-0.90 0.78
damping (depending on exciter)
100 mg to 100g
depending on no.
windings)
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Moving Mass (Mms) 100 mg to 100g 1.15g 1.61g
(depends on number of
windings)
For test exciters
specifically 1.15g
Mechanical Compliance of 0.4 10 3.2 mm/N 3.2 mm/N 0.338 mm/N
Suspension (Cms) (inverse
of suspension)
BL Product (BL) 18.5 N/Amp (same as 18.5 Tm 3.63 Tm
Tm)
Voice Coil Diameter 25 mm 25 mm 25mm
RMS Power Handling 2 W 2 W 24 watts
Wire Diameter 0.05 mm 0.05 mm 0.15
(including
insulation)
Number of windings 208 208 46
Number of Layers 4 4 2
Magnet Size 24 mm x 3.5 mm 24 mm x 3.5 mm 24 mm x 3.5
mm
Overall Outside Diameter 50.5 mm (5x5x0.1 to 60 mm and 65 mm (oval 50.5
50x50x10) shaped)
Overall Depth 20.5 mm 27 mm 20.5
Inductance! moving mass at least 6.52 mH per gram 7.36 mH per gram at
10.17 mH per gram at 1
ratio at 1 kHz kHz kHz
Mechanical compliance / at least 0.348 mm/N per 2.78 mm/N per gram
moving mass ratio gram 0.21 mm/N
per gram
BL product / moving mass at least 16 N/Amp per 16.09 N/Amp per gram
ratio gram 2.25 N/Amp
per gram
(BL x mechanical 51.48 [T*m^2 / (N * g)]
compliance)! moving mass 51.48 [T*m^2 / (N * g)] 0.76 [T*m^2
/ (N * g)]
Wright Parameters
K(r) 26-27 23 0.275
X(r) 0.175-0.185 0.194 0.286
K(i) 0.00709-0.01118 0.032 0.00045
X(i) 0.827-0.866 0.739 0.843
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[563] Parameters that may lead to high sensitivity and frequency range (higher
= better):
Voice Coil inductance, Total Q, mechanical compliance, BL product, number of
windings ( resulting in higher
BL and Inductance).
[564] Parameters that may lead to high sensitivity and frequency range (lower=
better):
Moving mass.
[565] The product of BL product and mechanical compliance may represent high
signal sensitivity amplified
by good mechanical compliance.
[566] The product of BL product and mechanical compliance) / mass may
represent high signal sensitivity
amplified by good mechanical compliance, further amplified by low moving mass.
[567] By way of background, and to support the abovedescribed experimental
approach, the following was
considered. An electrodynamic sensoriactuator is a reversible voice coil
transducer which has capability to
provide input vibrational energy to a host mechanical structure. It can be
regarded as a two-port system, including
electromechanical coupling through two pairs of dual variables: the voltage e
and current i for the electrical side,
and the transverse force F and velocity vs for the mechanical side.
[568] Using phasors to represent the complex amplitude (magnitude and phase)
of sinusoidal functions of
time, the characteristic equations of the sensoriactuator when attached to a
host mechanical structure can be
written as:
B1 i = .ma v a ¨Z v
ins = s (7)
e = Zei¨e (8)
where v a is the velocity of the moving rnas s, Es is the transverse velocity
atthe base ofthe actuator, e is the input
voltage applied to the electrical terminals, i is the current circulating in
the coil, Lõ, = joiAla+Ra +Kaj 0) is
the mechanical impedance of the inertial exciter, Ze =Re +joiLe is the blocked
electrical impedance of the
transducer, and = R, +Ka/Jo) is the impedance of the spring-dashpot
mounting system. Equations 7-8)
contain terms of electrodynamic coupling; Enag= B/i is the force caused by the
interaction of the magnetic
field and the moving free charges (current), and e = B 1(ya Is) is the back
electromotive force (voltage)
induced within the voice coil during motion. It is also assumed that all the
forces acting on the actuator are
small enough so that the displacements remain proportional to applied forces
(small-signal assumptions).
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[5691 The input impedance of the sensoriactuator is the complex ratio of the
voltage to the current in the
electrical circuit of the transducer. It determines the electrical impedance
(in n) "seen" by any equipment such
as electronic drive source, electrical network, etc., connected across its
input terminals. When attached to a pure
mass, the closed form expression of the input impedance of the sensoriactuator
can be obtained by combining
Eq. (7) and (8), as
(9)
ma
[570] As can be seen in Eq. (9), Z,, contains all the electromechanical
effects that are operating, including all
resistances and reactances of the actuator impedance. As discussed in the
following, measuring the input
impedance of the actuator enables certain key parameters such as the dc
resistance and natural frequency to be
evaluated.
[571] Substituting now Eq. (7) in Eq. (8), the transverse velocity at the base
of the actuator be expressed as:
(10)
__________________ (e Zed +
jwMaBl jwMa
[572] Equation (10) clearly shows that the transvers e velocity of the
structure where the actuator is located can
be estimated from the driving current and the voltage sensed at its input
terminals.
EXAMPLE 7¨ Preliminary detection of COVID-19 infection
[573] As seen in FIG. 45, in a preliminary study, Developers identified that
subjects with certain target
conditions have a biosignature distinguishable from those of healthy subjects.
For example, Developers have
demonstrated that vibroacoustic biosignatures can be used to determine
infection with Covid-19. Differences
were observed in the vibroacoustic biosignatures of Covid-19 symptomatic and
asymptomatic subjects
compared to those of healthy control subjects. These findings can be
reasonably extrapolated to other respiratory
conditions, as well as other viral and bacterial conditions and the like. The
vibroacoustic signal detection was
performed using the sensing device 400 as described with respect to FIG. 4.
