Note: Descriptions are shown in the official language in which they were submitted.
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INTELLIGENT DRUG DELIVERY SYSTEM
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation-in-part application of
U.S. Patent Application No.
16/593,020, filed October 4, 2019, which is hereby incorporated by reference
in its entirety.
TECHNICAL FIELD
[0002] The present disclosure generally relates to a controller and
associated sensor system
based on lifestyle event detection, and more particularly relates to a
controller and associated
sensor system for augmenting the automatic delivery of drugs based on the
detection and
determination of particular lifestyle events (a Pump Augmentation System
(PAS)). In one aspect,
the controller and associated sensor system relates to the operation of
insulin pumps, and more
particularly relates to an Insulin Pump Augmentation System (IPAS) for
assisting insulin pump
delivery of insulin to a user based on lifestyle event detection. In another
aspect, the controller and
associated sensor system relate to an Intelligent Drug Delivery System (IDDS)
for collecting
patient motion information and providing a continuous medicinal infusion pump
with patient
motion feedback information in order to effectuate a closed-loop dosage
determination.
BACKGROUND
[0003] Despite the progress of diabetic management via an insulin
pump, even after the
introduction and integration of continuous glucose monitoring with a "closed
loop- approach, there
still remains a disconnect between the capability of conventional insulin pump
systems to
satisfactorily detect and compensate for changing physiological, lifestyle,
and exercise of an
individual. All of these situations frequently result in unexpected raising
and/or lowering of blood
glucose levels, often times such that the blood glucose levels are outside of
their desired, targeted
or acceptable glucose ranges.
[0004] As an example, the everyday act of simply awakening for an
individual triggers a
release of hormones that characteristically causes a person's blood glucose
level to rise. In a non-
diabetic individual, the blood glucose levels are organically adjusted so
these situations go
unnoticed. In a diabetic individual, however, there is no (or only a limited)
physiological
mechanism that recognizes and compensates for such circumstances. Currently,
treatment of
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diabetes generally relies on an "after the fact- corrective measures to bring
the changing blood
glucose levels back to normal ranges.
[0005] In contrast to the need to treat rising blood glucose levels,
diabetic individuals also
continually face the opposite problem, even with "closed-loop- insulin pump
therapy. Normal
physical activity such as working, walking, or exercising can frequently bring
a diabetic
individual's blood glucose level down to dangerously low levels. To complicate
matters even
further, in certain circumstances the same physical exertion during a period
of elevated blood
glucose levels can actually further increase the blood glucose levels to a
dangerous degree.
[0006] At its core, the overall control problem results from the
fact that insulin pumps follow a
rigid, time of day based delivery process for the continuous, or basal, rate
of insulin delivery, as
well as only being able to react to an abnormal glucose level after a
deviation has already occurred,
or is in the process of taking place.
[0007] At its best, conventional insulin pumps or closed-loop
insulin pumps are inherently
limited to indirectly reacting to changes in interstitial fluid glucose
levels, which are in of itself a
delayed measure of true blood glucose levels. Present treatment methods lack
the ability to
dynamically and automatically proactively increase or decrease an insulin
delivery rate, and
therefore such methods merely treat the consequential effects of lifestyle or
physiological activity.
[0008] Unlike many clinical treatments that are guided by empirical
clinical measurements
related to a patient's condition, Parkinson's disease does not have a defined
laboratory test upon
which to empirically judge either the progression of the disease and/or the
true efficacy of
treatments As a result, a Parkinson's disease clinician is forced to depend on
either a patient's
subjective self-evaluation of a change in condition and/or observations made
during a clinical
snapshot of the patient in order to evaluate a patient's condition in an
effort to determine whether a
medicine dosage adjustment is necessary in an effort to minimize or curtail
abnormal movement
symptoms. Unfortunately, such methods for basing dosage adjustments typically
result in dosages
that are in excess of what is actually required, which in itself creates
secondary complications.
