NON-INVASIVE MULTIFUNCTIONAL TELEMETRY APPARATUS AND REAL-TIME SYSTEM FOR MONITORING CLINICAL SIGNALS AND HEALTH PARAMETERS

APPAREIL MULTIFONCTIONNEL NON INVASIF DE TELEMESURE ET SYSTEME EN TEMPS REEL DE SURVEILLANCE DE SIGNAUX CLINIQUES ET DE PARAMETRES DE SANTE

English Abstract

Multifunctional wireless apparatus, spectrometry instruments, real-time computational system and device ergonomic forms for live and telemetry monitoring of clinical parameters, health data and other vital medical information. Clinical parameters and medical information include pulse rate, respiratory rate, continuous blood glucose levels, continuous blood pressure levels, pulse rate variability, oxygen saturation ratio, body temperature, bio-electrical activity, sleep patterns, sleep health and other vital bio -signal data. The telemetry apparatus encompasses electrical and optical spectrometer instruments. The spectrometer designs and its accompanying circuit design ensure that device is bio-safe, lightweight, low-powered and portable. The biosensor configuration, comprehensive hardware design, computational process and ergonomic design enables the measurement with more accuracy and efficiency, even in movement artefact prone conditions. The system design also assures that the computational process is real-time, faster and low powered. The wireless apparatus keeps track of the user information on daily diet pattern, fluid and water intake, exercise intensity, other essential health data, and provides necessary alerts. The apparatus yields persona-oriented stress levels and helps the user manage stress through guided practices. The health management system functions based on the user inputs and previously computed parameters. An automated life-support functionality is integrated in the system, that can forecast chronic clinical conditions and health risks like sleep apnea, hypertension, hypoglycemia, hyperglycemia, hypothermia, hyperthermia, CO poisoning, fatigue conditions and more.

French Abstract

La présente invention concerne un appareil multifonctionnel sans fil, des instruments de spectrométrie, un système informatique en temps réel et des formes ergonomiques de dispositif pour la surveillance en direct et en télémétrie de paramètres cliniques, de données de santé et d'autres informations médicales vitales. Les paramètres cliniques et les informations médicales comprennent la fréquence du pouls, la fréquence respiratoire, les taux de glycémie en continu, les niveaux de pression artérielle en continu, la variabilité de la fréquence du pouls, le taux de saturation en oxygène, la température corporelle, l'activité bioélectrique, les phases du sommeil, la santé associée au sommeil et d'autres données de signaux biologiques vitaux. L'appareil de télémesure comprend des instruments spectromètres électriques et optiques. Les conceptions des spectromètres et la conception des circuits connexes associés garantissent que le dispositif est sûr biologiquement, léger, à faible consommation d'énergie et portable. La configuration de biocapteur, la conception de matériel complet, le processus informatique et la conception ergonomique permettent la mesure avec une plus grande précision et une plus grande efficacité, même dans des conditions sujettes à des artefacts de mouvement. La conception du système assure également que le processus informatique est réalisé en temps réel, est plus rapide et à faible consommation d'énergie. L'appareil sans fil garde une trace des informations d'utilisateur sur un modèle de régime alimentaire quotidien, une prise de fluide et d'eau, une intensité d'exercice, d'autres données de santé essentielles, et fournit des alertes nécessaires. L'appareil produit des niveaux de stress personnels et aide l'utilisateur à gérer le stress par l'intermédiaire d'exercices pratiques guidés. Le système de gestion de santé fonctionne sur la base des entrées d'utilisateur et des paramètres calculés précédemment. Une fonctionnalité automatisée de maintien des fonctions vitales est intégrée au système, qui peut prévoir des états cliniques chroniques et des risques de santé tels que l'apnée du sommeil, l'hypertension, l'hypoglycémie, l'hyperglycémie, l'hypothermie, l'hyperthermie, l'empoisonnement au CO, les conditions de fatigue et autres.

Claims

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Claims
The following are claimed:
1. A medical and health monitoring apparatus comprising:
a microprocessor with internal memory;
an optical spectrometer comprising:
at least one or more of a green LED, a red LED, an infrared LED or a near
infrared LED configured to inject a plurality of optical bio-signals;
a photodetector set configured to record a plurality of optical bio-signal
responses of the green LED, the red LED, the infrared LED and the near
infrared LED;
an optical component configured to concentrate and focus the plurality of
optical bio-signal responses on the photodetector set;
a gain programmable bio-LED frontend configured to generate a plurality of
gain adjustable input signals to the green LED, the red LED, the infrared and
the near infrared LED based on a user input or a programmed input;
a switch set configured to shift input signals from the gain programmable bio-
LED frontend to the green LED, the red LED, the infrared and the near
infrared LED as per a control command;
a biosafety circuit configured to control input signals to the green LED, the
red
LED, the infrared LED and near infrared LED within operational safety levels
to inject low powered optical bio-signals;
a series of processing circuits comprising a stage 1 amplifier, a buffer, a
power
notch, a stage 2 amplifier, an ADC and an ambient noise cancellation IC
configured to filter noises in, amplify, stabilize and process the plurality
of
optical bio-signal responses from the photodetector set;
an electrical spectrometer comprising:
at least a first electrical sensor and a fourth electrical sensor configured
to
inject and drain an electrical bio-signal;
at least a second and a third electrical sensor, placed between the first
electrical sensor and the fourth electrical sensor, configured to extract an
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electrical bio-signal response;
a biosafety circuit configured to control input of the electrical bio-signals
within operational safety levels;
a response circuit line comprising an instrumental amplifier, a gain amplifier

circuit, a power notch and a V to I converter configured to process, amplify,
convert and filter the electrical bio-signal response extracted from the
second
electrical sensor and the third electrical sensor;
an impedance analyzer IC configured to:
generate an input signal to inject the electrical bio-signal;
assess and resolve the electrical bio-signal response from the response
circuit line;
a temperature biosensor, placed at a distance away from a heat dissipation
surface,
configured to record an error-free body temperature and a theunal feedback;
a 9/6-axis accelerometer, aligned in a reference direction, configured to
provide a
real-time feedback signals to remove movement errors from the plurality of
optical
bio-signal responses and the electrical bio-signal responses;
a wireless antennae set comprising a bluetooth connection, a wireless local
area
network connection (WLAN) and a global position system (GPS) configured to
wirelessly communicate the plurality of optical bio-signal responses, the
electrical
bio-signal responses, the body temperature and a real-time signals from the
9/6-axis
accelerometer to a network of computational and storage devices; and
a power supply unit comprising a power management unit, a supercapacitor and a

renewable energy harvester and a battery configured to regulate, store and
supply
power.
2. The medical and health monitoring apparatus in Claim 1, wherein the
biosafety
circuit configured to control input signals in the optical spectrometer and
the electrical
spectrometer is an operational amplifier with an input impedance greater than
a
feedback impedance.
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3. The medical and health monitoring apparatus of Claim 1, wherein:
the green LED, the red LED, the infrared LED or the near infrared LED and the
photodetector set are arranged in a blood flow direction; and
the first electrical sensor, the second electrical sensor, the third
electrical sensor and
the fourth electrical sensor electrical sensor are placed in a straight line
and at
equidistant positions along the blood flow direction.
4. The medical and health monitoring apparatus in Claim 1, wherein the power
supply
unit of the medical and health monitoring apparatus further comprises:
a negative voltage converter configured to generate a negative reference
voltage; and
an additional supercapacitor attached to the battery configured to store and
supply
power.
5. The medical and health monitoring apparatus in Claim 1 further comprises a
mobile
communication module configured to wirelessly communicate the plurality of
optical
bio-signal responses, the electrical bio-signal responses, the body
temperature and the
real-time signals from the 9/6-axis accelerometer to the network of
computational and
storage devices.
6. The medical and health monitoring apparatus in Claim 1, further comprising
a
plurality of user interaction components, comprising:
a touch display, a mic, a video camera and a speaker configured:
to provide an access to a plurality of health and medical information;
to provide an access for interaction with a health advisors network for a
clinical and health analysis; and
to operate the medical and health monitoring apparatus.
7. The medical and health monitoring apparatus of Claim 1, wherein the medical
and
health monitoring apparatus is configured to obtain:
a first order noise free bio-signals:
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by applying a delay in real-time to the plurality of optical bio-signal
responses
and the electrical bio-signal responses, and by storing a real-time stable bio-

sensing samples of the plurality of optical bio-signal responses and the
electrical bio-signal responses;
by additionally passing the real-time stable bio-sensing samples through a
digital notch filter to remove power line noise;
by parallelly calibrating the real-time signals of the 9/6-axis accelerometer
to
obtain an angle calibrated accelerometer signals while storing the real-time
stable bio-sensing samples;
by a correlation of the angle calibrated accelerometer signals with the real-
time stable bio-sensing samples to remove movement errors from the plurality
of optical bio-signal responses and the electrical bio-signal responses;
a second order noise free bio-signals:
by analysing the first order noise free bio-signals, or the plurality of
optical
bio-signal responses and the electrical bio-signal responses, through a series
of
banked filters with a dynamic parameter;
a correlation factor:
by correlating the second order noise free bio-signals, or the plurality of
optical bio-signal responses and the electrical bio-signal responses, with a
delay and the angle calibrated accelerometer signals or the real-time signals
of
the 9/6-axis accelerometer;
a third order noise free bio-signals:
by deducing an undistorted energy values of the plurality of optical bio-
signal
responses and the electrical bio-signal responses through correlation of a
matrices of the second order noise free bio-signals and the real-time signals
of
the 9/6-axis accelerometer;
a time intervals dataset:
by analysing an amplitude dataset of the first, the second or the third order
noise free bio-signals for peaks and by storing a time interval between the
peaks of the amplitude dataset;
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an instantaneous heart rate dataset:
by extracting an instantaneous heart rate through an analysis of each of the
time intervals of the time intervals dataset for a per minute value;
an average heart rate:
by extracting a mean of the instantaneous heart rate dataset;
a HR tachogram:
by extracting a plotting of the time intervals dataset;
an autonomous neural activity coefficient of a al:
by extracting a root of a mean of differences between an adjacent values of
the
time intervals of the time intervals dataset;
an autonomous neural activity coefficient of a a2:
by extracting a mean of the time intervals of the time intervals dataset;
an autonomous neural activity coefficient of a a3:
by extracting a root of a mean of a deviation of the time intervals of the
time
intervals dataset from the a2;
an autonomous neural activity coefficients of a a3/ al, a 0-3/ a2 and a a2/
al:
by deriving ratios of the al, the a2 and the a3;
an autonomous neural activity parameters of P I, P2, P3, P4 and P5:
by dividing the third order noise free bio-signals or the plurality of optical
bi o-
signal responses and the electrical bio-signal responses into a high frequency

band signals, a low frequency band signals, a very low frequency band signals
and an ultra low frequency band signals, and followed:
by extracting a power spectrum under the low frequency band signals
to obtain a P1 of the autonomous neural activity parameters;
by extracting a power spectrum under the high frequency band signals
to obtain a P2 of the autonomous neural activity parameters;
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by extracting a ratio of the P1 and the P2 to obtain a P3 of the
autonomous neural activity parameters;
by extracting a power spectrum under the very low frequency band
signals to obtain a P4 of the autonomous neural activity parameters;
by extracting a power spectrum under the ultra low frequency band
signals to obtain a P5 of the autonomous neural activity parameters;
a continuous oxygen saturation:
by extracting a ratio, of an AC to DC ratio, of the optical bio-signal
responses
of the red LED to that of the infrared LED, wherein the optical bio-signals
are
obtained after removal of noise as in the first or the second or the third
order
noise free bio-signals;
an average oxygen saturation:
by extracting a mean of the continuous oxygen saturation;
a respiratory signal:
by an iterative analysis of an extremum of a local maxima and a local minima
of the amplitude dataset of the third order noise free bio-signals, or the
plurality of optical bio-signal responses and the electrical bio-signal
responses,
to decouple into a plurality of decoupled waves and by analysing the plurality

of decoupled waves for a frequency range within a breathing signals frequency
range;
a continuous respiratory rate:
by analysing the respiratory signals for peaks to store a respiratory rate
time
intervals dataset and by analysing the respiratory rate time intervals dataset
for
a per minute value; and
an average respiratory rate:
by extracting an average of the continuous respiratory rate.
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8. The medical and health monitoring apparatus of Claim 7, wherein:
the correlation of the angle calibrated accelerometer signals with the real-
time stable
bio-sensing samples to obtain the first order noise free bio-signals is a
normalized
least mean squaring parameters based adaptive filter; and
the correlation factor is anlayzed to obtain a movement error free bio-signal
responses
of the plurality of optical bio-signal responses and the electrical bio-signal
responses.
9. The medical and health monitoring apparatus of Claim 7, wherein the medical
and
health monitoring apparatus is configured to alternatively obtain the
instantaneous
heart rate dataset, through reduced computational efforts, by analysing a
frequency
dataset extracted by operating a selection matrix on the third order noise
free bio-
signals.
10. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a real-time diastolic blood pressure, a real-time systolic blood pressure and
a real-time
mean arterial blood pressure:
by extracting an extremum datasets of a maxima dataset and a minima dataset
of the optical bio-signal responses;
by correlating a mean of a corresponding ratios, of the minima dataset to the
maxima dataset of the extremum dataset, with a measured diastolic blood
pressure values in real-time and a measurement coefficient to extract the real-

time diastolic blood pressure;
by extracting a time intervals datasets for a corresponding bio-signal
response
between the extremum datasets of first optical spectrometer and second optical

spectrometer;
by extracting a mean of time intervals of the time intervals datasets;
by extracting a ratio of a distance, between first optical spectrometer and
second optical spectrometer, to that of the mean of time intervals to extract
a
mean longitudinal pulse velocity; and
by correlating the mean longitudinal pulse velocity with the real-time
diastolic
blood pressure to extract the real-time mean arterial blood pressure and the
real-time systolic blood pressure.
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11. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a heart to device length:
by displaying a plurality of user instructions to place arm in different
positions; and
by recording and correlating the real-time signals from the 9/6-axis
accelerometer.
12. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a real-time blood sugar levels:
by correlating the optical bio-signals responses of the green LED, the red LED