EXAMPLE 8 ¨Clinical trial for COV1D-19 infection
[574] Detection of COVTD-19 infection in subjects remains challenging,
particularly using non-invasive and
fast techniques. As previously mentioned, current COVID-19 screening
approaches are either simple and fast
but lack accuracy (e.g., temperature checks), or are accurate but neither
simple nor fast (e.g., antibody
screening). The gold standard for COVID-19 diagnosis is real-time reverse-
transcriptase polymerase chain
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reaction (RT-qPCR), however, many counties and states have limited RT-PCR
testing to individuals with overt
symptoms, and there are often significant delays between testing and result
reporting - providing opportunity
for unknown infectious spread. In addition to the 'classic' COVID-19 illness,
COVID-19-associated
multisystem inflammatory syndrome in children (MIS-C) has recently emerged as
a complicated and potentially
fatal outcome resulting in school and workplace closures. While COVID-19 is
primarily characterized by
acutely compromised lung and respiratory function with symptoms peaking 7-10
days following infection, MIS-
C affects multiple organ systems 2-4 weeks post-illness, and can include
gastrointestinal distress, kidney injury,
neurologic symptoms, and impaired heart function. With features that often
resemble toxic shock syndrome,
MIS-C can occur in children without prior symptoms of COVID-19 and can have a
variable clinical presentation
depending on affected organ systems. These attributes make MIS-C difficult to
predict, and challenging to
diagnose. Convenient and reliable screening approaches to identify those with
likely infection is critical to
limiting outbreaks, while understanding development of worsening illness is
essential for triage and mortality
reduction.
[575] In the present Pilot study, the study participants include 15 patients
with confirmed COVID-19 with
pulmonary symptoms ("case patients-) matched with 15 hospitalized control
inpatients without COVID-19 with
non-pulmonary diagnoses or symptoms ("control patients"). Study participant
matching attempted to make sure
that the control group is sufficiently similar to the cases group, with
respects to variables such as age, sex, BMI,
smoking status, etc. The methodology adopted in this Pilot Study data analysis
addresses the deficiencies of
modern classification techniques by exposing the structure of case-control
matching to the data analysis
methods. The approach in this Example models not only the 'horizontal'
classification into cases and controls,
but also the "vertical" transformations related to the matching variables
(age, sex, BM1, etc.), and so acquires
additional knowledge about the problem, which in turn lowers the risk of
overfitting and facilitates learning
from small samples.
[576] Signal detection using variants of the present system, such as the
sending device 400, was performed
on the Case subjects and the Control Subjects. Readings were taken from each
subject when the subject was in
different body positions (neutral sit, neutral upright stand, supine, left
lateral decubitus position (LLDP). Whilst
in each position, readings were taken whilst the subjects were performing
different activities (handgrip and
cough, and vocalizations that reveal pulmonary- consolidation). Each set of
readings was taken by positioning
the sensing device 400 on nine different auscultation positions on the subject
(9-step staircase ladder procedure
starting at the right carotid). The so obtained data was segmented into 10, 5,
3 heart cycles, and further split by
frequency range (<20Hz (infrasound), 20-20,000Hz (audible sound), and
>20,000Hz (ultrasound)) to expand
the paired data structure and facilitate
classification/clustering/individuation. The sensing device 400 was
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positioned over clothing. The sensing device 400 was also arranged to collect
additional sensor data such as
IMU data, contextual data, heart beat.
[577] The sensor data for this study illustrates the use of high-dimensional
data where the number of variables
is close to or moderately higher than the number of subjects. The approach
also helps with low-dimensional
data with appropriate variable selection. Since the framework seamlessly
incorporates variable selection with
fitting the prediction model for the matched design, variable selections can
be evaluated, ignoring and
considering the matched design to quantify impact on the prediction model
performance. As a matter of fact,
the approach goes beyond traditional feature selection and ventures into
feature construction, autonomously
synthesizing 'derivative descriptors' from the available variables.
[578] With reference to FIG. 46, in terms of sensor data / signal processing,
the vibroacoustic signal was first
divided into 11-term segments (windows) and then, for each segment, the t-term
processing stage was carried out.
The n-term segment was p ms long with q ms overlap between adjacent frames
(the frame rate is r frames per
second), where p,q and rare optimized as part of the algorithm development. At
a next step, the feature sequence,
F, which was been extracted from a n-term segment, was used for computing
feature statistics, (e.g.
volume/loudness, bandwidth, pitch, silence/pauses, and single frequency sound
markers, global and frame-
based time-domain features, spectral features, energy features, harmonic
features, and perceptual features). The
features underlying the COVID-19 biosignature has V bits, computed from W
subbands covering YL¨Yx Hz
cross-frequency couplets in bark-scale. In the end, each n-term segment is
represented by a set of statistics which
correspond to the respective t-term feature sequences. During n-term
processing, it was assumed that the n-term
segments exhibit homogenous behavior with respect to audio type and it
therefore makes sense to proceed with
the extraction of statistics on a segment basis. In practice, the duration of
n-term windows provides the minimum
time required to make a reliable diagnosis.
[579] Once the t-term feature sequences were generated, feature matrix is
obtained, with vectors that contain
the features and vectors that contain the resulting feature statistics. If,
for example, 23 feature sequences have
been computed on a t-tcrm basis and two n-term statistics arc drawn per
feature (e.g. the mean value and the
standard deviation of the feature), then, the output of the n-term function is
a 46-dimensional matrix.
[580] In some cases, the n-term feature extraction process was employed in
multi time-scales and/or multi-
frequency bands, in order to capture salient features of the broad-band
vibroacoustic signal. For example, in the
context of COVTD-19 classification of cases vs. controls it was sometimes
desirable to extract a single feature
vector as the representative of the class. In such cases, tsholt-term features
were first extracted as described above
and at an intermediary step, tionser-term statistics were computed on a
tionger-term segment basis. At a final stage,
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the tall-term statistics were long-term averaged, in order to provide a single
vector representation of the
biosignature signal.
[581] The general framework for the COV1D-19 biosignature was as follows ¨ a)
sensor data was first
segmented into n-term frames, and b) global and frame-based time-domain
features, spectral features, energy
features, harmonic features, and perceptual features were extracted for each
frame. Then, these features were c)
mapped into and class biosignature that is a compact representation. This
process is repeated ad nauseum to
increase sensitivity and specificity across
classification/clustering/individuation.