[0009] The use of a conventional infusion pump to deliver
Parkinson's disease related
medication may offer limited benefits to a patient such as preventing missed
doses and/or
preventing inadvertent duplicate doses, but typically cannot be used to
deliver medication doses
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when a patient is sleeping. Even with the use of a conventional infusion pump,
there is still great
clinical uncertainty as to whether the correct/optimum dosage has been
determined, especially
during sleep periods when a patient is unable to provide self-observations and
not usually able to
be observed in a clinical setting.
SUMMARY
[0010] According to a first aspect, a controller based on lifestyle
event detection, and more
particularly a controller for augmenting the automatic delivery of drugs based
on the detection and
determination of particular lifestyle events may be provided.
[0011] For example, in one embodiment, an insulin pump augmentation
system may include a
body, an accelerometer sensor, a gyroscopic pitch sensor, and a controller.
The accelerometer
sensor may be arranged on the body and configured to output motion data based
on detected
motion. The gyroscopic pitch sensor may be arranged on the body and configured
to output
orientation data based on detected orientation. The controller may be in
communication with the
accelerometer sensor and the gyroscopic pitch sensor. Further, the controller
may be configured
to receive the motion data and/or the orientation data. The controller may be
configured to
generate a pump instruction signal based on the motion data and/or the
orientation data. The
pump instruction signal may include a signal to change an insulin delivery
rate of an insulin
pump.
[0012] The signal to change an insulin delivery rate of an insulin
pump may be a signal to
reduce or increase the flow of insulin, to start a flow of insulin, to stop
the flow of insulin, or to
deliver an insulin bolus amount.
[0013] According to another embodiment, the controller may be
configured to analyze the
motion data and/or the orientation data on a time weighted basis. Further, the
controller may be
configured to utilize a data pattern matching algorithm to provide a
determination of an
occurrence of a lifestyle event of a user. The data pattern matching algorithm
may utilize pattern
data previously entered by a user. The pump instruction signal may be based,
wholly or partly,
on the determined lifestyle event.
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[0014] The controller may also be configured to receive circulating
insulin level data
indicative of a level of insulin circulating within the user. The pump
instruction may be based,
wholly or partly, on the circulating insulin level data.
[0015] The controller may be configured to receive blood glucose
level data indicative of a
level of blood glucose level within the user. The pump instruction signal may
be based, wholly
or partly, on the blood glucose level data.
[0016] The controller may be configured to analyze the circulating
insulin level data and the
blood glucose level data. The pump instruction signal may be based, wholly or
partly, on the
analysis of the circulating insulin level data and the blood glucose level
data.
[0017] According to another aspect, the controller may be configured
to analyze the
circulating insulin level data and the blood glucose level data with regard to
the determined
lifestyle event. The pump instruction signal may be based, wholly or partly,
on the analysis of
the circulating insulin level data and the blood glucose level data with
regard to the determined
lifestyle event.
[0018] According to a further embodiment, the controller may be
configured to analyze the
motion data and/or the orientation data on a time weighted basis. The
controller may be
configured to utilize a data pattern matching algorithm to compare the motion
data with one or
more predetermined motion data patterns stored in the pump augmentation
system. The
controller may further be configured to determine at least one of a type of
food being ingested by
the user, a quantity of said food being ingested by the user, and a resultant
carbohydrate load
being ingested by the user. The controller may be configured to determine a
target amount of
insulin based on at least one of the determined type of food, the determined
quantity of food, and
the determined carbohydrate load. The pump instruction signal may be based,
wholly or partly,
on the determined target amount of insulin.
[0019] According to another embodiment, the controller may include a
memory and be
configured to store in the memory the motion data and the orientation data
received by the
controller during a lifestyle event of a user. Further, the motion data and
orientation data may be
associated with a specific type of lifestyle event of a plurality of types of
lifestyle events.
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[0020] According to one embodiment, the insulin pump augmentation
system may be
incorporated within, and operationally connected to either an internal or
external insulin pump
which is attached to the user.
[0021] According to one embodiment, the body of the insulin pump
augmentation system
may be a stand-alone wearable device configured to be worn by the user. The
wearable device
may be configured to be worn on a limb, such as on the arm at the wrist of the
user, and is
operationally connected to either an internal or external insulin pump which
is attached to the
user.