and the infrared LED with the optical bio-signals responses of the near
infrared LED to eliminate baseline errors and beat to beat fluctuations of
tissue
absorption, blood flow fluctuations and coherent errors in the optical bio-
signals responses of the near infrared LED to extract a processed near
infrared
bio-signal responses;
by correlating the processed near infrared bio-signal responses with a
measured blood sugar values in real-time to extract the real-time blood sugar
levels; and
a hypoglycaemia and a hyperglycaemia condition:
by analysing the real-time blood sugar levels with a threshold values of
hypoglycaemia and hyperglycaemia.
13. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a rapid eye movement sleep cycles and a non-rapid eye movement sleep cycles:
by evaluating an average heart rate, an average respiratory rate, a blood
pressure levels, an oxygen saturation, a blood sugar levels and the body
temperature for a realistic range and by analysing the real-time signals of
the
9/6-axis accelerometer to verify a sleeping and dormant state;
by analysing at least the average respiratory and the blood pressure levels
with
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a sleep dataset, an activity dataset and a wake dataset to recognize a sleep
state;
by analysing a pattern of the average respiratory rate, the blood pressure
levels
and an instantaneous heart rate to recognize the rapid eye movement sleep
cycles and the non-rapid eye movement sleep cycles; and
by recording a time period of the rapid eye movement sleep cycles on
recognition of the rapid eye movement sleep cycles and a time period of the
non-rapid eye movement sleep cycles on recognition of the non-rapid eye
movement sleep cycles.
14. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a sleep apnoea conditions and a time periods of sleep apnoea:
by analysing an instantaneous heart rate dataset in one or more time frames
for
a specified range of beats per minute difference between their extremum and
for a falling edge and a raising edge in a cycle time to recognize the sleep
apnoea conditions;
by analysing a pattern of an average respiratory rate dataset to further
verify
the sleep apnoea conditions; and
by recording the time periods of sleep apnoea on recognition of the sleep
apnoea conditions.
15. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to obtain:
a step movements dataset:
by analysing the real-time signals of the 9/6-axis accelerometer to extract a
normalized values dataset; and
by analysing the normalized values dataset for peaks within a deviation from a

mean of the normalized values dataset to detect the step movements and a
number of steps.
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16. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is configured to:
start or wake the medical and health monitoring apparatus on detecting a
realistic bio-
signals;
record a plurality of inputs from the user for learning parameters
calibration;
detect or calibrate a plurality of user positions and movement data comprising
a
sleeping state, a sitting position, a standing position, a running state, a
sprinting state
and a resistance training state:
by analysing the real-time signals of the 9/6-axis accelerometer and a
plurality
of vital signal data comprising a heart rate, a respiratory rate, a blood
pressure
levels, a blood sugar levels, an oxygen saturation, a neural activity
parameter
and the body temperature;
detect the sleeping state, the sitting position or the standing position:
by analysing a pattern of the heart rate, the respiratory rate and the blood
pressure levels at a null step movement;
detect a cycling mode or a driving mode:
by evaluating an average speed with a human physical limit at the null step
movement;
detect a walking state, the running state or the sprinting state:
by analysing the average speed and the plurality of vital signal data at a
step
movement;
detect a number of strides or steps per minute, a number of laps and a minutes
per laps
count:
by analysing the real-time signals of the 9/6-axis accelerometer and stored
values of the GPS;
detect a fatigue condition:
by analysing a real part of an impedance response of the electrical bio-signal

responses;
record and display a threshold index of EI (Emotional Index) meter:
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by analysing a pattern of the heart rate, the respiratory rate and the real
part of
the impedance response;
guide the user to a guided breathing technique with an increased breath-out
and
decreased breath-in pattern, a meditation video and a social chat on
recognition of a
stress state;
record a new threshold index on trigger of a markup of the threshold index;
detect a hypoglycaemia state and a hyperglycaemia state:
by analysing the real-time blood sugar levels;
detect a congestive heart failure condition:
by analysing a pattern of the heart rate and the respiratory rate;
detect a CO poisoning condition:
by analysing for a decreasing pattern of the oxygen saturation and an
increasing pattern of the heart rate and the respiratory rate;
detect a hypoxia condition or a hypoxemia condition or a blood disease
condition:
by analysing for a low level of the oxygen saturation, a fast unsteady pattern
of the respiratory rate and an increasing pattern of the heart rate;
detect a hypothermia condition:
by analysing for a reducing pattern of the body temperature and the heart
rate;
detect a hyperthermia condition:
by analysing for an increasing pattern of the body temperature, the heart rate

and the respiratory rate;
automatically send a warning message to an user eco-system, emergency contacts
of
the user and the user on recognizing health and emergency conditions
comprising the
hypertheiiiiia, the hypothermia, the hypoxia condition, the CO poisoning
condition,
the congestive heart failure condition, the hypoglycaemia state and the
hyperglycaemia state;
extract and record a basal metabolic rate by analysing data of the heart rate;
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rectify errors in the plurality of optical bio-signal responses by applying a
feedback of
the electrical bio-signal responses; and
to remove errors due to circadian cycle and to asses a health of circadian
cycle by
applying an unsupervised learning.
17. The medical and health monitoring apparatus of Claim 1 is synchronized to
an
accessorial mobile device, wherein the accessorial mobile device is configured
to:
log and track a plurality of routine health check-up data comprising a height,
a weight,
a basal metabolic index, a basal metabolic rate, a workout target, a nutrition
intake
data and a physical exercise activities;
display a recorded health data including a base heart rate data, a distance
commuted
and a calories expenditure;
display an emotional index meter that shows a persona oriented stress levels
and a
tracking meter that reports progress on stress management;
direct to a guided breathing based stress management technique, a mediation
technique or a social media communication interface on detecting a threshold
of the
emotional index meter;
display a daily work management schedule that shows a plurality of scheduled
activity with their priority recorded by the user;
display a recorded sleep cycle trend, a sleep period, a non-rapid eye movement
sleep
cycle length, a rapid eye movement sleep cycle length and a sleep log;
display a warning message regarding sleep disorder on recognizing a sleep
disorder;
enable a health advisors network of medical practitioners, dieticians and
fitness
advisors to interact with the user and guide the user with health practices
and
therapies;
enable the user to access health blogs, articles and classes;
display a medication tracker and reminder that records a medication pattern
and a
medication reminders;
alert the user at a time to take medication;
display a real-time vital data of a heart rate, an oxygen saturation, a
respiratory rate, a
pulse rate variability, a neural activity, a body temperature, a blood sugar
levels and a
blood pressure levels along with a navigation access to an individual signal
physiological waveform of the real-time vital data;
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enable the user to share the real-time vital data, the medication pattern, the
recorded
health data, the sleep cycle trend, the sleep period, the non-rapid eye
movement sleep
cycle length, the rapid eye movement sleep cycle length, the sleep log, the
tracking
meter and the plurality of routine health check-up data with the health
advisors
network, and also to synchronize them on a cloud service; and
display an interface to synchronize, install and manage a plurality of third
party
applications on the medical and health monitoring apparatus.
18. The medical and health monitoring apparatus of Claim 1, wherein the
microprocessor
with internal memory, of the medical and health monitoring apparatus, along
with the
network of computational and storage devices, that includes at least a server
and a
plurality of accessorial devices, are configured to execute a parallel
computing to
increase speed and efficiency of computations.
19. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus further comprises:
a transmittive arrangement of the optical spectrometer configured to capture
the
plurality of optical bio-signal responses in a transmittive configuration;
an alternative inverted arrangement, of the optical spectrometer in the
transmittive
configuration, configured to minimize a background optical noise in the
plurality of
optical bio-signal responses;
a heat dissipating expandable ring body configured to securely hold the
medical and
health monitoring apparatus on a sensing spot in a size adaptable manner;
a plurality of ventilation holes, on said heat dissipating expandable ring
body,
configured to regulate a heating; and
a foam base on a contact surface configured to minimize motion errors and to
enhance
a mechanical gripping.
20. The medical and health monitoring apparatus of Claim 19, wherein the
medical and
health monitoring apparatus further comprises:
a spirally extending element, comprising at least an adjustable clipper and a
hinge,
configured to securely hold the medical and health monitoring apparatus on the

sensing spot in a size adaptable manner.
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21. The medical and health monitoring apparatus of Claim 19, wherein the
medical and
health monitoring apparatus further comprises:
an open ring structure configured to securely hold the medical and health
monitoring
apparatus on the sensing spot in a size adaptable manner.
22. The medical and health monitoring apparatus of Claim 21, wherein the
medical and
health monitoring apparatus further comprises:
one or more buttons configured to:
switch to a plurality of device modes comprising a meeting mode, a work
mode, a fitness mode and a sleep mode;
access and operate a telephonic call, a wireless synchronization facility and
a
presentation;
a gesture sensor configured to access and operate the presentations; and
a vibrator module configured to automatically vibrate in a pattern to guide
during an
instance of a stress or an anxiety.
23. The medical and health monitoring apparatus of Claim 22, wherein the
vibrator
module is configured to vibrate with an at least 7.5% 25% higher ON time to

indicate a breath-out demonstration and with an at least 7.5%-25% lower OFF
time
to indicate a breath-in demonstration, to guide during the instance of the
stress or the
anxiety.
24. The medical and health monitoring apparatus of Claim 22, wherein the
vibrator
module is further configured to prompt a plurality of alarms.
25. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus further comprises:
a reflective arrangement of the optical spectrometer configured to capture the
plurality
of optical bio-signal responses in a reflective configuration;
an adjacent LED-photodetector arrangement, wherein the green LED, the red LED,

the infrared LED or the near infrared LED are placed at a noise free recording

distance between one or more corresponding photodetectors of the photodetector
set;
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and
a foam base on a contact surface configured to minimize motion errors and to
enhance
a mechanical gripping.
26. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus is packaged, in a packaging form, through a
segregation
in one or more planes configured to curtail an electrical noise, reduce a
tracing effort
and increase a packaging efficiency.
27. The medical and health monitoring apparatus of Claim 26, wherein said
packaging
form has the wireless antennae set arranged in a way to reduce noise
interruptions.
28. The medical and health monitoring apparatus of Claim 26, wherein said
segregation
in one or more planes comprises a biosensor plane, an analog and digital
frontend
plane, an electronic plane and a power plane.
29. The medical and health monitoring apparatus of Claim 26, wherein said
packaging
form further comprises:
a plurality of ventilation pores, on said packaging form or a casing of said
packaging
form, configured to regulate a heating; and
a foam base, on a contact surface of said packaging form, configured to
minimize
motion errors and to enhance a mechanical gripping.
30. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus further comprises:
a heat regulating case comprising the optical spectrometer in a reflective
configuration;
a soft stretchable cloth configured to hold the medical and health monitoring
apparatus steadily on a sensing spot;
a stickable surface and an adhesive surface, on the soft stretchable cloth,
configured to
steadily hold and fasten the medical and health monitoring apparatus on the
sensing
spot; and
a foam base, on a contact surface, configured to minimize motion errors.
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31. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus further comprises:
a heat regulating case comprising the optical spectrometer in a reflective
configuration;
an expandable machine gripper holder configured to attach the medical and
health
monitoring apparatus to an exercising machine and to steadily hold on a
sensing spot;
and
a foam base, on a contact surface, configured to minimize motion errors.
32. The medical and health monitoring apparatus of Claim 1, wherein the
medical and
health monitoring apparatus further comprises:
an inflatable mini cuff configured to automatically inflate at a contact to
detect a
resonant point of blood pressure; and
a wireless base station with a touch display configured to display and provide
access
to live vital signals and a patient information.
33. The medical and health monitoring apparatus of Claim 32, wherein the
medical and
health monitoring apparatus further comprises:
a reflective configuration of the optical spectrometer placed in the
inflatable mini
cuff;
an electrical cord to alternatively attach the wireless base station to the
inflatable mini
cuff;
a button configured to reset a medical analysis and to power on or power off;
and
a wireless synchronization button configured to wirelessly synchronize the
medical
and health monitoring apparatus with external devices.
34. The medical and health monitoring apparatus of Claim 1 packaged in a
wearable
form, wherein the medical and health monitoring apparatus further comprises:
a mini inflatable strap configured to inflate to detect a resonant point of
blood
pressure;
a stress management LED set comprising:
a red light indicator LED that automatically flashes during an instance of a
stress or an anxiety; and
Date Recue/Date Received 2023-06-26

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57
a green light indicator LED that automatically flashes in a stress management
assisting pattern to guide during the instance of the stress or the anxiety.
35. The medical and health monitoring apparatus of Claim 34, wherein the green
light
indicator LED is configured to blink with an at least 7.5% 25% higher ON
time to
indicate a breath-out demonstration and with an at least 7.5% _____ 25% lower
OFF time
to indicate a breath-in demonstration to guide during the instance of the
stress or the
anxiety.
36. The medical and health monitoring apparatus of Claim 34, wherein the
medical and
health monitoring apparatus further comprises:
a wireless synchronization button configured to wirelessly synchronize the
medical
and health monitoring apparatus with the network of computational and storage
devices;
a trigger button configured to operate applications and functionalities of the
medical
and health monitoring apparatus; and
a mode indicator light configured to show an operating mode or a functional
status of
the medical and health monitoring apparatus.
37. The medical and health monitoring apparatus of Claim 1 packaged in a
wearable
form, wherein the medical and health monitoring apparatus further comprises:
a mini touch display configured to provide an access to:
a startup application that displays a time and date, a calorie burnt
information,
a calorie consumed information, a weekly health history, a battery strength, a

climate information and a wireless connectivity information;
a background application, of the startup application, that displays a
motivational quote intended to improve spirit of user;
a cardiac training application that tracks and displays a plurality of
training
data comprising a training intensity, a training period, a rest period, a
cardiac
rate, an average speed, a distance travelled, a sets count and a reps count;
a persona oriented stress management application that tracks and displays a
real-time stress levels in an emotional index meter, a queued work schedule
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58
with a priority rating and a descriptive information on stress levels and
stress
management techniques;
a sleep management application that tracks and displays a real-time sleep
information, a user configured alarm and a moming motivational quote;
a medical application that tracks and displays plurality of real-time and
recorded vital information that at least includes a heart rate, an oxygen
saturation, a respiratory rate, a body temperature, a pulse rate variability,
a
neural activity balance, a blood pressure levels and a blood sugar levels; and
at least a potentiometer integrated crown and a button configured to navigate
through
and operate the startup application, the cardiac training application, the
persona
oriented stress management application, the sleep management application and
the
medial application.
38. The medical and health monitoring apparatus of Claim 37, wherein the
medical and
health monitoring apparatus is configured to:
begin a tracking of a training session, with plurality of training data, on a
long hold of
the button in the cardiac training application;
switch between the tracking of the training session between the rest period
and the
training period on a short press of the button in the cardiac training
application;
halt the tracking of the training session on the long hold of the button in
the cardiac
training application;
end the tracking of the training session on the short hold of the button post
a halt in
the cardiac training application; and
resume the tracking of the training session on the long hold of the button in
the
cardiac training application.
39. The medical and health monitoring apparatus of Claim 37, wherein the
medical and
health monitoring apparatus is configured to:
record a plurality of subjective reference data points marked through a press
of the
button in the persona oriented stress management application; and
generate the real-time stress levels in the emotional index meter based on the
plurality
of subjective reference data points.
Date Recue/Date Received 2023-06-26