[582] Mel-frequency cepstral coefficients (MFCC) or cepstral coefficients (CC)
are widely used for speech
recognition and speaker recognition applications. While both of these provide
a smoothed representation of the
original spectrum of an audio signal, MFCC further considers the non-linear
property of the human hearing
system with respect to different frequencies. Given the success of MFCC in the
speech domain, it is also every
popular in other audio signal processing, for example, audio/music
classification, audio content segmentation,
speaker segmentation, language identification, etc. For audio-based video copy
detection, MFCC, equalized
MFCC (the mean of cepstral features in each audio is subtracted to generate
zero mean features), and
Gaussianized MFCC (non-linear transformation is applied to the cepstrum such
that the features have a Gaussian
distribution) were adopted in. MFCC has 13 dimensions, and when the first
order temporal derivative of MFCC
is considered, the total feature dimension becomes 26. The difference between
any two MFCC feature vectors
can be measured by their Euclidean Distance. Other acoustic features that can
be used for audio content
identification include Fourier Coefficients, Linear Predictive Coding (LPC)
coefficients, Modulated Complex
Lapped Transform (MCLT), etc.
[583] The method of determining the COVID-19 biosignature featured the
following steps:
1. Pull frames in the file (p ms frames shifted by q ms each time)
2. For each frame: Extract the data, do optional dithering, pre-emphasis and
dc offset removal, and
multiply it by a windowing function (e.g. Hamming)
3. Determine frame energy and perform stateless frame by frame energy max-
normalization. The
spectrogram, computed for the input audio by short-time Fourier transform,
represents the vibroacoustic
energy at certain (time, frequency) coordinate. Peaks, the time-frequency
points whose energy is the
local maximum in a region centered around the point, are selected to construct
a constellation map. For
an anchor point in the constellation map, a target zone is constructed in the
constellation map based on
its time and frequency. The anchor point and any point in the target zone form
a pair, and their
frequencies and time difference are used to create a 0-bit unsigned integer
(biosignature). Once
identified the bisosignaturcs and accompanying covariates are bootstrap
recycled to quantify
reproducibility, even in the presence of noise and compression]
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4. Perform FFT and compute the power spectrum. [Alternatively, short-time
Fourier transform (STFT),
and then converted into P bands in vibe-scale. Spectral salient points can
then be selected, which are
the local spectral peaks in time and/or frequency domains. The average energy
values of all regions are
computed and a fixed length binary descriptor is constructed by comparing the
energy of a selected pair
of regions. This local binary descriptor is used as vibroacoustic biosignature
for indexing and retrieval]
5. Compute the energy in each vibe bin; these are e.g. ç triangular
overlapping bins whose centers are
equally spaced in the vibe-frequency domain
6. Compute the log of the energies and take the cosine transform, keeping
as many coefficients as specified
7. Perform cepstral liftering and piecewise linear mapping of the interval
[Y1. low-freq, YH high-freq] to
[YL low-freq, YH high-freq].
8. Perform domain adaptive feature extraction using domain specific languages
for biosignature
identification.
[584] The lower and upper cutoff of the frequency range covered by the
triangular vibe bins are controlled by
the options YL¨low-freq and YH¨high-freq.
[585] Low resolution images were created from the sensor data. Self-Organizing
Maps (SOMs) provide a
useful approach to vibroacoustic data feature visualization. They are capable
of generating 2D quantized
(discretized) representations of an initial vibroacoustic data feature space.
SOMs are neural networks trained in
an unsupervised mode in order to produce the desired data organizing map. An
important difference among
SOMs and typical neural networks is that each node (neuron) of a SOM has a
specific position in a defined
topology of nodes. In other words, SOMs implement a projection of the initial
high-dimensional feature space
to a lower-dimensional grid of nodes (neurons). Compact fingerprints were
created from the sensor data (audio
spectrogram), which is treated as an image. The image could be extended to
include other data, if it makes sense
at this location. Specifically, a spectrogram was computed for the input
vibroacoustic signal, and was
decomposed using the multi-resolution Haar wavelets. To reduce the effect of
noise, only the top Haar wavelets
according to their magnitudes were kept. Instead of keeping the actual values
of the wavelet coefficients, their
signs were used to save memory usage. Then Min Hash technique was applied on
this binary vector multiple
times (fi times) to create a set of p integers as the audio fingerprint.
Basically, the MM Hash method permutes
the binary vector positions in a pseudorandom order, and measures the first
position that I occurs.
The fi dimension fingerprint can be further compressed with the Locality
Sensitive Hashing (LSH) to reduce
the number of comparisons in retrieval stage.
[586] Example data extracts of the collected vibroacoustic sensor data from
the Subject and Control cases are
illustrated in FIGS. 47-51. The data extracts were extracted by: (1) using
position flags to extract a middle 25
secs of VI data for each {body position} x {auscultation point}; (2) within
this 25 sec segment, the 10 sec
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segment that has the smallest max(VI)-min(VI) value was found (this was to
avoid segments where the device
is moved against clothing, etc. to avoid disturbances); and (the 10 sec VI
segment was normalized by subtracting
its mean and dividing by its standard deviation.
[587] In FIG. 47, sensor data extracts (vibroacoustic only) of three Subject
Cases and three Control Cases are
shown, in which the data was collected while the subjects were in the supine
position, and the data was collected
from the right 2nd ICS of the subjects' body.
[588] FIG. 48 shows sensor data extracts from three Subject cases (S002, S003,
S004), in a first visit and a
second visit, in which the vibroacoustic test data was collected while the
subjects were in the supine position,
and the data was collected from the right 2nd ICS of the subjects' body.
[589] FIG. 49 shows sensor data extracts (vibroacoustic only) of fifteen
Subject Cases and three Control Cases
taken while the patients were in the supine position and from a 2nd ICS
location on their bodies. The blank
rectangles indicate when the subjects were not able to assume the given
position.
[590] FIG. 50 shows sensor data extracts (vibroacoustic only) of two Subject
Cases and three Control Cases
taken while the patients were in the supine position, and from different
locations on their bodies (carotid, right
clavicle, left clavicle, left 2nd ICS, right 2nd ICS, right 4111 ICS, left 4th
ICS. left 6111
ICS, right 6th ICS).
[591] FIG. 51 shows sensor data extracts (vibroacoustic only) of two Subject
Cases and three Control Cases
taken while the patients were in different positions and performing different
actions (sitting, standing, supine,
left lateral, cough and hand squeeze, speech) with the sensing device position
on the right 2nd ICS location on
their bodies.