[0022] According to another embodiment, the insulin pump
augmentation system may
include a microphone configured to detect audio and to output audio data based
on the detected
audio. The controller may be configured to receive the audio data. The pump
instruction signal
may be based, wholly or partly, on the audio data received by the controller.
[0023] According to even another embodiment, the controller may
include a memory and be
configured to store in the memory certain previously stored audio data
received by the controller
during ingestion of food. The controller may also be configured to receive an
identifying input
from the user to define and match a particular food type of the food
previously ingested and
matched to the audio data received by the controller. The controller may be
configured to store
the audio data in association with the particular food type indicated by the
input. Further, the
controller may be configured to determine a particular food type based on the
stored audio data.
[0024] The controller may be configured to store, into a memory, the
motion data and the
orientation data received by the controller during a previous ingestion of a
particular type of
food. In the memory, the motion data and orientation data may be associated
with a particular
food type of a plurality of food types.
[0025] The controller may be configured to receive a selection from
the user of physical
ingestion characteristics of the particular food type based on stored motion
data and orientation
data or other physical ingestion characteristics.
[0026] According to an embodiment, the controller may be configured
to select a particular
food type from a plurality of food types, stored in a memory, based on at
least one of the motion
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data, the orientation data and the audio data. The controller may further be
configured to
generate the pump instruction signal based on the selection of the particular
food type.
[0027] The controller may be configured to estimate a quantity of
calories ingested by a user
and maintain a running caloric count representative of a sum of calories
ingested by the user
throughout a time period. Further, the controller may be configured to
generate a signal when
the sum of calories ingested by the user is greater than or equal to a
predetermined caloric
threshold.
[0028] The controller may be configured to estimate a quantity of
carbohydrates ingested by
a user and maintain a running carbohydrate count representative of a sum of
carbohydrates
ingested by the user throughout a time period. Further, the controller may be
configured to
generate a signal when the sum of carbohydrates ingested by the user is
greater than or equal to a
predetermined carbohydrate threshold.
[0029] According to another embodiment, the insulin pump
augmentation system may
include an indicator emitting device configured to emit a sound(s) or
vibration. The controller
may be operatively connected to the indicator emitting device and configured
to increase the
sound level and/or vibration level and increase a duration of the sound and/or
vibration when the
controller determines a user is non-responsive to acknowledging the sound or
vibration.
[0030] The controller may be operatively connected to a
communication device, and may be
configured to cause the communication device to be activated when the
controller determines the
user is not responding to an escalating series of alarm sounds or vibration.
Optionally, when the
communication device is activated, an emergency call or message may be sent
that includes real-
time medical information relevant to the user and/or location information.
[0031] According to another aspect, a pump augmentation system may
include a body, at
least a six-axis accelerometer sensor, a gyroscopic pitch sensor, and a
controller. The six-axis
accelerometer sensor may be arranged in or on the body and configured to
output motion data
based on detected motion. The gyroscopic pitch sensor may be arranged in or on
the body and
configured to output orientation data based on detected orientation. The
controller may be
operatively connected to the six-axis accelerometer and the gyroscopic pitch
sensor and
configured to receive the motion data and/or the orientation data. The
controller may be
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configured to generate a pump instruction signal based on the motion data
and/or the orientation
data, wherein the pump instruction signal may include a signal to change a
material delivery rate
of a pump.
[0032] According to another aspect, a method of augmenting a pump
system includes
monitoring motion data and/or orientation data, and generating a pump
instruction signal based
on the motion data and/or the orientation data. The pump instruction signal
may include a signal
to change a material delivery rate of a pump. The pump system may include a
device body, an
accelerometer sensor arranged in or on the device body and configured to
output the motion data
based on detected motion, a gyroscopic pitch sensor arranged in or on the body
and configured to
output the orientation data based on detected orientation, and a controller
connected to the
accelerometer and the gyroscopic pitch sensor, the controller being configured
to receive the
motion data and/or the orientation data. The controller may perform the
generating a pump
instruction signal.
[0033] According to another aspect, an intelligent drug delivery
system (IDDS) and method
uniquely provides an objective analysis of drug efficacy over time because the
system can
continuously monitor any physical symptoms that a patient presents and
continuously analyze the
effect of various dosages even while a patient is asleep and, therefore,
incapable of making any
subjective observations during a large portion of the day, e.g. one-third of
the day.