Description

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1
Description
Title of the Invention: Non-Invasive Multifunctional Telemetry Apparatus and
Real-Time
System for Monitoring Clinical Signals and Health Parameters
Technical Field
[0001] The present invention relates to a telemetry multi-functional medical
instrumentation,
real-time system and software device for precisely monitoring vital bio-
signals. The vital
bio-signals include cardiac rate, pulse rate variability, blood volume
fluctuations,
continuous blood sugar levels, continuous blood pressure levels, respiratory
rate, neural
activity, stress levels, oxygen saturation, body temperature, sleep patterns,
etc. It also
illustrates an integrated automated life-support system which forecasts the
risk of
congestive heart failure (CHF), hypertension, hypothermia, hypoglycemia,
hyperglycemia,
hyperthermia, sleep apnea (OSA), CO poising, nervous breakdown and other
chronic
medical conditions. It describes technologies that can work efficiently even
in ambulatory
and motion artefact prone situations. The processing system and hardware
architecture of
the device can be broadly classified into clinical system, live clinical
diagnostic
instrumentation, mobile medical device and telemetry wellness management
technology.
The overall disclosure presents an invention related to an advanced integrated
solution of
telemetry multi-functional medical device and general wellness instrument,
more
specifically a technology involving non-invasive bio-sensing technology.
Background of the Invention
[0002] With the evolution of information technology and advanced medical
diagnostic tools,
it has become easier for medical professionals to diagnose and treat a
disorder or life
threatening medical condition. Despite this progress and advancement, the
clinical centres
and hospitals have become overly crowded places. The congested scenario of the
clinical
centres can be accounted to modern human lifestyle and use of stationary
medical
instruments. Clinical staff spend significant amount of time on attaching the
several
complex instrumentations and bulky devices to the patients.

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[0003] Pulse oximeter devices have been utilized to improve the portability
and reduce the
complexity of the diagnosis, but these devices suffer limitations in terms of
accuracy and
deficient of information. Further attempts have been made by scientists and
inventors to
propose an instrument that could monitor multiple clinical parameters. But,
these proposals
as well lack proper implementation system and a corrugate technology
architecture for non-
invasive monitoring of multiple clinical parameters.
[0004]
What is needed is an integrated solution of:
compact and less complex medical instrumentation with maximized clinical
information;
accurate telemetry device which can offer complete medical diagnostic
solution; and
an advanced wellness management technology.
Summary of the Invention
[0005] The object of the invention is to present a precise state-of-art
multifunctional telemetry
medical device with an integrated well-being management solution for recording
and
monitoring multitude of vital bio-signals. The device can also be utilized to
monitor real-
time physiological parameters and other important clinical information even in
a portable
or remote setting. The invention addresses wireless mobile apparatus, hardware

configurations, real-time system and embodiment forms for telemetry clinical
monitoring
and daily health management. The goal of invention is to present a compact
portable
solution for remote and live clinical monitoring, and for well-being
management.
FIRST ASPECT
[0006] In the first aspect of the invention, a low-powered and compact
hardware architecture
of the telemetry apparatus is provided. The hardware architecture enables the
measurement
of clinical signals and general wellness parameters with more precision and
efficiency.
[0007] The hardware comprises of electrical spectrometer and optical
spectrometer. The
optical spectrometer contains signal probe set of Green LED, Red LED,
Infrared(IR) LED
and Near-Infrared (Near-IR), which are operated by a single gain programmable
LED
frontend. The intensity and trigger of the input signals are adjusted through
the circuit line
of LED frontend and central microprocessor. A multiple pole switch set (or) a
set of
switches enables the operation of the multiple LED signal probes by a single
frontend,

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which makes it low powered and more compact. The LED frontend contains an op-
amp
based bio-safety circuit that ensures the optical signal probes emit low
powered optical
signal. The low powered optical response is amplified and focused by an
optical amplifier
on the photodetector set. The photodetector set records the output optical
response and the
response is processed by a circuit line of stage 1 amplifier, buffer, power
notch filter, stage
2 amplifier and ambient noise cancellation IC. The circuit line of the
photodetector
amplifies, filters and refines the output signal, and sends the processed
output signal to the
microprocessor.
[0008] The microprocessor is attached to a non-contact MEMs/NEMs temperature
biosensor,
which logs the body temperature response and thermal feedback. A 9/6 axis
MEMs/NEMs
accelerometer of the hardware is utilized as a real-time feedback to remove
motion noise
from bio-signal response. A set of wireless antennae of WLAN, BLE, GSM and GPS
are
either externally attached to the microprocessor or integrated inside the
microprocessor.
The set of wireless antennae communicates the data between the telemetry
apparatus, and
the set of external storage and computing devices like accessorial mobile
devices, server,
etc. The set of wireless antennae along with the accelerometer is used for
tracking the real-
time location and movement signals like phase, speed, steps taken, etc. The
wireless
microprocessor with inbuilt memory, is used for communicating commands and
feedbacks
with the internal electronic components of LED frontend, photodetector
frontend,
Impedance analyser IC, Accelerometer, temperature biosensors, other sensors,
wireless
antennas, USB module and other electronics modules. The function of
microprocessor also
includes computing and storing the required information. A touch display is
attached to the
hardware for viewing and accessing the real-time medical information, health
data and on-
device applications. The touch display is also used to operate the
instrumentation and
embodiment forms of the telemetry apparatus.
[0009] The hardware of the telemetry apparatus is powered by a power supply
unit, which
comprises of a power management IC, supercapacitor-battery set, supercapacitor-

renewable energy harvester, USB module and negative voltage converter. The
power
management IC of power supply unit, attached to the hardware and
microprocessor,
regulates the current flow and power supply. The USB module and supercapacitor-
battery
are utilized for powering the electronic circuit. The USB module is also used
for
communicating the data with the external devices and charging the battery of
the internal
circuit. A negative voltage converter attached to the power management unit
generates the

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negative voltage reference. The power supply unit includes an alternative and
supplementary power supply unit containing renewable energy harvester and
supercapacitor.
[0010] Apart from the display unit, the hardware of the telemetry device is
internally or
externally attached to an additional user interaction system of mic, video
camera and
speaker. The set of user interaction hardware components is utilized by user
for interacting
with the professional medical and health practitioners for clinical and health
analysis. The
professionals can send and receive the information, as well supervise the user
through the
user interaction system. The user interaction unit is also used as the means
to perceive the
recorded and computed information, and to operate the telemetry device and its
in-built
applications.
SECOND ASPECT
[0011] The second aspect of the invention explains an electrical spectrometer
apparatus of the
telemetry hardware, which is utilized as the means for measuring electrical
and
electrodermal bio-signals. Preferably, a set of four electrodes of the
electrical spectrometer
are placed at equidistant positions in a straight line. An input electrical
sensor injects the
low power signal, and an electrical sensor drains the signal through the
ground. A biosafety
circuit, containing operational amplifier with a feedback impedance having
lesser value
compared to the input impedance, is attached to the input electrical sensor.
The biosafety
circuit improves operational safety of the electrical spectrometer apparatus.
[0012] A set of two response electrical sensors are placed between the signal
input electrical
sensor and drain electrode. The signal between response electrical sensors are
processed,
amplified and filtered through a response circuit line of Instrumental
amplifier, Gain
amplifier circuit, power notch filter, and V-I converter IC. The processed
output response
passes to the Impedance Analyzer chip. The Impedance Analyzer chip assess and
resolves
the output electrical response, and communicates the analyzed results to the
microprocessor.
THIRD ASPECT
[0013] A reflective optical spectrometer technology with adjacent LED-
photodiode
arrangement is exhibited in the third aspect of the invention. In the optical
apparatus, the
signal probes of Near-Infrared LED, Infrared LED, Red LED and Green LED, are
embedded between their corresponding wavelength response photodetectors and
are
aligned in blood flow direction. An optical lens or a micro-prism is placed on
the Near-IR

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LED probe to tune the Near-Infrared signal. The reflected responses are
recorded by the set
of corresponding adjacent photodetector probes, which are assembled at a noise-
free
recording distance. This adjacent configuration of LED-photodetectors enables
simultaneous operation of different signals probes with more accuracy and
speed. A non-
contact MEMs/NEMs temperature biosensor is positioned at the edge of the
sensor board
with a minimum distance from heat dissipating surface, that is utilized for
record the error-
free body temperature and thermal noise feedback. A disposable foam/sponge is
placed on
the contact surface surrounding the sensors, signal probe and receiver area
for reducing the
motion errors and increasing the reusability,
FOURTH ASPECT
[0014] A compact and efficient spectrometer apparatus packaging method is
proposed in the
fourth aspect of the invention disclosure. The packaging design of the
spectrometer
comprises biosensors of electrical sensors, optical signal and detector
probes, and non-
contact MEMs/NEMs temperature sensor placed on the top surface (or) contact
surface.
The 9/6-axis accelerometer is arranged in a fixed reference direction to the
biosensor
direction, which is utilized as an efficient assembly technique to record the
feedback signals
and the movement signals. The Analog and Digital frontend plane is placed in a
successive
vertical plane to the biosensor plane. The third sequential plane is an
electronic plane
containing microprocessor, power supply unit, computing unit, wireless
antennas and other
ICs embedded plane. The last layer accommodates the set of battery, energy
generation unit
and other power unit components such that it does not obstruct the wireless
antennas, which
is used to reduce noise interruption. The aforementioned packaging technology
and
sequential packing method is utilized to reduce tracing efforts, curtail
electrical noise and
increase packaging efficiency. The apparatus packaging around the electronics
is perforated
with ventilation pores for regulating device heating. A disposable foam/sponge
base is
placed on the contact surface without obstructing the bio sensors, which is
used for reducing
the motion errors and increasing the multi-use utility.
FIFTH ASPECT
[0015] In the fifth aspect, a ring form for remote and telemetry monitoring is
provided. The
LED signal probes of Near-Infrared LED, Infrared LED, Red LED and Green LED of
the
device are placed in an inverted transmission configuration, where LED probes
faces the
underside of the contact surface. The photodetector set of visible/IR and Near-
IR

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photodetectors are aligned with the corresponding signal probes and are placed
on the top
response receiving surface. The inverted configuration of LED signal probes
and
photodetector set minimizes the background optical noise in the response
recording. An
optical lens is placed before the photodetector set for efficiently capturing
and focusing low
powered optical response on photodetector set. The NEMs/MEMs non-contact
temperature
biosensor is assembled at edge ofthe ring frame and away from the heat
dissipating surface,
which is utilized to measure body temperature values and thermal feedback. A
set of four
electrical bio sensors are assembled in a straight line, on the perpendicular
contact surface
to the optical probes, for extracting electrical and electrodermal bio-
signals. A 9/6-axis
NEMs/MEMs accelerometer is positioned in a specific direction with reference
to the
optical and electrical sensing probes, which is used as a sensor assembly
method to record
the movement feedback more accurately. The device is fabricated in a spiral
ring structure
with a heating dissipating and expandable casing material. The main ring frame
contains
sensors, wireless antennae, power supply unit, battery, digital chips, Analog
ICs,
microprocessor, integrated circuits and other electronic components. A clipper-
hinge
element protrudes from the main ring frame to form a spiral ring structure,
which holds the
instrument securely on the sensing spot. The expandable casing with adjustable
clipper-
hinge element, is utilized as the mechanical method for fastening the
instrument in a size-
adaptable manner. A reasonable number of pores are vented on the device frame
to regulate
electronics heating. A disposable foam base is placed on the contact surface
surrounding
the biosensors, which is utilized to enhance the mechanical gripping, clinical
hygiene and
reusability efficiency.
SIXTH ASPECT
[0016] A ring embodiment form for telemetry monitoring and daily wellness
management is
explained in the sixth aspect of the invention. The ring apparatus has an open
ring structure
for comfortably holding the device on the sensing spot in a size adjustable
manner. The
ring comprises of sensing components of optical apparatus, electrical
spectrometer
apparatus and other biosensor components, which are placed at an optical
sensing spot. A
vibrator is implanted on the contact of the ring to guide the user during
mental stress, and
to prompt the scheduled alarms calls. The device has an in-built persona-
oriented stress
management application, which automatically activates and guides the user
during the
instances of stress or anxiety. Once state of stress or anxiety is recognized,
the vibrator
module on the contact surface oscillates in a definite remedial pattern
according to the real-

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time physiological condition of the user. During the real-time guided stress
management
application, the vibrator oscillates with 7.5%-25% higher ON time to indicate
breath-out
demonstration and 7.5%-25% lower OFF time to indicate breath-in demonstration.
The
ring apparatus has a button on the outer top surface and a button on the lower
bottom edge
surface. The button on lower surface is used to operate the functional modes
of meeting
mode, work mode, fitness mode, sleep mode and others. The button on the top is
utilized
for operating the telephonic calls, wireless synchronization facilities and
other
functionalities. A gesture sensor is embedded on the user facing front
surface, which is used
as an interactive gestural means for accessing and navigating through the
presentations and
the applications. Additionally, the button inputs are used to access
presentations and
applications.
SEVENTH ASPECT
[0017] The seventh aspect of the invention puts forward a multifunctional
medical instrument
for limb attachment or forehead telemetry. The electronics components and
sensors of the
hardware are packaged in a heat regulating case, according to the fourth
aspect. The
biosensors are arranged on the contact surface of the case of the telemetry
apparatus. A soft
stretchable cloth attached to the main packaging case, contains adhesive
surface and
stickable surface end tail pads. The adhesion action between the adhesive pad
and stickable
pad, and the stretchable cloth belt are utilized to fasten the apparatus
steadily on the sensing
spot. The foam base situated on the contact surface and surrounding the
biosensors, is
utilized as a mechanical means to reduce movement noise in the bio-signal
recording. The
other utility of the disposable foam includes improvement of the clinical
hygiene and
reusability efficiency.
EIGHTH ASPECT
[0018] The eighth aspect of the invention illustrates an auxiliary wellness
management and
clinical monitoring device, that can be attached to an exercising machine. The
essential
sensors and electronics components of the apparatus are packaged in a heat
regulating case,
as per the fourth aspect. The biosensors are assembled on the contact surface
of the case of
the telemetry apparatus. The heat regulating case is attached to an expandable
machine
gripping holder, and this expandable holder is used to attach the device to
wellness
instrument (like exercise cycle, treadmill, bike etc). The expandable holder
grips the
exercise machine and the keep the apparatus steady on the sensing spot. A foam
base on