[592] These plots show some clear differences associated with respiration
based on the detected vibroacoustic
sensor data. For the COVID-19 patients, one can see frequency envelopes in the
spectrograms associated with
breathing (breathing can be assumed by either looking at the timescales of
these envelopes or by looking at the
low-frequency baseline changes in the VI plots). These envelopes are not
present to the same extent in the
controls. Respiratory vibrational changes consistent with those observed in
the plots above are expected with
COVID-19. During inhalation, inflammatory and other immune responses that
constrict the airways in the upper
respiratory system are expected to elicit more turbulent airflow entering the
lungs. The increased turbulence
will be associated with higher-frequency respiratory sounds. Additionally, in
COVID-19 patients with fluid
accumulation and inflammation in the lungs, higher-frequency sounds (e.g.,
rates or pleural friction rub) will be
present.
[593] interestingly, for the COVID-19 patients with a second visit (FIG. 48),
the envelopes seem to get smaller
on the second visit in the sense that the higher frequencies are diminished_
Assuming that "higher frequencies
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<-> pathological" and the patients are recovering while in the hospital, this
highlights the need for diagnosing
early disease.
[594] Biosignature of COV1D-19 was developed using variations of the machine
learning module of the
present technology. As well as the vibroacoustic data, data from
phonocardiograms augmented with
sociodemographic, medical history, and current health characteristics was also
used. Data from healthy
unexposed participants and participants who were exposed but did not develop
infection was also included.
[595] Biosignature development comprised bootstrapping the within-pair
comparisons by splitting the MCC
study data by ¨ a) body position (neutral sit, neutral upright stand, supine,
left lateral decubitus position (LLDP),
handgrip and cough, and vocalizations that reveal pulmonary consolidation), b)
device location on the body in
the 9-step staircase ladder procedure starting at the right carotid, c)
segmentation into 10, 5, 3 heart cycles, and
d) further splitting data into <20Hz (infrasound), 20-20,000Hz (audible
sound), and >20,000Hz (ultrasound) to
expand the paired data structure and facilitate
classification/clustering/individuation.
[596] Independent data sets were used for each of the training, validation,
and testing phases. Concerning the
construction of specific ML models, a portfolio of methods were applied
ranging from statistics and
conventional machine learning through to novel evolutionary models. The latter
allows posing the task of feature
construction from wide-spectrum vibroacoustics as a program synthesis task.
The unique advantage of this
approach is the ability to provide the search algorithm with additional expert
guidance, by supplying it with a
formal grammar and symbolically expressed cardiopulmonary, digital signal
processing and sound engineering
domain-specific language that encapsulates the relevant domain knowledge. This
not only makes the resulting
features transparent (which are expressed, among others, as algebraic
expressions and/or, if/then rules), but also
eases learning from small data, both in 'n-sense' (low number of available
samples/examples) and 't-sense'
(relatively short duration of recordings).
[597] The hybrid numeric-symbolic representation of the present technology
allows to reason formally about
the synthesized descriptors and provide formal guarantees about their
outcomes. The language was designed so
that it embraces the semantics of the functional health data phenotypes. The
domain-specific knowledge
incorporated into this approach ensures that learned relationships are
causally meaningful, thereby greatly aiding
in both the predictive capability of the resulting models and their human
interpretability. These approaches build
generalizable models by combining principled Bayesian inference with a
learning algorithm that respects
relational dependencies in the data. This is in stark contrast to mainstream
machine learning, where training
usually requires large volumes of data (or otherwise the models tend to
overfit) and the models are completely
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opaque (there is little or no insight in the inner workings of the model, and
consequently limited capability to
explain the decisions being made).
[598[ As well as splitting the MCC study into non-overlapping training and
validation datasets, a nested case-
control design was also looked at that includes bootstrapped cases and selects
matched/alternate controls for a
case among in the full continually expanding cohort (risk-set matched case-
control design). This design is
expected to produce a similar result to the training and validation sequential
analysis. As additional data from
planned studies is accumulated, the MCC study will be used as the training
data set without losing statistical
power in the development and the rest of the cohort as the validation data
set. When predicting uncommon
clinical events, limiting false positive prediction (1-specificity) is often
more of interest than limiting false
negative prediction. Then, since all cases are included in the case-control
cohort, only partial validation will be
available based on the fraction of true negative prediction (specificity). In
the nested case-control cohort,
variable selection is conducted and fit a prediction model on those selected
variables. Then, the selection is
validated by comparing the specificity of the fitted prediction model in the
case-control subjects (internal) to
that in the subjects who were not selected as controls within the cohort
(external).
EXAMPLE 9¨ Remote sensing
[599] An example variation of a sensing device of the present technology in a
panel-form, such as the sensing
device illustrated and described in FIG. 31, was evaluated. The sensing device
had a sealed cavity. A subject
was positioned at varying distances from the diaphragm of the panel and
including different barriers between
the subject and the diaphragm in terms of apparel (wearing a sweater, without
a sweater).
[600] FIG. 52 shows vibroacoustic test data collected by the sensing device
when the subject without a
clothing barrier is positioned 12 cm from the diaphragm of the sensing device
(FIG. 52A), the subject without
a clothing barrier is positioned 100 cm from the diaphragm of the sensing
device 100 cm away (FIG. 52B), the
subject wearing a sweater is positioned 12 cm from the diaphragm of the
sensing device (FIG. 52C), and the
subject wearing a sweater is positioned 100 cm from the diaphragm of the
sensing device (FIG. 52D).
[601] It is clear from the figures that systems and sensing devices of the
present technology can detect body
vibrations remotely through air gaps of various distances. Due to attenuation
inherently present in the
propagating sound signals the amplitude is reduced at greater distances, as
most evident in the time domain
signals. However, as evident from the frequency spectra, signals are still
being captured at the larger distance
and can be extracted. In addition, the important lower frequencies are less
attenuated due to near field conditions,
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which allows sensing them from even greater distances. As can also be seen,
the presence of clothing has little
effect on the signal quality.