[0034] An IDDS according to the present disclosure uniquely provides
a way to quantitatively
measure and evaluate a patient's symptoms through the patient wearing a
sensing device of the
IDDS on their wrist(s) and/or other parts of their body. The sensing device(s)
may be used in a
stand-alone manner for the purpose of supplying a physician with instant
and/or archived empirical
data for a clinician or physician to base subsequent dosage decisions for
either oral or infusible
medication. The sensing device(s) can be used with an operative connection to
a continuous
medical infusion pump to form a closed loop system.
[0035] These and other objects, features and advantages of the
present invention will become
apparent in light of the description of embodiments and features thereof, as
illustrated and
enhanced by the accompanying diagrams.
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BRIEF DESCRIPTION OF THE DRAWINGS
[0036] FIG. 1 shows an exemplary pump for a pump augmentation system
(PAS) (e.g., an
IPAS-enabled insulin pump or an IDD S - en ab 1 e d drug delivery pump) in
accordance with
embodiments of the present disclosure;
[0037] FIG. 2 shows an exemplary PAS-enabled wrist-worn device
(e.g., an IPAS-enabled
wrist-worn device or an IDDS-enabled wrist-worn device) in accordance with
embodiments of the
present disclosure;
[0038] FIG. 3 shows an exemplary flow diagram for the operation of
the IPAS of FIG. 1 in
accordance with embodiments of the present disclosure;
[0039] FIG. 4 shows an exemplary flow diagram for the operation of
the IPAS of FIG. 1 in
accordance with embodiments of the present disclosure;
[0040] FIG. 5 shows an exemplary flow diagram for the operation of
the IPAS of FIG. 1 in
accordance with embodiments of the present disclosure;
[0041] FIG. 6 shows an exemplary flow diagram for the operation of
the IPAS of FIG. 1 in
accordance with embodiments of the present disclosure; and
[0042] FIG. 7 shows an exemplary flow diagram for the operation of
the IDDS of FIGS. 1 and
2 in accordance with embodiments of the present disclosure.
DETAILED DESCRIPTION
[0043] Before various embodiments are described in further detail,
it is to be understood that
the present disclosure is not limited to the particular embodiments described.
It will also be
understood that the methods and apparatuses described herein may be adapted
and modified as
appropriate for the application being addressed and that the devices, systems
and methods
described herein may be employed in other suitable applications, and that such
other additions and
modifications will not depart from the scope thereof.
[0044] Although various features have been shown in different
figures for simplicity, it
should be readily apparent to one of skill in the art that the various
features may be combined
without departing from the scope of the present disclosure.
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[0045] Certain features and elements of the Pump Augmentation
Systems (PAS) described
below are applicable to an Insulin Pump Augmentation System (IPAS) for
treating diabetes
and/or to an Intelligent Drug Delivery System (IDDS) for treating diseases
such as Parkinson's
disease. An IPAS is configured for delivering insulin, while an IDDS may be
configured to
deliver an anti-tremor medication or other medication for treating a patient
with Parkinson's
disease.
[0046] According to certain aspects, a controller associated with a
Pump Augmentation
System (PAS) or with an Insulin Pump Augmentation System (IPAS), in accordance
with the
present disclosure, provides improved pump operation or insulin pump operation
control schemes
and devices and systems for use with a pump or an insulin pump.
[0047] For example, the present disclosure provides an Insulin Pump
Augmentation System
(IPAS), which uniquely provides a closed-loop insulin pump with an
understanding of various
physiological and/or lifestyle activities its user is undergoing in real-time,
so as to allow for
dynamic proactive automatic compensation for said activities to better keep a
diabetic individual's
(or other individual) blood glucose level within a "desirable" target range.
This proactivity is
immensely important, as the mechanical insertion of insulin into a body,
whether through a manual
injection process or through an insulin pump, does not confer the same
immediate glycemic
response to a diabetic individual's glucose level, as compared to what a
"normal" (non-diabetic)
organic solution would provide.