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the contact surface around the biosensors, is utilized to reduce movement
noise in the bio-
signal recording.
NINTH ASPECT
[0019] A bracelet or smart band embodiment for telemetry and general wellness
management
is presented in the ninth aspect of the invention. The optical apparatus,
electrical
spectrometer and non-contact temperature sensor are placed on the contact
surface of the
device. The casing of the device contains the accelerometer, sensors, wireless
antennas,
power supply unit, battery, digital chips, Analog ICs, microprocessor,
integrated circuits
and other necessary electronic components. The device has an integrated low-
pressure
mini-cuff, which automatically inflates to the detect the resonant compression
point for
blood pressure calibration. A mini-touch display is placed on the top surface
of the
apparatus, which is used for operating the apparatus, accessing in-built
application, and
viewing the essential information (such as medical information, health data,
bio-signals,
general wellness data, etc). A set of Red and Green indicator LEDs are
embedded on the
top surface near the display. The indicator LEDs automatically blinks to guide
the user
during the instances of psychological stress or anxiety. During the recognized
state of
mental stress, the red indicator light flashes at the detected neural
activity, and the green
indicator light flashes at a definite assisting pattern. The green indicator
light blinks with a
7.5% - 25% higher ON time to indicate breath-out demonstration, and 7.5% - 25%
lower
OFF time to indicate breath-in demonstration. A mode indicator light denotes
different
operating modes and other functional status of the apparatus. A trigger button
placed on the
top surface is used for operating the device, accessing in-built application
and utilizing
other functionalities. The device has a wireless synchronization button for
synchronizing
the data and device with accessorial devices.
TENTH ASPECT
[0020] In the tenth aspect, a live multi-functional telemetry instrumentation
is elucidated. The
live wireless clinical monitor comprises of a cuff packaged with biosensors
and a base
station packaged with other essential electronic components. The biosensors of
electrical
spectrometer, optical spectrometer, accelerometer and non-contact MEMs/NEMs
temperature sensor are arranged and packaged inside an inflatable mini-cuff.
In the
presence of user, the cuff automatically inflates to detect the resonant point
for blood
pressure calibration. The electrical cord of the instrument is used as the
wired method to

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the attach the base station and the cuff. A slate sized touch display is
assembled on the
wireless base station for accessing and viewing live medical signals, patient
history,
patient's physical activities, other clinical information and health data. The
touch screen is
as well utilized to operate the device and access the in-built application. A
wireless
synchronization button and a power button is embedded on the wireless base
station. The
wireless synchronization button is used for synchronizing the clinical
recording, patient
history, medical information and other important information between the
telemetry
apparatus and computer server/accessorial mobile apparatus. The power button
on the base
station is utilized as the means to reset the medical analysis, power on/off
the device and
access other in-built fiinctionalities.
ELEVENTH ASPECT
[0021] According to the eleventh aspect, a smart wearable instrument for
medical monitoring
and daily wellness management is presented. The smart wearable comprises of a
round case
or rounded rectangular case, that holds the electronic components and sensors
of the
telemetry device. The biosensors, aligned in the blood flow direction, are
placed on the
contact surface, and a mini touch display is embedded on the top surface. The
device is
operated through the mini-touch display. The clinical information, health
data,
psychological stress, sleep data, daily diet pattern, fluid intake
information, amount of
expended energy, active step/stride taken, and other lifestyle management data
are
displayed on the mini touchscreen. The mini display is also used to view and
access real-
time medical diagnostic signals, recorded information, therapy techniques,
automated
cardiac activity guide, wake-up alarm, in-built applications and other
important information.
Push buttons and potentiometer integrated crown, are embedded on the parallel
to side
surface and perpendicular to the electronic board. The push buttons and crown
are utilized
to access different device applications, to calibrate the apparatus and to
switch between the
different functional modes. The crown integrated with potentiometer is used as
the
electronic embedded method to navigate through the application in row and
columns, and
to operate other apparatus fimctionalities. The rounded comers or round
contact surface is
used to evade the cuts, that may otherwise occur due to sharp edges.
[0022] The home screen of the smart wearable displays daily health management
information
and a motivational quote. The background motivational quote application is
intended to
psychologically improve the spirit of the user. The smart wearable apparatus
comprises of
applications for real-time clinical monitoring, cardiac training, tracking
Emotional Index,

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persona oriented phycological stress management, sleep management and other
lifestyle/wellness management information.
[0023] During physical training, the cardiac training application
automatically tracks training
intensity, rest period, training period, cardiac rate, training phase and
other important health
data. The automated cardiac application also has essential information to
guide the user
with health improvement and recovery. The push buttons are utilized to trigger
begin, pause,
un-pause and reset in the cardiac activity tiaining application. The touch
display, push
buttons and the crown are used to access other functional command in the
cardiac activity
training application.
[0024] The real-time stress information is displayed in the emotional index
(El) meter and in
a persona-oriented stress management application. The psychological stress
management
application displays El meter, stress threshold information, stress management
information
and work schedule management features with priority stickies. The El meter
displays
persona-oriented stress information, which has been extracted from the
previously marked
stress data points. The touch display and push buttons are used to mark
unwanted stress
levels.
[0025] The sleep application automatically tracks sleep and displays sleep
period, sleep health,
motivational wake-up quote and other sleep related information. The sleep
application also
includes a user configured wake-up alarm.
[0026] The medical application shows real-time information and recorded data
on pulse rate,
oxygen saturation, respiratory rate, body temperature, average pulse rate
variability, neural
activity balance, blood pressure data and blood glucose levels.
TWELFTH ASPECT
[0027] In the twelfth aspect, a parallel computational network is provided.
The parallel
computational network enables the computation with much higher speed and
efficiency,
while keeping the complexity low. The network of parallel computation network
comprises
of internal microprocessor, external server computers, accessorial mobiles
devices, external
computers and other connected local devices. The external servers are used for
executing
computational process, and as well as for remotely storing the information.
The accessorial
mobile devices and other synchronized devices are also used to compute and
store the
information. The network of parallel computing devices are accessed through
wireless
methods of `WLAN, BLE, GSM' and through other possible modes of communication.

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Whenever necessary, stored information and computed results are communicated
between
the telemetry apparatus and network of devices.
THIRTEENTH ASPECT
[0028] The thirteenth aspect of the invention presents a real-time medical
monitoring and
wellness data processing system.
[0029] Initially, the recorded bio-signals passes through an accelerometer-
based noise filtering
process. The real-time feedback of the angle calibrated accelerometer signals
are sampled
in a normalized form, and the bio-signals are processed through 50/60 Hz
digital filter to
remove the power line noise disruption. The processed bio-signal and
accelerometer signals
passes through repetitive adaptive filter and other computational steps. This
process
removes motion noise from the bio-signal. Then the first order noise free
signal further
passes through a series of banked filters, low pass filter and correlation
computational step
for removing the rest of the noise.
[0030] The filtered signal is further analyzed through time domain and
frequency domain peak
processing methods to precisely compute real-time avg. pulse rate,
instantaneous heart rate,
hr tachogram and neural Activity balance coefficients of al, a2, a-3, cr3/
crl, cr3/ a-2, cr2/
al. The set of computed data and raw signals are sampled at a rate of 7.5Hz,
15 Hz, 30Hz,
100Hz, 125Hz, 240Hz, or 11(Hz. The sampled data is processed using a fast
response
analysis method, and the processed sampled is condensed utilizing a matrix
compression
method. The sampling and compressed data selection method significantly
decreases
computational effort needed to analyze the entire waveform. The compression is
followed
by an analysis to calculate continuous heart rate and average pulse rate. The
signal ratio
between the oscillating peak and stationary peak of red and Infrared
biosensor, in the form
of signal derivate is taken, to determine the oxygen saturation ratio.
[0031] The signal is passed through digital filters of High-Frequency(HF), Low-

Frequency(LF), Very Low Frequency(VLF), Meyer pass filter and Ultra-low
Frequency(ULF) signals. Then, the relative power under each frequency spectrum
is
calculated to assess neural activity. The derived coefficient ofP1, P2, P3 and
P4 are evaluated
through a set of computational steps to determine the overall health of
Autonomous Neural
System and cardiac system.
[0032] The noise-free signals are further analysed in different spectrums to
compute
respiratory rate, avg. breathing rate and meyer wave signal. The pulse signal
is processed

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to decouple the noise artefact free signals into different wave signals. The
pulse wave is
iteratively decoupled to obtain breathing signal, and the derived signal is
processed for
peaks to determine the respiratory rate. The analysed signal is mathematically
operated for
computing average breathing rate, continuous respiratory rate and breathing
rate. A similar
analysis is utilized to decompose the meyer wave signal and its related
parameters.
[0033] The user calibration input, extremum of optical data with respect to
time and recorded
data are analyzed for extracting the continuous blood pressure and diastolic
pressure values.
The dual sensor configuration is utilized to estimate momentum loss in the
blood vessel,
mean pressure and the systolic pressure. The recorded heart to device
reference length is
used in the cuff-based apparatus to accurately measure the mean arterial
pressure.
[0034] An automated method to calibrate the heart to device reference length
is as well
provided. The value of 9-axis accelerometer sensor signals are recorded at
different
instructed arm positions of bent arm, fully stretched arm, lifted arm and
straightened down
stretched arm. Using the recorded sensor data, the forearm and Arm length are
calculated,
through which average heart to device reference length is generated.
[0035] The Near-Infrared biosensor signals and other optical signals of Green,
Infrared and
Red signals are processed to compute Blood Sugar Level. Initially, the input
on the blood
sugar level is taken for sensor calibration. The Green LED, Infrared LED and
Red LED
response signals are processed to remove the losses in the Near-Infrared
signals, due to the
blood flow fluctuations, tissue absorption and other coherent errors. The
Processed Near-
Infrared data is correlated and fitted over various
patient's/user's/physician's inputs to
calibrate the Near-Infrared biosensor. The continuous blood glucose levels,
blood sugar
levels, hyperglycemia and hypoglycemia are computed from the calibrated data.
In case of
chronic medical condition, the system automatically reminds the patient for
medication, or
alerts the user, user network and the physician network about the diagnosed
health
condition.
[0036] The real-time system further comprises of an automated method to record
various
stages of the sleep cycle, and to recognize obstructive sleep apnoea. The
accelerometer
values are initially evaluated for state of sleeping or dormancy, and the real
time
physiological signals are compared to wake or activity physiological data.
After the
verification process, the real time physiological signals of avg. breathing
rate, systolic
blood pressure, diastolic blood pressure and instantaneous Heart Rate signals
are processed

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for tracking the time periods of non-rapid eye movement and rapid eye movement
sleep
cycles. Then a series of computational steps is applied on the instantaneous
pulse rate data,
analyzing for beats per minute difference in definite time intervals, for
recognizing the sleep
apnea condition. Then, the respiratory signal pattern validation step is
utilized for verifying
the state of sleep apnea and sleep cycle. The sleep apnea condition and its
time-period are
recorded in the system.
FOUR __ l'EENTH ASPECT
[0037] The fourteenth aspect of the invention provides a life-support system,
which
automatically recognizes daily activity, pre-clinical emergencies and records
one's state of
well-being. The recorded biosensor data, motion sensor data and wireless
antennae are
processed to evaluate the various postures, user training information, rest
period, activity
period and state of fatigue. The system further learns and records the various
postures,
movement data and activities of the user (such as (of sitting, standing,
number of steps,
number of strides, lap count, speed, training phase, resistance training,
cycling, driving and
more). The life-support system records subjective psychological stress points
and identifies
the stress state of the individual based on the computed vital bio-signal and
electrical
spectrometer signals. If the state of psychological stress is detected, the
system
automatically guides the user to a breathing stress management technique or
other stress
management methods. The system consists of automated clinical emergency life
support
method to detect the risk of CHF attacks, hypoxia, hypothermia, hypoxemia,
blood poising,
blood loss, hyperthermia, unusual ventricular activity, heat stroke, nervous
breakdown and
other chronic conditions. If a life threating or chronic condition is
recognized, the apparatus
alerts the user's network and life support network. The invention also
provides an
automated power saving method. The real-time system comprises of a low powered
method
to recognize the presence of the user based on the estimation of the realistic
bio-response
data and movement data. The recognized user presence is utilized to
automatically power
on, power off or restart the device.
FIFTEENTH ASPECT
[0038] The fifteenth aspect of the invention presents the accessorial software
application and
accessorial mobile apparatus, that is attached to the telemetry apparatus. The
accessorial
software application of the accessorial mobile apparatus comprises of
components for daily
health management, clinical condition management and device application
management.