[602] FIG. 53 shows vibroacoustic test data collected by the sensing device
when the subject wearing a
sweater is positioned 10 cm from a diaphragm of the sensing device and is
facing the diaphragm (FIG. 53A),
the subject wearing a sweater is positioned 10 cm from a diaphragm of the
sensing device and is facing away
from the diaphragm (FIG. 53B), and the subject wearing a sweater is positioned
100 cm from a diaphragm of
the sensing device and is facing the diaphragm. These signals are presented as
time domain signals, and
separated into relevant frequency bandwidths. The top cyan colored signal is
the combined captured signal, the
green signal the infrasound component in the captured signal (<20 Hz), the
yellow signal is the audible
component (>20Hz) and the bottom is a spectrogram. It is evident that
infrasound and audible spectrum are
captured with good signal to noise ratio. Although frequencies in the audible
spectrum are attenuated compared
to a distance of 10 cm, the infrasound components are still captured well.
[603] It is reasonably expected that when openings are provided on the back
cover, the effect on frequency
detected would be affected (i.e. shifted to higher frequencies). Optimization
of the sensing device can therefore
be performed through a combination of analytical and finite element analysis
(FEM) of different extents of
sealing of the cavity and based on a desired frequency detection range in a
high dimensional parameter space.
EXAMPLE 10¨ Vibroacoustic si2nals from animals
[604] FIGS. 55-59 illustrate example snippets of data collected using an
embodiment of the sensing device of
FIGS. 4A-4I from various animals. FIG. 55 shows vibroacoustic data from a
dairy cow before milking (left
hand graphs), during milking (middle graphs) and after milking (right hand
slides). Significant differences are
apparent in the data between the different udder states of the dairy cow
indicating that sensing devices of the
present technology can be used to detect different udder states of an animal.
FIGS. 55 and 56 show vibroacoustic
data from a free-range dairy cow and a red angus beef cattle, respectively,
thereby demonstrating a noticeable
distinction between different types of animals. FIGS. 57, 58 and 59 show
vibroacoustic data from a female
sheep, a male sheep and a male goat, respectively, the data having been
collected by placing the sensing device
on approximately a same anatomical region of each animal. FIG. 58 also depicts
comparative human data.
[605] It will be clear that sensing devices of different form factors can be
used for such animal use, such as
livestock gate form factor (e.g. FIG. 60), hand-held form factor (e.g. FIG. 4)
and panel form (e.g. FIG. 31)
[606] Embodiments of the devices, methods and systems of the present
technology can be used to
monitor/predict/maintain health status as well as illness, such as one or more
of: (i) udder health to maximize
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milk production, (ii) rumen fermentation to maintain body condition; (iii)
energy balance for pre-partum health,
estrus detection, pregnancy and lactation, (iv) infection, (v) other disease
states.
[607[ In certain embodiments, quantification of the levels of fermentation in
ruminants in response to changes
in neutral detergent fiber (NDF) in the diet can be determined. For example,
substituting wheat for corn may
cause bloating in ruminant animals. The level of bloating may be detected
through changes in the vibroacoustic
signatures of the animals and the diet may be adjusted accordingly to prevent
ill effects and to optimize growth
and quality of the animal products derived from the animal.
[608] In other aspects, the level of methane emission from burping and
flatulence may also be quantified and
the diet and supplement mix provided to the animal may be adjusted to minimize
such emissions and to enhance
animal growth and the quality of animal products derived from such treated
animals.
[609] The epidemics and pandemics of a few infectious diseases during the past
couple of decades have
accentuated the significance of emerging infectious diseases (EIDs) due to
their influence on public health.
Although Asia region has been identified as the epicentre of many EIDs and
upcoming infections, several new
pathogens have also emerged in the past in other parts of the world.
Furthermore, the emergence of new viral
diseases/infections, such as Rift Valley fever, West Nile fever, SARS
coronavinis, Hendra virus, avian influenza
A (H5N1), Nipah virus, Zika virus and swine influenza A (H1N1) virus, from
time to time is a glaring example
threatening adversely both animal and public health globally. Infectious
diseases are dynamic and concerning
due to their epidemiology and aetiological agents, which is manifested within
a host, pathogen and environment
continuum involving domestic animals, wildlife, and human populations. High-
impact animal diseases such as
foot-and-mouth disease, peste des petits ruminants, classical or African swine
fevers, while not directly affecting
human health, do affect food and nutrition security and livestock production
and trade. The complex relationship
among host populations and other environmental factors creates conditions for
the emergence of diseases. The
factors driving the emergence of different emerging infectious disease (EID)
interfaces include global travel,
urbanisation and biomedical manipulations for human EiDs; agricultural
intensification for domestic animal
EIDs: translocation for wildlife EIDs; human encroachment, ex situ contact and
ecological manipulation for
wildlife¨human EiDs; encroachment, new introductions and 'spill-over' and '
spill-back '; and technology and
industry for domestic animal¨human EIDs. Globalization, land encroachment and
climate change contribute to
outbreaks of such animal diseases ¨ some transmissible to humans ¨ as
brucellosis, bovine tuberculosis, parasitic
illnesses, anthrax, bovine spongiform encephalopathy (BSE) and certain strains
of influenza viruses.
[610] The concepts of sanitary and phytosanitary (SPS) measures and
biosecurity have gained recognition
globally in almost all the realms of human activities, including livestock
health and production management.
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[611] Cross-facility, cross-farm and transboundary animal diseases are highly
contagious epidemic diseases
that can spread extremely rapidly, irrespective of national borders. They
cause high rates of death and disease
in animals, thereby having serious socio-economic and sometimes public health
consequences while
constituting a constant threat to the livelihoods of livestock farmers. Animal
diseases have potential to reduce:
quantity and quality of food, such as meat and milk; livestock products:
hides, skins, fibres; andanimal power:
traction, transport.
[612] Reproductive events have to be precisely monitored to improve both the
management and the economic
performance of cattle herds. Estrus and calving are the most sensitive steps:
they require time for their detection
and once detected, crucial decisions, including insemination and human
intervention for newborn delivery, have
to be made. There is evidence that the sensitivity of estrus detection by
visual observation (3 periods of 20
minutes each, every day) of behavioral signs is limited (50-60%). Furthermore,
the visual detection method is
made more challenging by the short duration and low intensity of estrus signs
in modern dairy cows, the
increasing herd sizes and the limited availability of labor time per cow.
These two last factors have also probably
contributed to the increase in the prevalence of dystocia and stillbirths in
dairy cattle. In Holstein dairy cows in
the USA, the proportion of calvings with a calf born dead at term or dying 24
h after birth is high, around 8%,
and the rate of calvings considered dy-stocic reaches almost 14%.