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[0039] The personal fitness management component of the software application
is utilized to
log and track personal information, routine health check-up data (like weight,
height, basal
metabolic index, basal metabolic rate, workout target), physical exercise
activities and
nutrition intake. The application displays real-time and recorded health data
of base heart
rate, commuted distance and calories expenditure. A cloud synchronization
button on the
application is utilized to synchronize the data with the cloud services and
share the data
with professional practitioners.
[0040] The stress management component of the software application comprises
of emotional
index meter, stress management information, stress management progress meter
and guided
meditation components. The Emotional Index meter shows persona-oriented stress
levels
and it oscillates according to the neural balance. The stress management meter
reports the
progress on the stress management. As the stress meter reaches the threshold,
the device
directs the user to guided breathing/meditation method or to a social
communication
interface. A daily work management feature on this interface is used to
schedule
professional work activity with priority. The work management functionality is
included as
procrastination is an indirect counterpart cause of mental stress.
[0041] The sleep management component of the accessorial software application
tracks sleep
cycles, sleep period, NREM-REM cycle length and other sleep trends. The user
can view
and access the computed data and recorded log. On recognizing sleep disorders,
a warning
message regarding the disorder symptom appears on the user screen. The user
can connect
with physicians and health professionals through the sleep management
inteiface.
[0042] The accessorial mobile device further comprises of an interface to
monitor real-time
information on pulse rate, oxygen saturation, pulse rate variability, neutral
activity,
breathing rate, body temperature, blood pressure levels and blood glucose
levels. The
computed real-time and recorded results are displayed on the screen along with
access to
the individual physiological signal wave form. The user can connect with
medical and
health professional through this interface. The medication tracker and
reminder feature
records the medication pattern and medication reminder. The device
automatically alerts
the user at the correct time for medication. The data on this interface can be
shared on
online platforms and with medical and health professionals through the data
synchronization button.

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[0043] Health network interface of the software application enables
professional medical
practitioners, dieticians, fitness instructors and other health professionals
to interact with
the patient/user. The health network is used by the professionals to guide the
user with
health and therapy practices. The health blogs, articles and classes can be
accessed by the
user through this component of the software application.
[0044] A daily health management component displays information on the number
of active
steps taken, sleep health, heart rate with oxygen saturation ratio and
emotional index matrix.
The background information on daily well-being can be accessed through the
daily health
management component. The progress and history of the user can be accessed by
clicking
on the history trend button of this intei face. The work schedule can also
be organized
through this interface.
[0045] The ease of lifestyle organization interface of the accessorial
software application has
the functionalities to synchronize, install and manage 3rd party and native
applications on
the telemetry mobile apparatus.
Brief Description of the Artwork
[0046] FIG. 1 is the block diagram and hardware architecture of the telemetry
apparatus;
[0047] FIG. 2 shows the design of a reflective optical spectrometer with
adjacent LED-
photodiode configuration;
[0048] FIG. 3 is the isometric view of the hardware packaging of the
reflective sensing
apparatus;
[0049] FIG. 4 is the transmittive optical configuration based spiral ring
embodiment form of
the telemetry apparatus;
[0050] FIG. 5A and FIG. 513 show isometric view of a ring based wearable
embodiment form
for remote clinical monitoring and daily wellness management;
[0051] FIG. 6 illustrates the 3-D view of the clinical embodiment form for
forehead and limb
telemetry monitoring;
[0052] FIG. 7 is the auxiliary embodiment form utilized for monitoring health
and clinical
information during exercise on training machines;
[0053] FIG. 8 is the 3D-view of the live clinical and telemetry monitoring
instrumentation;

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[0054] FIG. 9A and FIG. 9B show isometric view of wearable tracker embodiment
form for
real-time medical monitoring and general wellness management;
[0055] FIG. 10A and FIG. 10B show the smart wearable embodiment form of the
telemetry
apparatus with rounded corners;
[0056] FIG. 11A and FIG. 11B show the round face smart wearable embodiment
form of the
telemetry apparatus;
[0057] FIG. 12A illustrates an automated cardiac training software application
of the
wearable embodiment form;
[0058] FIG. 12B is a persona oriented psychological stress management
application of the
wearable embodiment form;
[0059] FIG. 12C is the sleep management software application of the smart
wearable
embodiment form;
[0060] FIG. 12D shows the application design to view live and stored medical
information;
[0061] FIG. 13 illustrates the network of devices technology to compute and
extract
information more speedily and efficiently;
[0062] FIG. 14 illustrates the application of this telemetry device for remote
clinical
monitoring purposes;
[0063] FIG. 15 shows the application of this telemetry device for live
clinical monitoring in a
crowded hospital scenario;
[0064] FIG. 16A address the processing method and flow chart to remove the
motion
disruptions from Input bio-signal using accelerometer signals as real-time
feedback;
[0065] FIG. 16B describes accelerometer signal computation method to record
the movement
data set;
[0066] FIG. 17 is the flow diagram of a low powered computational method to
process the
first order motion artefact free bio-signal for further removing noise and for
calculating
Avg. Heart Rate, Instantaneous Heart Rate and Neural Activity balance;
[0067] FIG. 18 describes the flow-chart of a low powered real-time bio-sensor
processing
method to compute the Continuous Heart Rate and Oxygen Saturation Ratio;

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[0068] FIG. 19 shows signal analysis methods to extract the parameters related
to Neural
Activity, respiratory activity and Meyer wave activity;
[0069] FIG. 20 shows the real-time computational method to compute breathing
signals and
meyer wave signals;
[0070] FIG. 21 shows the computational flowchart to measure blood pressure
signals from
optical signals and calibrated data;
[0071] FIG. 22 illustrates the automated method to calibrate anatomical
measurements
necessary for micro cuff-based blood pressure measurement;
[0072] FIG. 23 describes the Near-infrared optical biosensor-based method to
extract blood
glucose levels, and blood glucose thresholds;
[0073] FIG. 24 is the flow diagram of the computational method to recognize
sleep cycles
and the risk of Obstructive Sleep Apnea Disorder;
[0074] FIG. 25 shows a basic flow diagram of multi-functional medical device
that computes
medical information using the previously described computational methods;
[0075] FIG. 26A, FIG. 26B and FIG. 26C describe an automated life-support
system that
automatically recognizes postures, user activity, acute clinical conditions
and the state of
well-being, and automatically alerts the user eco-system on detecting health
risks;
[0076] FIG. 27A shows the accessorial software application that displays
important logged
and computed information on user's or patient's heath;
[0077] FIG. 27B shows the accessorial software interface for stress and work
management;
[0078] FIG. 27C shows the accessorial software to monitor sleep patterns and
sleep health;
[0079] FIG. 27D shows the accessorial software application to monitor vital
bio-signals, and
it also includes other functionalities to manage medical conditions;
[0080] FIG. 27E shows the accessorial health platform software interface for
connecting with
health network and professional practitioners;
[0081] FIG. 27F shows the user application interface for tracking daily health

and for well-being management; and
[0082] FIG. 27G shows the application interface to install and manage
applications on the
mobile apparatus.

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Detailed Description of the invention
[0083] Comprehensively, the disclosure can be utilized and perceived in
various applications
that include clinical instrumentation, portable medical device, general
wellness
management technology and other forms of smart health tracking auxiliary
devices. The
principle of the described invention is not intended to limit to the specific
device or
instrumentation application. The disclosure can be chiefly classified into
live clinical
diagnostic instruments, telemetry medical apparatuses, mobile wellness
management
devices, software medical device and other forms of health management devices.
(Hardware Architecture)
[0084] FIG. 1 is the hardware architecture of the telemetry apparatus. It
comprises of optical
elements, optical spectrometer, electrical spectrometer, biosensors, analogue
circuitry,
digital ICs, power supply unit, wireless antennae, computational device and
other electronic
components.
[0085] The hardware of the optical spectrometer has reduced input signal sent
to LED signal
probes, of Near-Infrared LED 1, Infrared LED 2, Red LED 3 and Green LED 4,
through a
biosafety frontend 6. A multiple switch set 5 is attached to the biosafety
circuit and a gain
programmable Bio-LED frontend 7, which is utilized as the means to reduce the
power
requirement and number of active components. The gain programmable LED
frontend 7
triggers the input signal, where the gain can be adjusted based on the user
input or
programmed input. The set of multiple switches 5 automatically shifts the
input signal to
generate the multi-spectral signal as per the control commands.
[0086] An optical component 8 focuses and concentrates the optical response on
the
photodetector set 9. The photodetector set 9 records the optical response and
the photo-
response excitation passes through a series of logic circuit of Stage 1
amplifier 10, Buffer
11, power notch 12, Stage 2 amplifier 13, ADC 14 and Ambient noise
cancellation IC 15.
The series of logic circuit comprising of 10, 11, 12, 13, 14 and 15 filters
noise, amplifies
and processes the output response. The response, in turn, is communicated to
the
microprocessor 45.
[0087] The electrical spectrometer comprises of set of electrical sensors 16-
17-18-19, bio-
safety circuit 20, a series response processing circuit, and Impedance
Analyzer IC 27. The
input signal is generated by the impedance Analyzer chip 27 and passes through
a biosafety
circuit 20. The biosafety circuit is made of an input impedance 21 greater
than the feedback

PPH
19
impedance 22, which is used as the means to improve the operational safety.
The regulated
input signal is injected through an input electrical sensor El 16 and drains
through the
electrical sensor E4 19.
[0088] The electrical sensor E2 17 and electrical sensor E3 18, are placed
between the input
electrical sensor El 16 and draining electrode E4 19, for extracting the
response signals.
The response is analysed, amplified and filtered through a response circuit
line of
Instrumental amplifier 23, Gain amplifier circuit 24, power notch filter 25
and V to I
converter IC 26. The analysed and processed response passes through the
Impedance
Analyzer chip 27, which assess and resolves the output electrical response,
and
communicates the analyzed response to the microprocessor.
[0089] The sensor set of MEMs/NEMs non-contact temperature biosensor 28 and
MEMs/NEMs 9/6-axis accelerometer 29 are attached to the microprocessor 45,
which are
utilized to record real-time feedback, body temperature and motion signals. A
set of
wireless antennae of the WLAN 30, BLE 31, GSM 32 and GPS 33 are either
externally
attached to the microprocessor or integrated inside the microprocessor 45. The
set of
wireless antennae 30-31-32-33 communicates the data between the telemetry
apparatus,
and the set of external storage and computing devices like accessorial mobile
devices,
server, etc. The set of wireless antennae 30-31-32-33, along with the
accelerometer 29, is
used for tracking the real-time location and movement signals like phase,
speed, steps taken,
etc. The wireless microprocessor 45 with inbuilt memory, is used for
communicating
commands and feedbacks with the internal electronic components of LED
frontend,
photodetector frontend, Impedance analyser IC 27, Accelerometer 29,
temperature
biosensor 28, other sensors, wireless antennas 30-31-32-33, USB module 39 and
other
electronics modules. The microprocessor 45 also computes and stores the
required
information.
[0090] The hardware of the telemetry apparatus is powered by a power supply
"nit, containing
power management IC 34, supercapacitor 35-battery set 36, supercapacitor 38-
renewable
energy harvester 37, USB module 39 and negative voltage converter 40. The
power
management unit 34 is attached to the power supply unit, and microprocessor
45. The
power management IC 34 regulates the current flow and power supply. The USB
module
39 and supercapacitor 35¨battery set 36 powers the electronic circuit. The
micro-USB
module 39 is also used to communicate the data with the external devices and
charging the
battery 36 of the internal circuit. The negative signal reference is generated
by the negative
Date Recue/Date Received 2023-06-26

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voltage converter 40. The power supply unit has an alternative powering unit
containing
renewable energy harvester 37 and supercapacitor 38.
[0091] A touch display 41 is attached to the hardware for viewing and
accessing the real-time
medical information, health data and on-device applications. The touch display
41 is used
to operate the instrumentation and embodiment forms of the telemetry
apparatus. Apart
from the display unit 41, the hardware of the telemetry device is internally
or externally
attached to an additional user interaction system of mic 42, video camera 43
and speaker
44. The set of user interaction hardware components is utilized for
interacting with the
professional medical and health practitioners for clinical and health
analysis. The
professionals can send and receive the information, as well supervise the
user. The user
interaction unit 42-43-44 is also used as the means to perceive the recorded
and computed
information, and to operate the telemetry device and its in-built
applications.
(Reflective Optical Spectrometer)
[0092] FIG. 2 is the reflective optical spectrometer with adjacent LED-
photodiode
arrangement, where each signal probe and respective response detectors are
placed next to
each other. The signal probes of Green LED 46, Red LED 47, IR LED 48 and Near-
Infrared
LED 49 are assembled at optimal distance between their corresponding
photodetector set
of visible, IR photodetector and Near-Infrared photodetector of 51-52-53-54-
55. The
Infrared LED's 49 radiation is tuned and focused through an optical
system/micro-prism
50. The set of LED signal probes 46-47-48-49 inject the optical signals and
the reflected
the signal response is recorded by the set of adjacent Photodetector probes 51-
52-53-54-55.
The Non-contact NEMs/MEMs temperature bio-sensor 56 is placed at an optimal
distance
and away from the heat dissipation surface, and with its thermopile probes
facing the
contact surface. The temperature bio-sensor 56 is utilized for recording the
error-free body
temperature and thermal noise feedback. A disposable foam base 57 is placed on
the contact
surface of the optical spectrometer 58, around the sensors, signal probes and
receiver area,
which is used as a mechanical means for reducing the motion errors. The
adjacent LED-
photodetector configuration is utilized to quickly and simultaneously extract
the optical
response.
(Hardware packaging of the telemetry apparatus with reflective spectrometer)
[0093] FIG. 3 is the isometric view of the spectrometer packing. The
biosensors set of optical
spectrometer apparatus 58, non-contact MEMs/NEMs temperature sensor 63 and the
set of

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electrical sensors 59-60-61-62 are assembled on the contact surface 64, for
extracting the
bio-signal response. The optical apparatus 58 is aligned in the blood flow
direction for
extracting optical response. The 9/6-axis MEMs/NEMs accelerometer 65 is
arranged in a
corresponding reference direction to the biosensor set, which is utilized as
an efficient
method to extract the feedback signals and motion signals. The electrical
sensor of 59, 60,
61 and 62 are arranged in a straight line, and in a specific direction with
reference to the
accelerometer sensor 65. The electrical sensor 60 and electrical sensor 61 are
placed in
between the input electrical sensor 59 and drain electrical sensor 62, which
is used for
extracting the electrical response. The Analog and Digital frontend plane 66,
containing the
sensor's digital and analog frontend, is placed in a successive vertical plane
to the biosensor
plane. The third sequential electronic plane 67 containing microprocessor,
power supply
unit, computing unit, wireless antennas and other ICs embedded plane. The last
layer 68 of
the packaging accommodates the set of battery, energy generation unit and
other power
unit components. The last power plane 68 is packaged such that the battery and
metal
components does not obstruct the wireless antennas, which is used as method to
curtail
noise interruption. The casing of the package is perforated with ventilation
pores 70 for
regulating the heat of the device. The described packaging method is used as
the means to
reduce tracing efforts, curtail electrical noise and increase packaging
efficiency. The foam
base/disposable sponge 69 is placed on the contact surface 64 around the bio
sensors, which
is utilized for reducing the motion errors and increasing the multi-use
utility.
(Spiral Ring Embodiment form with transmittive optical configuration)
[0094] FIG. 4 is the isometric view of the transmittive optical configuration
based ring
embodiment preferred in the clinical monitoring and general wellness
management. The
ring embodiment form is fabricated in a spiral ring structure with a main heat
dissipating
expandable ring body 71 and a spirally extending element 89. The ring 71-89 is
made up
of heat dissipating and expandable material. The main ring frame 71 contains
sensors,
wireless antennas, power supply unit, battery, digital chips, Analog ICs,
microprocessor,
integrated circuits and other essential electronic components. The optical
signal probes of
Near-Infrared LED 72, Infrared LED 73, Red LED 74 and Green LED 75 are placed
in an
inverted configuration with LED probes facing the underside ofthe contact
surface 78. The
NEMs/MEMs non-contact temperature biosensor 76 is assembled at edge of the
ring frame
and away from the heat dissipation surface, which is utilized for measuring
body
temperature values and thermal feedback. A 9/6-axis NEMs/MEMs accelerometer 77
is

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positioned in a specific reference direction to the biosensors for precisely
recording the
movement feedback and movement signals. The photodetector set of visible/IR 80
and
Near-IR photodetectors 81 are aligned with the corresponding signal probes and
placed on
the top response receiving surface 82. An optical lens 79 is placed before the
photodetector
set 80-81 for efficiently capturing and focusing low powered optical response
on
photodetector set 80-81. The inverted configuration of LED signal probes 72-73-
74-75 and
photodetector set 80-81, minimizes the background optical noise in the
recorded response.
The set of electrical biosensors 83-84-85-86 are assembled in a straight line
on the
perpendicular contact surface 87, or in an aligned straight line on the
contact surface, which
is utilized for extracting electrical bio-signals. The regulated input signal
is injected through
the input electrical sensor 83 and drains through the electrical sensor 86.
The electrical
sensor 84 and electrical sensor 85, placed between the input electrical sensor
83 and
draining electrode 86, are used for extracting the response signals.
[0095] The spirally protruding structure 89 contains an adjustable clipper 90
and hinge 91, that
holds the instrument on the sensing spot in a size adaptable manner. The
expandable
material is additionally utilized to hold the device securely on the sensing
spot. The
ventilation pores 88 are embedded on the device casing. The heat dissipating
casing
material along with the ventilation pores 88 are used as the means to regulate
the device
heating. A foam base 92, implanted on the contact surface surrounding the
biosensors,
enhances the mechanical gripping of the device.
(Open Ring Embodiment form of the telemetry apparatus)
[0096] FIG. 5A and FIG. 5B show the telemetry embodiment form for general
wellness
management and telemetry monitoring. The sensors, detectors and signal probes
are
assembled at an optimal sensing point 93 and an optimal response spot 94 of
the contact
surface 96. A micro vibrator 95 is assembled on the contact surface 96 of the
ring, which
is utilized to guide the user during mental stress/anxiety and to prompt the
scheduled alarms
calls. The device has a vibrator 95 based persona-oriented stress management
application,
which automatically activates and guides the user during the instances of
stress or anxiety.
Once the state of stress or anxiety is recognized, the micro-vibrator module
95 on the
contact surface oscillates in a definite remedial pattern to calm the user.
During the real-
time guided stress management application, the vibrator 95 oscillates with
7.5%-25%
higher ON time to indicate breath-out demonstration and 7.5%-25% lower OFF
time to
indicate breath-in demonstration. The button 101 on lower edge surface 102 is
used to

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switch the device mode to meeting mode, work mode, fitness mode and sleep
mode. The
button 97 on the top surface 98 is used for accessing the telephonic calls,
wireless
synchronization facilities and other functionalities. A gesture sensor 99 is
embedded on the
front sui __ face 100 (user facing surface). The gesture sensor 99 is used for
accessing and
navigating through the presentations and applications. The button inputs 97-
101 are also
used to access presentations and applications. The open ring structure 103 of
the ring
apparatus holds the device on the sensing spot in a size adjustable manner.
(Telemetry embodiment form for forehead or limb monitoring)
[0097] FIG. 6 is the 3D view of the embodiment form for clinical forehead
monitoring or
ambulatory limb telemetry monitoring. The Reflective bio-sensing apparatus
with foam
base 104 is embedded on the contact surface of the main casing 105, which is
used for
sensing the bio-signals. The main casing 105 is made of heat regulating
material. The digital
IC, analog chips, microprocessor, wireless antennae, sensors, power supply
unit and rest of
electronics items are packaged inside the heat regulating casing 105. A soft
stretchable
cloth 106 is attached to the main packaging case 105, which contains adhesive
surface 107
and stickable surface 108 end tail pads. The adhesion action between the
adhesive pad 107
and stickable pad 108 is used to fasten the device, and as well hold the
sensing apparatus
on the sensing spot. Additionally, the stretchable cloth belt 106 holds the
apparatus steadily
on the sensing spot. The foam base on the contact surface and surrounding the
biosensors
is utilized as a mechanical means to reduce movement noise in the bio-signal
recording.
The other use of the disposable foam includes improvement of the clinical
hygiene and
reusability efficiency.
(Auxiliary training machine attachment embodiment form)
[0098] FIG. 7 shows the embodiment form utilized as an auxiliary attachment to
the wellness
instrument. The auxiliary device 109 is utilized while training on exercise
machines like
cycle, treadmill or bike to record and monitor clinical/health signals. The
instrument 109
with the heat regulating casing 110 is attached to the wellness exercising
instrument
through an expandable machine gripping holder 112. During the health
management
activity and medical monitoring, the expandable machine gripping holder 112 is
used for
fastening the instrument 109 on the auxiliary machine handles. The reflective
sensing
hardware and the set of bio sensors with foam base 111 is placed on the
contact surface of
the main packaging frame 110, which is used for recording the relevant real-
time clinical

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and health information. The digital chips, analog ICs, microprocessor,
wireless antennae,
sensors, microprocessor and essential electronics components of the apparatus
109 are
packaged in the heat regulating case 110. The foam base on the contact surface
around the
biosensors, is utilized to reduce movement noise in the bio-signal recording,
and as well to
improve the clinical hygiene and reusability efficiency.
(Multifunctional clinical instrument for live and telemetry monitoring)
[0099] FIG. 8 is the live and telemetry clinical monitor, that can display
real-time medical
signals as well as personalized results. The live clinical monitor has a
central wireless base
station 116 and an inflatable mini-cuff 113 packaged with set of biosensors
114 (electrical
spectrometer, optical spectrometer, non-contact MEMs/NEMs temperature sensor,
accelerometer, etc). The digital ICs, analog chips, power supply unit,
sensors,
microprocessor, wireless antennae and other electronics are packaged inside
the wireless
base station 116. At the contact of the user, the mini-cuff 113 automatically
inflates to
detect the resonant point for blood pressure calibration. The bio-signals are
extracted
through the set of biosensors 114. A slate sized touch display 117 is
assembled on the
wireless base station 116, which is utilized for accessing and viewing
important clinical
information, patient history, patient's physical activities, health data and
live medical
signals (like breathing rate, heart rate, oxygen saturation, bio-temperature,
blood pressure,
blood sugar levels, neural activity balance, etc). The slate sized touch
display 117 is also
used at the means to operate the medical instrument and to access the in-built
applications.
The base station 116 along with the slate sized monitor 117 and buttons 118-
119, is attached
to the mini-cuff 113 both wirelessly or through an electrical cord 115. The
button 118 on
the base station 116 resets the medical analysis, powers on/offthe device and
executes other
important functionalities. The patient history, medical information and other
important
information are synchronized, between mobile telemetry apparatus and computer
server/accessoriai mobile apparatus, through the button 119 on the base
station 116.
(Smart band embodiment form of the telemetry apparatus)
[0100] FIG. 9 is the preferred wearable embodiment form for remote clinical
monitoring and
daily well-being management. FIG. 9A shows the isometric front view of the
smart band
embodiment form. FIG. 9B shows the isometric back view of the smart band
embodiment
form with reflective hardware apparatus. The device comprises of mini touch
display 120,
trigger button 121, mode-indicator 122, wireless synchronization button 123,
micro/mini-

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inflatable strap 126 and Stress Management blinking LED set 124-125. The mini-
touch
display 120, placed on the top surface of the apparatus, is utilized for
operating the
apparatus, accessing in-built application and viewing the essential
information (such as
medical information, health data, bio-signals, general wellness data, etc). A
set of Red
indicator LED 124 and Green indicator LED 125, attached on the top surface,
are used as
an apparatus guided method for stress management. The indicator LEDs of 124-
125
automatically blinks to guide the user during the instances of psychological
stress or anxiety.
During the state of mental stress, the red indicator light 124 automatically
flashes at the
detected neural activity and the green indicator light 125 automatically
flashes in a definite
assisting pattern. For guiding the user through stress management, the green
indicator light
125 blinks with a 7.5%-25% higher ON time to indicate breath-out
demonstration, and
7.5%-25% lower OFF time to indicate breath-in demonstration. The strap-based
micro/mini-inflatable cuff 126 automatically inflates to detect the resonant
compression
point for blood pressure calibration. The mode indicator light 122 shows
different operating
modes and other functional status of the apparatus. The trigger button 121 is
utilized for
operating the device, accessing in-built applications and utilizing other
functionalities. The
apparatus has a wireless button 123 for synchronizing the data and telemetry
device with
the accessorial devices. The biosensor set and reflective sensing apparatus
128 (of optical
apparatus, electrical, non-contact temperature sensor and accelerometer) is
assembled on
the contact surface of the device. The digital ICs, analog chips, power supply
unit, sensors,
microprocessor, wireless antennae and other electronics are packaged in the
casing 127.
(Smart wearable embodiment form of the telemetry apparatus)
[0101] FIG. 10A shows the start-up application and rounded corner smart mobile
apparatus
design for general wellness management and telemetry medical monitoring. The
mobile
apparatus 132 has a potentiometer integrated crown 133 and push buttons 134-
135, which
are utilized as the means to operate the apparatus 132 and access in-built
applications. The
real-time diagnostic signals, health management data, medical data and other
important
information are viewed on the mini-touch screen 136. The mini touch display
136 is also
used as the means to operate the device 132, and device applications. A
background
application containing motivational quote 137 is displayed on the top of the
apparatus 132,
which is intended to improve the spirit of the user. The diagram also shows a
start-up
application comprising information on Time & Date 138, Step Count 139, Calorie
burnt

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26
140, Calorie consumed 141, weekly health history 142, battery strength 143,
climate
information 144, wireless connectivity 145 and other trends.
[0102] FIG. 10B shows the placement of the reflective sensing apparatus on the
mobile
apparatus with rounded corner design. The reflective sensing apparatus 146 is
assembled
in an optimal sensing spot 147 on the contact surface 148 ofthe apparatus 132.
The rounded
corners 149-150-151-152 of the apparatus 132 are chosen as a means to evade
cuts and
injuries, that may occur due to the otherwise sharp corners.
[0103] FIG. 11A shows the start-up application and round face smart mobile
apparatus design
for general wellness management and telemetry medical monitoring. The mobile
apparatus
153 has a potentiometer integrated crown 133 and push buttons 134-135, which
are utilized
as the means to operate the apparatus 153 and access in-built applications.
The real-time
diagnostic signals, health management data, medical data and other important
information
are viewed on the mini-touch screen 136. The mini touch display 136 is also
used as the
means to operate the device 153, and device applications. A background
application
containing motivational quote 137 is displayed on the top of the apparatus
153, which is
intended to improve the spirit of the user. The diagram also shows a start-up
application
comprising information on Time & Date 138, Step Count 139, Calorie burnt 140,
Calorie
consumed 141, weekly health history 142, battery strength 143, climate
information 144,
wireless connectivity 145 and other trends.
[0104] FIG. 11B shows the placement of the reflective sensing apparatus on the
mobile
apparatus with round fare design. The reflective sensing apparatus 146 is
assembled in an
optimal sensing spot 154 on the contact surface 155 of the apparatus 153. A
round face and
bezel 156 of the apparatus is chosen as a means to evade cuts and injuries,
that may occur
due to the otherwise sharp comers.
[0105] Series of Figure 12 shows the embedded health management and clinical
monitoring
applications of the smart wearable embodiment.
[0106] FIG. 12A is the cardiac training software application of the smart
wearable apparatus.
During physical training, the cardiac training application automatically
tracks both
quantitative and qualitative data such as training intensity 157, training
period 158, rest
period 159, cardiac rate 160, training phase 161 (such as distance travelled,
average speed
count), sets and reps counts 162 and other important health data.

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[0107] The training session begins on the long hold of the trigger push
buttons 134-135, and
the real-time training data is recorded. The tracked data is displayed on the
mini screen 136.
On a subsequent short press of 134-135, the tracking switches between rest and
intensity
period, and a long hold of the push button 134-135, the tracking period halts.
The apparatus
either ends the activity tracking on a successive small hold of the push
button 134-135 or
resumes the tracking on a successive long hold of the push button 134-135. The
mini-touch
display 136 is used as an alternative means to operate the commands of the
application.
[0108] FIG. 12B shows a persona oriented psychological stress management
application. The
mobile apparatus's mini screen 136 displays queued work schedule with priority
rating 163,
real-time stress levels (Emotional Index meter) 164, and information on stress
levels and
stress management 165. The user initially marks several reference data points
to train the
smart apparatus for learning the persona-oriented stress levels. The real-time
stress levels
are generated through previously marked subjective data points. The reference
data points
are generated based on the analysis of biosensor and other vital information.
Based on the
reference points and real-time signals, the apparatus generates subjective
psychological
stress data 164. On recognizing the state of stress or anxiety, the
application automatically
guides the user to a stress management method. The push buttons 134-135, crown
133 and
mini-touch display 136 are utilized as the means to mark the stress data
points, to navigate
through the work schedule and to operate the functionalities of the
application.
[0109] FIG. 12C shows the sleep management application of the smart wearable
apparatus.
The real-time sleep information 166 is automatically recorded and displayed on
the screen
136, along with an accessorial user configured alarm control 167. A morning
motivational
quote 168 is displayed on the screen 136 to keep the user inspired. The push
buttons 134-
135, crown 133 and mini-touch display 136 are used as the means to set the
alarm, access
the logged data, view the recorded data and as well to operate the
functionalities of the
sleep management application.
[0110] FIG. 12D shows the mobile application of the smart wearable apparatus
to view live
medical information and access logged data. The recorded and real-time vital
information
169 of pulse rate, oxygen saturation ratio, breathing rate, body temperature,
heart rate
variably, blood sugar data, blood pressure data and Neural Activity are
displayed on the
mini-screen 136. The push buttons 134-135, crown 133 and mini-touch display
136 are
utilized as the means to access the logged data and operate the
functionalities of the live
monitoring application.