[613] The goal of every dairy feeding program is to develop a low cost diet
that meets the nutritional
requirements of cows while optimizing milk production and cow health. In most
conventional herds, this is
accomplished by feeding a totally mixed ration (TMR) where all the ingredients
are mixed together and
delivered to the cow. For robotic milking system (RMS) herds, a partially
mixed ration (PMR) containing all
the forage and some of the concentrate is offered in the feed bunk. An
additional amount of concentrate is fed
through the RMS milking station; this amount varies according to the cow's
stage of lactation.
[614] Feed that is offered pelleted through an RMS is the major motivating
factor to attract cows to
consistently visit the milking station. However, cow's attendance to the
milking station is not only dependent
on the PMR and pellets offered in the RMS, but also on feeding management. cow
comfort, cow health, and
social interactions among cows. Dairy cow nutritionist suggest that quality of
the pellet offered in the milking
station and consistent mixing of the PMR are the two biggest feeding factors
contributing to RMS success.,
specifically, feeding a high quality pellet (hard pellet with few fines made
from palatable ingredients) increased
the number of voluntary milkings from 1.72 to 2.06/cow per day compared with
feeding a low quality pellet.
Many producers add that even minor changes in the PMR moisture, consistency of
the mix (i.e., long hay that
is difficult to process to a consistent length), and changes in forage quality
affected visits. If forage moisture
changes and rations are not adjusted promptly, visits may drop. The drop in
visits will result in a decrease in
milk production and an increase in the number of fetch cows. The increase in
fetch cows may disrupt other cow
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behaviors, resulting in even bigger decreases in visits and milk production,
leading to a downward spiral that
creates much frustration for the producer. It is crucial to have consistent
feeding in order to maintain high
production and minimize the number of fetch cows.
Precision feeding
[615] One potential advantage of RMS is the opportunity to feed each cow
closer to her nutrient requirements
by providing nutrients through a combination of the PMR and milking station
pellet. Even though RMS allow
for feeding more than one feed in the milking station, many producers in our
survey only used one feed. Some
producers are now using more than one feed to better target cows' nutrient
requirements.
Fresh cow management
[616] Most AMS facilities do not have a separate fresh/early lactation group.
Suggestions to consider that
may increase the likelihood that all cows have a successful transition and
high milk production include:
[617] Special observation and monitoring of fresh cows. Fresh cows that are
not feeling well may continue to
consume all the milking station pellet but decrease intake of the PMR. This
can potentially lead to sub-acute
rumen acidosis, digestive upsets, and increase the risk for other diseases.
[618] Rumination and activity on all fresh cows should be observed daily. The
RMS software creates a daily
list of cows that are not meeting rumination and activity goals compared to
herd mates. If these metrics are
deteriorating, producers need to intervene rapidly and consider making
adjustments to the milking station feed
offered.
Feeding consistency
[619] Cows like consistency. This is even more important in an RMS herd.
Farmcrs that achieve consistently
high milk production have the following attributes: (i) Consistent PMR (PMR is
adjusted to maintain nutrient
concentration as forage DM changes) that is well balanced and composed of high
quality ingredients, (ii)
Consistent mixing and delivery of the PMR, (iii) Consistent feed push ups, and
(iv) Consistent, high quality
RMS milking station pellet
[620] In both the calving and feeding contexts, sensors, i.e. devices
measuring a physiological or behavioral
parameter of individual cows and enabling automated, on-farm detection of its
changes, are potent tools for
estrus and calving management in the field. The present technology: 1)
provides a state-of-the art solution sensor
platform to detect estrus and calving time; 2) positively impacts economic
issues related to connected devices
for the management of milk reproduction; 3) proposes a completely novel data-
driven perspective for device-
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driven intervention for the milk industry superceding sensors measuring a
single physiological parameter on
animals but with no automated data transmission, such as thermal cameras,
estrus patches or blood assays.
Beef Cattle Operations
[621] Systems of commercial beef cattle production may be divided into three
general categories: (1) the cow-
calf segment which produces weaned feeder calves for further grazing and/or
feeding, (2) the backgrounding or
stocker phase of production in which body weight is added to recently weaned
calves, resulting in feedlot-ready
yearlings and (3) the finishing phase of production in which cattle are
fattened for slaughter. Subsequently the
math is simple, two important factors that affect the profitability of a cow-
calf enterprise are (1) calf crop
percentage and (2) calf weaning weight. Together, these two factors represent
the reproductive efficiency of a
herd, which is defined as the total number of pounds of calf weaned divided by
the number of cows exposed
during the breeding season.
[622] The failure of cows to become pregnant and the loss of calves at or
shortly after parturition are the
leading causes of low calf crop percentages. Proper nutrition during late
gestation and during the early
postpartum period has a tremendous impact on conception and pregnancy rates of
cows. Likewise, close
observation and timely intervention and management can greatly reduce the
number of calves lost during the
calving season.
[623] Cow-calf producers strive for at least a 90 percent calf crop, and an
emphasis should be placed on cows
delivering a live calf every 12 months. Cows that calve at intervals greater
than 12 months are usually not
profitable. Feeder calves that typically bring a premium price at cattle
auctions are medium- to large-framed,
#1 muscled, crossbred calves. The following types of calves are usually
discounted at the market: light-muscled
calves with poor structure and conformation, calves that are too small (early-
maturing) or too large
(late-maturing), calves with too much flesh, straightbred calves and calves
with horns. lso, steercalves are
usually 10 cents per pound higher than heifer calves and 4 to 6 cents per
pound higher than bull calves.
[624] The ideal time of year for calving season in any given cow-calf
operation depends on the forage and/or
feed supply, available labor and the intended marketing dates. More important
than the time of calving season
is a controlled, scheduled calving season (60 to 90 days), as opposed to a
year-round calving season. The present
technology presents a commercial beef production system with which a
controlled, scheduled calving season
can be achieved, (1) herd management practices can be performed
simultaneously, (2) use of time and labor can
be more concentrated and efficient, (3) slow- or non-breeding cows can be more
easily identified and (4) a more
uniform calf crop can be produced.