PPH
28
(Network of Computational and Storage Devices)
[0111] FIG. 13 shows wireless devices network based parallel computation
method to compute
and extract information more quickly. The Telemetry device 170 sends and
receives data
to/from the server computer 171 and the other accessorial devices 172 via
BLE/WLAN,
GSM and other techniques. The accessorial mobile apparatus 172, server
computer 171 and
other network of devices are utilized for computing and storing the
information. The
network of devices based computational and storage method is used as a faster
and efficient
means to compute and store information. The communication channel between the
170 and
172 is established via central server 171 or directly through the wireless
pathways.
[0112] FIG. 14 shows the application of the telemetry device for remote
clinical monitoring
purposes. The recorded real-time information, clinical information, health-
data and user
input information are wirelessly sent to the hospitals 175 from the wireless
medical device
173 in a remote location 174. The clinical advice, medical instruction and
other information
are sent wirelessly from the Medical Centre/Hospitals 175 to the Telemetry
device 173
located in Remote Location 174.
[0113] FIG. 15 shows the application of the telemetry devices in a crowded
hospital scenario.
The medical practitioners 177 can attach medical devices of 173 to the
patients in the rooms
R1 178, R2 179, R3 180, R4 181 and in many such rooms in the patient's
clinical
compartment 176b. The recorded real-time information, clinical information,
health-data
and user input information are wirelessly sent from the wireless medical
devices of 173 in
rooms of 178, 179, 180, 181 and in many such rooms to the physician's room
176a with
telemetry monitor and base station 175. The real-time medical information,
patient's
history, patient's information, diagnosed clinical condition and recorded
medical analysis
are viewed on the wireless telemetry monitor of the base station 175. The
clinical advice,
medical instruction, drug dosage recommendation and other important
information are sent
wirelessly from the Physician's compartment 176a or personally conveyed to the
patient
The information can be communicated wirelessly between the medical
practitioners 177,
patients (in 178, 179, 180, 181 and many such rooms) and physician's room 176a
in lesser
time and more efficiently compared to the typical clinical and hospital set-
up. This scenario
shows that clinical analysis of patients in multiple rooms of 178, 179, 180,
181 and many
such rooms in the patient's compartment 176b can be conducted and analyzed in
lesser
time with lesser efforts and with more efficacy.
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29
(Real-time System)
[0114] FIG. 16A is the signal processing flow diagram which describes the
utilization of
accelerometer signals as a real time feedback to remove the motion errors from
the bio-
signal. Accelerometer signals are recorded along with other bio-sensor data
with their
respective sampling rate. The sampled bio-signal is initially passed through a
50/60 Hz
Notch filter to remove the power line noise disruption. The bio-sensor data
and angle
calibrated accelerometer data is processed with a normalized parameter based
repetitive
adaptive filter and other computational method to remove low frequency motion
noise from
the bio-signal. A first order noise free bio-signals are obtained after the
correlation of the
angle calibrated accelerometer data with bio-sensor data with a delay through
a normalized
parameter based least mean squaring based adaptive filtering. The first order
noise free bio-
signals obtained, after removal of the movement error (A"(n)) i.e. the motion
noise, is
processed through later mentioned flow diagrams to further remove motion noise
or
movement errors associated with the bio-sensor data.
[0115] FIG. 16B is the flow diagram to process accelerometer values to compute
the movement
activity of the user or patient. Normalized magnitude for amplitude of the
recorded
accelerometer signals is computed and then the base line errors are removed.
Then, a data
based computational method and peak detection algorithm is applied to the
processed data
to calculate the active movement data. As described in FIG. 16B, the data
based
computation method is detecting a deviation from a mean of the normalized
magnitude
dataset (i.e. processed data of the 9/6-axis accelerometer) and then peaks
within the
deviation dataset of the normalized magnitude dataset are detected to obtain
the active
movement data (i.e. step movements and also number of steps).
[0116] FIG. 17 is the flow diagram to process the first order motion artefact
free bio -signal to
compute avg. pulse rate, instantaneous heart rate, pulse rate variability and
neural activity
coefficients. The first order signal is passed through a series of banked and
low pass filter
to remove the rest of the noise in the bio-signals. Then, a data correlation
method is applied
between the processed bio-sensor data and accelerometer data to further remove
the motion
artefact noise from the original signal. A peak detection algorithm is applied
to the 3"' Order
processed motion artefact free signal to compute average, pulse rate and
instantaneous heart
rate. The recorded heart rate time intervals are plotted to display the pulse
rate variability
and HR Tachogram. A variance-based data method is applied to the derived pulse
rate and
variability data for computing the autonomous neural activity coefficients of
al, a2, a3,
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a3/ al, a3/ 02, a2/ al. As described in the flow diagram of FIG. 17, after
sending the first
order signals (or first order noise free bio-signals) through a series of
banked filters with
dynamic parameter (M), a second order noise free bio-signals are obtained. A
correlation
factor (Corr) is extracted by correlating the second order noise free bio-
signals with a delay
and the angle calibrated accelerometer signals, which is anlayzed to obtain a
movement
error free bio-signal responses. Then, a data correlation method of the
accelerometer data
operation on the second order noise free bio-signals is applied to obtain
noise data (M'(n))
and the noise data is removed to extract energy undistorted values of a third
order noise
free bio-signals. The autonomous neural activity coefficient of al is
extracted by
computing a root of a mean of a differences between an adjacent values of the
time intervals
of the time intervals dataset. The autonomous neural activity coefficient of
a2 is extracted
by computing a mean of the time intervals of the time intervals dataset. The
autonomous
neural activity coefficient of a3 is extracted by computing a root of a mean
of a deviation
of the time intervals of the time intervals dataset from the a2.
[0117] FIG. 18 shows the low powered computational method to extract
continuous heart Rate,
avg. pulse rate and oxygen saturation levels. The 3th Order signal is sampled
at chosen
sampling rate and recorded in 32/64/128.... data points. A discrete wave
transformation is
applied to the processed signal and a selection matrix is operated on the
resulting frequency
domain signal. The operation of selection matrix significantly decreases
computational
effort needed to analyse the entire waveform, and an iterative peak detection
algorithm is
applied to the processed signal to determine maxima's frequency and thereof
continuous
heart rate and average heart rate are extracted. The signal ratio between the
oscillating peak
and stationary peak of red and Infrared biosensor is taken to determine the
oxygen
saturation ratio. The mean of the determined oxygen saturation ratio (i.e.
continuous
oxygen saturation) from the third order noise free bio-signals is extracted to
obtain an
average oxygen saturation (Avg. Sp02).
[0118] FIG. 19 shows band-pass digital filters and power spectrum analysis
methods to process
Inverted tachogram data (i.e. frequency domain signal of Instantaneous heart
rate). The
reconstructed frequency domain signal is divided into High-Frequency, Low-
Frequency,
Very Low Frequency, Meyer band and Ultra-low frequency signals using the high
pass,
bandpass and low pass digital filters of corresponding bandwidths. Then, the
relative power
under each frequency spectrum is calculated to assess neural activity. The
derived
coefficient of Pi, P2, P3, P4, etc are evaluated through a set of
computational steps to
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31
determine the overall health of Autonomous Neural System and cardiac system.
The
autonomous neural activity parameters of P1, P2, P4 and P5 are respectively
obtained by
extracting the power spectrum under the low frequency, the high frequency, the
very low
frequency and the ultra low frequency band signals. A ratio of P1 to P2 is
taken to obtain
P3.
[0119] FIG. 20 shows the flow diagram and analysis method to compute and
display
respiratory signal, continuous respiratory rate, meyer wave signal and average
breathing
rate. The noise-free pulse bio-signals are analyzed for extremum to decouple
the noise
artefact free signals into different wave signals. An iterative wave
decoupling algorithm is
applied to the pulse signal to obtain the low frequency breathing signal. The
derived signal
is processed for peaks and experimental parameter to determine the respiratory
rate. The
analysed signal is mathematically operated for computing average breathing
rate,
continuous respiratory rate and breathing rate. A similar analysis is applied
to decompose
the meyer wave signal and its related neural parameters. This method of
computational
wave decoupling is low powered, and the accessorial mobile/server
computational devices
are utilized to improve the response time of the medical apparatus. As
described in FIG. 20,
the decoupled waves obtained after the iterative analysis with the extremum
(of interpolated
maxima and minima of the local maxima and the local minima), is evaluated for
a breathing
signals frequency range to obtain the breathing signals (r1uR(0).
[0120] FIG. 21 is the flow diagram and computational technique to measure
blood pressure
data from previously calibrated user data. The user calibration input, optical
data and
extremum of the samples with respect to time are recorded. The user input and
recorded
optical data are employed to calibrate the biosensor reading. In all device
configurations,
the method of optical intensity ratio between the extremum is utilized to
calibrate the blood
pressure values of continuous blood pressure and diastolic pressure. The dual
sensor
configuration is utilized to estimate momentum loss in the blood vessel, mean
pressure and
the systolic pressure. The recorded heart to device reference length is used
in the cuff-based
apparatus to accurately measure the mean arterial pressure.
[0121] As described in the flow diagram of FIG. 21, a mean of a corresponding
ratios of the
minima dataset to the maxima dataset of the extremum dataset (recorded with
respect to
time) is correlated with measured diastolic blood pressure values in real-time
and a
measurement coefficient (Z) to extract the real-time diastolic blood pressure
(i.e. the
utilized method of optical intensity ratio between the extremum). In the dual
sensor
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32
configuration (i.e. optical spectrometer A and optical spectrometer B) to
estimate
momentum loss in the blood vessel, mean pressure and the systolic pressure, a
time
intervals datasets for a corresponding bio-signal response between the
extremum datasets
of optical spectrometer A and optical spectrometer B is recorded. Then, a
ratio of a mean
of the time intervals to the distance (d) between the dual sensor (i.e.
optical spectrometer
A and optical spectrometer B) is taken to obtain a Mean Longitudinal Pulse
Velocity (Long.
Vpube). The mean longitudinal pulse velocity and the real-time diastolic blood
pressure are
correlated to extract the real-time mean arterial blood pressure and the real-
time systolic
blood pressure. A ratio (K) between the measured and calibrated values is used
to improve
the accuracy of the real-time blood pressure values. Alternatively, recorded
heart to device
reference length is used in the cuff-based apparatus to accurately measure the
mean arterial
pressure that is obtained by correlating the cuff pressure and the blood
density at the
resonant point i.e. Pcuff +pghr. In this case, a standard value of blood
density (p) or user
input on the same is taken for computations in cuff based apparatus. The heart
to device
reference length (hr) can also be obtained automatically by analysing the real-
time signals
from the 9/6-axis accelerometer in different arm positions of user (which is
described in
the next flow diagram and their relevant description).
[0122] FIG. 22 shows the flow diagram to automatically calibrate the heart to
device reference
length, that is employed to compute blood pressure. The value of 9-axis
accelerometer
sensor signals are recorded at different arm positions of bent arm position,
fully stretched
arm position, lifted arm position and straight down arm position. Using the
recorded sensor
data, the forearm and arm length are calculated, through which average heart
to device
reference length is generated.
[0123] FIG. 23 shows the flow diagram and method to process the near-infrared
bio-sensor
signals and other optical signals to compute blood sugar levels. Initially the
input on the
present blood sugar level is taken for sensor calibration. The Green LED, IR
LED and Red
LED response signals are used to compensate the intensity losses due to the
blood flow
fluctuations, tissue absorption and other coherent errors. The Processed Near-
Infrared data
is correlated and fitted over various patient's/user's/physician's inputs to
calibrate the
biosensors for approximate real time Blood Sugar values. Physiological
threshold values
of hyperglycemia and hypoglycemia are analyzed from the calibrated data. The
system
automatically reminds the patient for medication and alerts the user/user
network or the
physician about the diagnosed health condition.
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33
[0124] FIG. 24 shows the flowchart and computational process to record various
stages of the
sleep cycle and to recognize obstructive sleep apnea Conditions. The
accelerometer values
are initially verified to make sure that user is in sleeping or dormant
position. Then the real
time physiological signals of (oxygen saturation ratio, body temperature,
blood glucose
levels, blood pressure, etc) are compared to state of wake, sleep and activity
data to verify
the state of sleep and rest. After the verification process, the real time
physiological signals
of avg. breathing rate, avg. systolic blood pressure and instantaneous heart
rate signals are
processed to track the time periods of non-rapid eye movement and rapid eye
movement
sleep cycles. Then a series of methodical computational steps are applied on
the
instantaneous heart rate, sleep cycle and respiratory rate data to recognize
sleep apnea
conditions and to calculate the time-period of sleep apnea. The pulse rate
data in a time
interval of 30-60s and for 5-7BPM difference is analyzed to recognize sleep
apnea
conditions. The respiratory signals are validated for sleep apnea conditions
after pulse rate
and instantaneous pulse rate data analysis. The recognized sleep health
conditions and time
period are recorded. Once the mild to severe symptoms of OSA are recognized by
the
apparatus, a warning message is sent to the patient and her/his physician
network.
[0125] In the series of methodical computational steps applied on the
instantaneous heart rate,
sleep cycle and respiratory rate data to recognize sleep apnoea conditions and
to calculate
the time-period of sleep apnoea, the instantaneous heart rate dataset is
anlayzed in one or
more time frames, for a specified range of beats per minute difference between
their
extremum, and for a falling edge and a raising edge in a cycle time. As
mentioned before,
the specified range of beats per minute (BPM) is in range of the 5-7 BPM, the
cycle time
is at 9.5 seconds and the time frames (i.e. time intervals) are kept at 30-60
seconds followed
by time frames of 20-120 seconds. The time periods of sleep apnoea are
recorded on
recognition of the sleep apnoea conditions (TApnea= to ¨ tn ). As mentioned
before, a pattern
of an average respiratory rate dataset (i.e. respiratory signals) further
verifies or validates
the sleep apnoea conditions. A low and irregular pattern of the average
respiratory rate
dataset is used for verifying the sleep apnea conditions. Also, initially
during the sleep
recognition processing, the vital information of average heart rate, average
respiratory rate,
blood pressure levels, oxygen saturation, blood sugar levels and body
temperature are
anlayzed for a realistic range while analysing the real-time signals of the
9/6-axis
accelerometer to verify that the Sleep Tracker is ON and the user is a
sleeping and dormant
state. The median values of 1x, dy, dz obtained from accelerometer values over
a period
Date Recue/Date Received 2023-06-26

PPII
34
of time are evaluated against the heart to device reference length (hr) or
null values to verify
the sleeping and dormant state.
[0126] FIG. 25 illustrates the basic low powered flow diagram that is utilized
in
multifunctional medical device, telemetry apparatus and general wellness
management
applications. Initially, the values of the vital signals like pulse rate,
continuous heart rate,
pulse rate, avg. heart rate, oxygen saturation ratio, neural activity,
breathing rate, blood
pressure data and blood sugar levels are extracted using the previously
described
computational methods. The realistic value of biological signals are verified
to check if the
worn by the user. The device automatically restarts on recognizing realistic
value, else it
remains in or goes to the sleep and shut-down mode. The device also
automatically alerts
user's life-support network and social on detecting clinical emergency risks.
[0127] FIG. 26A, FIG. 26B and FIG. 26C shows an automated life-support method
for
recognizing user activity, pre-clinical emergency conditions and for recording
one's state
of well-being. Initially, the sensor values are processed and calibrated. The
sensor data,
accelerometer values, GPS antenna, wireless antenna and bio-signals are
evaluated for
recognizing various postures and movement data (of sitting, standing, number
of steps,
number of strides, lap count, speed, training phase, resistance training,
cycling, driving,
etc). The recorded physiological information and motion sensor data are
further processed
and learnt by the device for precisely evaluating the postures, fatigue
condition, rest period
and activity period of the user. The postures, activity state, training data
and other computed
information are learnt and recorded_ The circadian errors are removed from the
derived data
and the health of circadian cycle is evaluated using a learning method. The
electrical signals
and optical signals are correlated and corrected to rectify the errors in the
bio-signal data.
Then, the system computes BMR data and calorie expenditure from the computed
vital
signals and physical activity. A learning method of the system automatically
derives the
low-powered bio-signal processing methods and life-support process. The system
detects
the state of mental stress or anxiety utilizing the EEG patterns, recognized
cortisol level,
respiratory patterns and HRV patterns. If the user triggers for new stress
threshold, the
device records new stress mark-ups Based on the bio-signal data and stress
mark-ups, the
system derives subjective stress levels. On recognizing the state of mental
stress, a guided
breathing stress management technique is presented to the user that functions
on the
individual's real time vital signals or the user is diverted to a stress
management support
network and social media. The clinical life-support component of the system
automatically
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recognizes the risk of CHF attacks, hypoxia, hypothermia, hypoxemia, blood
poising, blood
loss, hyperthermia, unusual ventricular activity, heat stroke, nervous
breakdown and other
chronic conditions from oxygen saturation data, pulse rate, breathing data,
neural
parameters and HRV data pattern. If a life threating or chronic clinical
condition is
recognized, the apparatus automatically alerts the user's network and life
support network_
[0128] Elaboration of the description of the processing as written in flow
diagrams of FIG.
26A, FIG. 26B and FIG. 26C is provided in this paragraph. The device i.e.
apparatus is sent
to start or wake up mode after detecting a realistic range of bio-signals from
the biosensor
set. For first few times, a plurality of inputs from the user on clinical and
health data for
biosensor calibration and learning parameters calibration are recorded. If
already sufficient
inputs on inputs from the user on clinical and health data is recorded, the
recordings of
inputs are skipped. The vital data (i.e. plurality of vital signal data) of
the heart rate, the
respiratory rate, the blood pressure levels, the blood sugar levels, the
oxygen saturation, the
neural activity parameters and the body temperature are computed and stored.
The vital
signal data and the real-time signals of the 9/6-axis accelerometer are
calibrated to detect a
plurality of user positions and movement data comprising a sleeping state, a
sitting position,
a standing position, a running state, a sprinting state and a resistance
training state. If
already calibration is accomplished, a plurality of user positions and
movement data is
recognized. The step movements are analyzed to infer user positions, user
postures, user
state and user activity. At null step movement (i.e. step = 0); a pattern of
the heart rate, the
respiratory rate and the blood pressure levels (i.e. vital signal data) is
analyzed to detect
whether user is in the sleeping state, the sitting position or the standing
position. At null
step movement (i.e. step = 0); Avg. speed (average speed) is evaluated with a
human
physical limit to detect a cycling or a driving mode. The vital signal data is
further analyzed
to infer the cycling mode or the driving mode. At step movements (step > 0),
the average
speed and the vital signal data are analyzed to detect a walking, a running or
sprinting state.
The plurality of user activity, posture and the movement data is verified by
applying an
unsupervised learning on the heart rate pattern. The stored values of the GPS
and the real-
time signals of the accelerometer is analyzed to detect a number of laps, the
value of laps,
a number of strides or steps per minute and a minutes per laps count
(minute/lap count).
The state of fatigue is detected based on vital signal pattern and real part
of the impedance
response. The vital signal pattern of the heart rate, the respiratory rate and
the real part of
the impedance response is analyzed to record and display a threshold index on
the El meter.
Date Recue/Date Received 2023-06-26

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36
On recognizing a stress state, the apparatus automatically guides the user to
a guided
breathing technique with an increased breath-out and decreased breath-in
pattern, a
meditation video and a social chat or call. If mark-up is triggered, a new
threshold index is
stored. The real-time blood sugar levels are anlayzed to detect a
hypoglycaemia state and a
hyperglycaemia state. A pattern of the heart rate, the respiratory rate, the
SNS/PNS, the
neural parameters and the impedance response are anlayzed to detect a
Congestive Heart
Failure condition. A decreasing pattern of the oxygen saturation, an
increasing pattern of
the heart rate and the respiratory rate (i.e. fast breathing) is anlayzed to
detect a CO poising
condition. A low levels of the oxygen saturation, a fast unsteady pattern of
the respiratory
rate and an increasing pattern of the heart rate is anlayzed for detecting a
hypoxia condition,
a hypoxemia condition or a blood disease condition. A reducing pattern of the
body
temperature and the heart rate is anlayzed for detecting a hypothermia
condition. An
increasing pattern of the body temperature, the heart rate and the respiratory
rate (i.e.
increasing unsteady breathing) is anlayzed to detect a hyperthermia condition.
A threshold
of the SNS/PNS and the real part of the impedance response is anlayzed to
detect an anxiety
and a seizure state. A basal metabolic rate (BMR) value is derived and stored
from heart
rate data. Calories burnt is computed/obtained based on BMR value, distance
commuted
and intensity of physical exercise. The BMR generated from the most accurate
heart rate
result is used for analysis. The imaginary impedance from the electrical
spectrometer is
used as a feedback for the optical spectrometer to compute/obtain more
accurate vital signal
data. A data correlation is applied between the processing steps and
computations of the
optical spectrometer and the electrical spectrometer to detect low powered
methods for
computations and processing. An unsupervised learning is applied to remove
errors due to
circadian cycle and to analyse the health of circadian cycle health. The
apparatus
automatically sends a warning message to the user eco-system, the emergency
contacts of
the user and the user on recognizing health and emergency conditions.
(Accessorial Mobile Device and Software Application)
[0129] Series of FIG. 27 are the software applications of the accessorial
mobile apparatus
attached to the telemetry apparatus.
[0130] FIG. 27A shows the accessorial software, which displays important
logged and
processed information on user's or patient's heath. The user can log and track
their personal
Date Recue/Date Received 2023-06-26

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37
information 182, routine health check-up data 183 (like weight, height, Basal
Metabolic
Index, Basal Metabolic Rate, workout target), physical exercise activities
184, and nutrition
intake 185. The mobile apparatus shows real time and recorded health data 186
of the user
or patient that includes base heart rate, distance commuted and calories
expenditure. This
information can help the user, patient or health advisor to measure the
intensity of the
physical exercise and progress of the therapy or fitness program. The cloud
synchronization
button 187 is utilized to synchronize the data with the cloud services and to
share the data
with professionals.
[0131] FIG. 27B shows the software application interface for the stress
management in
professional environment. It can be also employed by patients suffering from
hypertension.
The emotional index meter 189 is shown on the left, which shows persona-
oriented
measurement. The emotional index meter 189 oscillates according to the neural
balance
and other calibrated bio-signal. As the stress meter 189 reaches the
threshold, the device
directs the user to real time bio-signal based guided breathing/meditation
method 188 or to
a social communication interface. The progress on the stress management
program is
reported in tracking meter 190 shown at the center bottom of the diagram. The
daily work
management feature 191 is displayed on the right half, which shows the
scheduled activity
and their priority recorded by the user. The work management functionality is
included,
since procrastination is considered as an indirect counterpart cause of mental
stress.
[0132] FIG. 27C shows the accessorial software to track and monitor sleep. As
described
earlier in the computational flow diagram section, the sleep cycle and other
related data are
computed using the biosensor signals. The recorded sleep cycle trend 192 and
NREM-REM
cycle length 193 are displayed, with access to sleep data log 194. In case of
sleep disorder
related clinical conditions, a warning message regarding the disorder symptom
appears on
the user screen. The user can connect with physicians and health professionals
by clicking
on the 195.
[0133] FIG. 27D shows the accessorial mobile device interface to monitor vital
signals 196 of
pulse rate, oxygen saturation, pulse rate variability, neutral activity,
breathing rate, body
temperature, blood glucose levels and blood pressure levels. The biosensor
data is either
processed by the mobile apparatus, central server or other accessorial
wireless
computational device. The computed real-time and recorded results 196 are
displayed on
the screen along with navigation access to view the individual physiological
signal wave
form. The medication tracker/remainder 197 (on centre bottom of the screen)
and
Date Recue/Date Received 2023-06-26

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38
physician's network 198 (right bottom of the screen) are included to enhance
the clinical
management experience of the patient. The user can connect with medical and
health
professional by clicking on the button 198. The medication tracker and
reminder 197
records the medication pattern and medication reminder. The device
automatically alerts
the user at the correct time to take medication. The data can be shared on
online platforms
and with medical and health professionals by clicking on 199.
[0134] FIG. 27E shows the accessorial software interface to connect with
health advisor
network. This application interface enables professional medical practitioners
200,
dieticians 201, fitness instructors 202 and other health advisors to interact
with the user,
and to guide them with health practices/therapies. The health blogs, articles
and classes can
be accessed by the user through clicking on the icon 203.
[0135] FIG. 27F shows the user application interface for daily health
management. It displays
information on the number of active steps taken 204, sleep health 205, heart
rate with
oxygen saturation ratio 206, and emotional index matrix 207. The El matrix 207
is the real-
time information and recorded patterns of the emotional status and stress
condition of the
user. The background information on daily well-being can be accessed by the
user by
clicking on the left bottom button 208 (which can be evaluated to improve
one's state of
general health). The progress and history of the user can be accessed by
clicking on the
history trend button 210. The work schedule is organized by clicking on the
center bottom
work schedule button 209.
[0136] FIG. 27G shows the ease of lifestyle organization application
interface, which displays
the functionalities to synchronize, install and manage 3' party and native
applications on
the telemetry mobile apparatus.
[0137] The above described invention disclosure is intended for illustration
purposes, and for
those skilled in the art may instantly perceive numerous modifications,
variations and
equivalents. Therefore, the disclosure is not exhaustive in broader aspects
and the invention
is not intended to limit to specific details, illustrated hardware designs,
described
computational methods and embodiment forms. All equivalents and modifications
are
intended to be included within the scope of disclosure and attached claims.
Accordingly,
additional changes and modifications may be made without departing from the
scope or
spirit of the invention disclosure appended in the document, claims and their
equivalents.
Date Recue/Date Received 2023-06-26

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39
Industrial Applicability
[0138] The described technological invention can be utilized as telemetry
clinical
instrumentations, general wellness management devices, real-time diagnostic
technology,
portable medical apparatuses, well-being management gadgets, smart wearable
devices,
server based real-time clinical diagnosis and health tracking system, life-
support devices,
health tracking software device and software medical device.
Prior Art and Citation List
[0139] CN 204467155 U (Kiwi Field (Hong Kong) Co. Ltd) 19-01-2011
[0140] US 006122536 A (Animas Corporation) 19-09-2000
[0141] US 006819950 B2 (Alexander K. Mills) 16-11-2004
[0142] US 20120041276 Al (Delcina Doreus and Evon Doreus) 16-02-2012
[0143] WO 2015167251 Al (Huino Corporation) 05-11-2015
[0144] Shubhangi Shripati Kadam and Sameer S. Nagtilak. "Non-Invasive Blood
Glucose,
Blood Pressure, Heart Rate and Body Temperature Monitoring Device", India,
URITCC,
Apr 2017, Vol 5, Issue 4, ISSN 2321-8169, Pg. 69-72
Lexicography and Clarification of Terms:
[0145] The following clarification and lexicography are presented and
discussed in general
terms in an effort to ease comprehension of the matters and claims in the
current disclosure:
i. El, E2, E3 and E4 electrical sensors are respectively referred to as
first electrical sensor,
second electrical sensor, third electrical sensor and fourth electrical
sensor.
WLAN indicates wireless local area network that establishes wireless internet
connection for communication and data transfer.
iii. A mobile communication module indicates a global system for mobile
communication
(GSM) that establishes wireless connection for communication and data transfer

through mobile communication/cellular towers.
iv. GPS indicates global position system that wirelessly captures the
location or position
information through satellites.
Date Recue/Date Received 2023-06-26

PM
v. These
wireless connections through these wireless antennae as per the disclosure of
the priority
include a self-assembling and automated wireless reconfigurable connections
(or) through
reconfigurable modules.
Date Recue/Date Received 2023-06-26

Representative Drawing