Late winter or spring calving for marketing in the fall
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[625] Late winter calving fits a slack labor period on most farms, and this
system makes use of abundant
summer pasture. Cows are on pasture during the breeding season, thus forages
are heavily utilized. Also, in this
system most cows are non-lactating and thus have their lowest nutritional
requirements in midwinter (a point in
time when feed costs are highest). The demand for calves to graze winter
annual pasture is usually strong in the
fall, but this is also when most feeder calves arc marketed, so calf prices
often weaken during the fall.
Fall Calving
[626] In the fall calving system, calves are born in mid to late fall
(September and October) and marketed
anywhere from late spring to early summer. Calves are old and large enough by
spring and early summer to
utilize grass pastures. Fall calves are typically heavier at weaning than
spring calves, but the greater cost of
feeding a lactating cow (the stage of production where her nutrient
requirements are highest) through the winter
may offset any additional value in the heavier calf Also, fall calving may
interfere with harvesting field crops
on some farms.
[627] The cow-calf and backgrounding system is suitable for some businesses
located in areas well suited for
forage production. Both calf and yearling production utilize forages as the
primary feed. Backgrounding may
be most often defined as the process of growing and developing calves from
weaning weights (450 to 600 lb)
to yearling weights of 700 to 850 lb when the cattle are ready to enter a
feedyard for finishing. As a rule, starting
with lighter, thinner calves is more profitable. Basic principles involved in
backgrounding beef cattle are (1)
adding 200 to 300 pounds of weight per calf, (2) extensive and intensive use
of high-quality forage rather than
the more expensive high-energy feed sources, (3) assembly of calves into more
marketable groups ¨ uniformity
in breeding, gender, weight, and quality and (4) more marketing flexibility
for calf/yearling owners. The
backgrounding phase usually represents a period of efficient, predominantly
lean growth. While most
backgrounding operations utilize grass for feed, some producers develop calves
on harvested forages. For
example, hay or corn silage, when supplemented with the necessary grain and
protein supplement for a balanced
ration, can be fed to enable calves to grow but not fatten. The cost of gain
in this type of program is typically
higher than when the cattle arc allowed to harvest forage; however, when grain
prices arc low, this approach
has some merit. Methane production can also be controlled via feeding.
[628] In contrast to feeder calf and stocker production, finishing cattle for
slaughter requires large amounts
of feed grains and a relatively dry climate. Several variations of production
systems exist for producers. Some
cow-calf producers may choose to sell their heaviest calves at weaning and
background their lighter calves (in
addition to purchased light calves) to heavier weights before selling them.
This option spreads out cash flow
and market risks. Other backgrounding systems besides the more standard fall
to spring method include a
program in which fall-weaned calves are "roughed" through the winter with
minimal inputs and costs, then
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placed on spring and summer pasture where they achieve efficient, compensatory
growth, and then marketed in
the fall. "Pay day" is delayed with this system, but it makes good use of
summer pasture.
[629] Finishing/Feedlot Phase
[630] Cattle are usually finished for slaughter confined in a drylot on full
feed with grain and limited
roughage. Cattle usually go on feed as yearlings weighing 700 to 850 lb,
average gaining 3 lb or more per day
in the feedlot and finish weighing between 1,250 and 1,400 lb. Most cattle
feeders strive for a finish sufficient
to grade U.S. Choice. The feeding period often spans 180 days, although large-
framed, late-maturing cattle
require a longer period and small-framed, early-maturing cattle finish sooner.
Calves that wean at heavy weights
(650 to 750 lb) may be placed directly into the feedlot and finished for
slaughter over a 180- to 200-day period.
The finishing ration can be quantitatively and optimally altered for calves to
include more roughage and less
concentrate early in the feeding period, but working up to high concentrate
feeding during the last 120 days.
The present technology can also provide quantitative guidance for finishing
cattle with grain while they are still
on pasture (i.e., "grain on grass"). This system, when empirically
implemented, does not achieve the high degree
of finish that is attained in the feedlot since roughage consumption is
difficult to control and the cattle expend
energy during movement within the pasture.
The Purebred Herd
[631] Breeding purebred cattle requires a greater capital outlay to get
established and more money to operate
than a commercial herd. Bulls suitable for herd improvement arc often more
costly to buy. The value of the
average cow and the cost to properly raise and develop purebred calves are
greater than in a commercial herd.
Progressive purebred breeders use artificial insemination, EPDs (expected
progeny differences), cow herd
performance records, performance test young bulls, obtain carcass data on
offspring of sires, ultrasound scan
yearling cattle for carcass measures and, in some cases, utilize embryo
transfer and genetic testing. Purebred
herds are important for providing breeding stock to commercial cattle
producers. Purebred cattle production is
a long-term endeavor. Progress in beef cattle improvement through selection
and culling is slow. Many top
purebred breeders have been in business over 20 years. The successful purebred
breeder requires the support
and quantitative guidance of the imPulse System in animal breeding and
nutrition if he/she wants to separate
themselves from the crowd and is dedicated to improving the breed.
imPulse Lambing System
[632] A lambing system concerns when lambing will occur (what season or
months), how often an ewe will
Iamb (annual vs. accelerated), and how and where lambing will occur (shed vs.
pasture). Currently there is no
one "best" lambing system or way to raise lambs. Each producer needs to match
their lambing system to their
personal goals and objectives, resources, and market demand. In addition, the
same farm or ranch may utilize
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different lambing systems for different groups of sheep. All this is achieved
empirically. The present technology
provides for a Lambing System that takes the guesswork out of lambing, optimal
health and optimal growth.
Early vs. Late Lambing
[633] The first decision to make is when to lamb. There are pros and cons
associated with lambing at different
times of the year.
Early Lambing (winter-early spring)
[634] Early lambing systems have several advantages. High on the list is labor
availability. For producers
who farm full-time, the winter may be a time when labor is more readily
available versus the spring when field
work and planting begins. Lambs born early in the year are usually gone by the
time summer comes, which
frees labor for other farming operations.
[635] Another advantage is marketing. Historically, lamb prices have been
highest during the first half of the
year, especially during the Easter season. As a result, lambs born in the
winter are usually sold for higher prices
than those born in the spring. In more recent years, population demographics
have altered the demand for lamb.
Very often, the highest lamb prices of the year occur slightly before the
Muslim Festival of the Sacrifice.
[636] Producers who lamb in the winter can usually carry more ewes on their
pastures, since ewe feed
requirements are only maintenance and lambs are not competing for a possibly
limiting resource, pasture.
[637] If lambing occurs during the winter months, good facilities are needed.
Housing is a big consideration.
Overhead costs are higher with winter lambing. Mastitis, scours, and pneumonia
can be bigger issues with early
lambing because sheep are confined into smaller areas. Early-born lambs are
often creep fed and finished on
concentrate rations. They usually grow faster than those born later in the
year, but their cost of gain is usually
higher. If winter-born lambs are put to pasture, they usually have less
parasite problems compared to lambs born
later in the spring.
Late Lambing (April-May)
[638] Late lambing has many advantages over early lambing and is gaining in
popularity. With spring
lambing, the sheep production cycle is synchronized with the forage production
cycle, allowing for maximum
use of forage resources. Late lambing takes optimal advantage of the spring
flush of grass. For most of the
winter, ewes can be maintained on a maintenance diet of relatively inexpensive
hay or silage.
[639] Spring lambing coincides with the natural breeding and lambing seasons.
With spring lambing, breeding
and lambing periods tend to be more condensed, because ewes and rams are most
fertile during a fall mating
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season. Most ewes conceive during their first heat cycle and almost all will
settle within two heat cycles,
resulting in a short 35-day lambing period.
[640] Another advantage is that ewes usually give birth to larger lamb crops.
Even the breeds noted for out-
of-season lambing will produce a 10 to 20 percent higher lamb crop in the
spring than in the fall. Any breed of
sheep can be raised in a late-lambing season.
[641] The primary benefit to late lambing is reduced production costs: lower
feed costs, less labor, and
overhead. However, late lambing requires better pasture management than early
lambing, since lambs are
usually fed or finished on grass. Internal parasites and predators can be a
significantly larger problem with late
lambing programs.
[642] Early spring and late summer conditions are the worst for parasite
infestations. Highest predation
typically occurs from late spring through September-October, as most predator
species have pups or kits to feed.
It is essential that producers have a plan for dealing with both potential
problems.
Fall Lambing (September-November)
[643] Fall lambing has several advantages over the previous systems. Late-
gestation and lactation coincide
with fall forage growth. Weather conditions are usually ideal for pasture
lambing. There are fewer problems
with parasites and predators with fall lambing. Lambs can usually be sold when
prices are the highest, around
Christmas time.
[644] However, fall lambing is a challenge because conception rates are much
lower than with spring
breeding. Less seasonal breeds arc usually favored in a fall lambing program,
although seasonal breeds can be
primed to lamb in the fall using the ram effect, light control, and/or
hormonal manipulation of the reproductive
cycle.
[645] From an industry standpoint, if more lambs were born in the fall, the
supply of lamb would be more
even distributed, resulting in more stable prices and steadier demand.
Accelerated Lambing
[646] Accelerated lambing is when ewes lamb more frequently than once a year.
The purpose of accelerated
lambing systems is to reduce fixed costs, produce a more uniform supply of
lamb throughout the year, and
increase profitability. There are several accelerated lambing systems.
Twice a year lambing
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[647] The most intensive form of accelerated lambing is twice a year lambing
whereby an ewe would produce
two lamb crops per year. Twice a year lambing has the potential to maximize
lamb production, but may not be
practical under most commercial situations. Twice a year lambing is probably
most common near the equator.
Opportunistic Lambing
[648] Opportunistic lambing is when rams are kept with the flock on a
continuous basis. With the right kind
of ewes, this will result in a lambing interval of less than 12 months. The
problem with opportunistic lambing
is you don't know when lambs are due, so the timing of vaccinations,
deworming, and supplemental feeding is
more difficult. Lambs may also be born forage resources are poor. Keeping the
ram with the flock all the time
also increases the probability of inbreeding, if female progeny are not
removed in a timely fashion.
Three lamb crops in two years
[649] The most common system of accelerated lambing is three lamb crops in two
years, resulting in an
average lambing interval of 8 months or 1.5 lambings per ewe per year. The 3/2
system is usually characterized
by a fixed mating and lambing schedule, such as May mating/October lambing,
January mating/June lambing,
and September mating/February lambing (or slight variations). Another option
is an 8 month overlapping system
in which two groups of ewes lamb every eight months, but there are six lambing
periods per year. To be
successful, accelerated lambing requires the right sheep and careful
management. Ewes and rams must be
capable of breeding year-round. Less seasonal breeds, such as the Dorset,
Merino, Finnsheep, Barbados
Blackbelly, Polypay, Katandin, St. Croix, Romanov, and Rambouillet, arc best
suited to accelerated lambing
systems.
[650] Example 11
[651] The device 400 illustrated in FIG. 4A-4E and including a vibroacoustic
sensor module and bioelectric
sensors was used to measure blood pressure in subjects. For each subject, the
device 400 was held to the skin
for a 30 second auscultation on the neck and other pressure points on the
subject. The vibroacoustic data derived
from the sensor module and the bioelectric data derived from the bioelectric
sensors was processed, according
to embodiments of the present technology, to estimate blood pressure. The
bioelectric data permitted heart cycle
identification which was combined with the vibroacoustic data. The estimated
blood pressure was compared
with blood pressure data obtained from an -off the shelf' electronic blood
pressure cuff. It was found that the
estimated blood pressure using the device 400 was comparable with that
obtained using the electronic blood
pressure cuff.
[652] The foregoing description, for purposes of explanation, used specific
nomenclature to provide a
thorough understanding of the invention. However, it will be apparent to one
skilled in the art that specific
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PCT/US2021/046566
details are not required in order to practice the invention. Thus, the
foregoing descriptions of specific variations
of the invention are presented for purposes of illustration and description.
They are not intended to be exhaustive
or to limit the invention to the precise forms disclosed; obviously, many
modifications and variations are
possible in view of the above teachings. The variations were chosen and
described in order to explain the
principles of the invention and its practical applications, they thereby
enable others skilled in the art to utilize
the invention and various embodiments with various modifications as are suited
to the particular use
contemplated. It is intended that the following claims and their equivalents
define the scope of the invention.
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