[0048] There is a time lag between changes in blood glucose levels
and when those changes
are subsequently reflected by interstitial fluid readings, and as a result the
existing "after the fact"
insulin delivery reaction and correctional methods to external lifestyle
factors typically result in
undesirable "out of range- conditions. While insulin pumps are generally able
to deliver different
preset basal insulin infusion (delivery) rates based upon fixed, predetermined
time schedules, these
rates are not able to take into consideration the typical variations to an
insulin pump user's varying
schedule.
[0049] As an example, with the rise in glucose levels that diabetic
individuals experience upon
awakening as a result of the "Dawn Phenomenon," the best that current
technology can do is to be
statically programmed to allow for an increased basal insulin delivery during
a specific pre-set time
frame. The obvious problem with this method, however, is that unless an
individual exactly
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conforms to the strict time schedule corresponding to the expected insulin
delivery increase, this
timed increased insulin delivery level will not match the actual glucose level
insulin requirement,
and can result in abnormally low or high blood glucose levels
[0050] Given the reality of the numerous every-day "real-world"
variations, precisely
achieving both an exact time to bed, as well as an exact time of awakening in
order to maintain
consistent sleep durations in order to predict when a hormone release should
occur is almost
impossible to achieve consistently. Since present-design insulin pumps do not
have the ability to
recognize changes in sleep patterns (such as is experienced with variations
between weekday sleep
schedules and weekend or vacation sleep schedules, etc.), there is an inherent
timing issue with the
present treatment methods which prevent the proper response to the "Dawn
Phenomenon" blood
glucose changes.
[0051] In a similar fashion, conventional insulin pumps have no way
to proactively react to
spontaneous physical activity, whether it is during emergency situations (such
as having to run
down numerous flights of during an emergency evacuation), or for pleasure
(such as a spontaneous
extra round of tennis or other sporting activity that was not previously
envisioned), and as a result
even a closed-loop insulin pump crudely attempts to reactively reduce or
suspend insulin delivery
after the fact in order to maintain control
[0052] Where 'conventional' (non-PAS enabled or non-IPAS-enabled)
'smart watches' or
similar devices are capable of generating reports or saving information about
the total number of
strides or other physical activity, these devices only display prior
information such as calories
burned and distances covered, and are not configured for automatic responsive
action based on
such information for controlling or modifying an insulin pump. In contrast,
according to an aspect
of the present disclosure, a controller (for example, a controller integrated
into an IPAS) uses
sensed data to automatically determine and provide beneficial changes to the
insulin delivery rate
of an insulin pump (e.g. increases and/or decreases of insulin delivery rate).
The novel use of an
Insulin Pump Augmentation System (IPAS), which may, for example, incorporate
one or more six-
axis accelerometer/gyroscopic pitch sensors (or other number of axis
accelerometer(s)), and whose
data output may be processed and analyzed in real-time through an artificial
intelligence software
program, for the first time gives a closed-loop insulin pump the ability to
have physiological and/or
physical situation awareness in order to better match insulin delivery levels
to a body's actual
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insulin requirements. IPAS is also ideally suited for common problematic
situations, where
insulin-pump users either forget to temporarily suspend the insulin delivery
of their pump
beforehand and/or during exercise, and/or forget to bolus for a planned or
ingested carbohydrate
load. Both aforementioned situations can result in potentially serious blood-
glucose excursions
developing, which may be avoided through the use of IPAS according to
embodiments of the
present disclosure.
[0053] For the purposes of present disclosure, the term "lifestyle"
includes events such as: a
person's current sleep state (e.g., determining if a person is awake or
sleeping); a person's current
exercise or physical motion state (or movement state); a person's current food
intake state (eating,
chewing, drinking, etc.); and a person's real-time identification of a
specific food currently being
ingested as well as the total quantity of that food having been ingested. A -
lifestyle" situation
awareness augmentation provided to an insulin-pump by an IPAS allows a closed-
loop insulin
pump to monitor and automatically correct for physical exertion activity which
may change a
user's glucose level, a 'real-time' monitoring, identification, and insulin
compensation for a range
of ingested food, and the ability to monitor an individual's sleep/awake
status and compensate for
end-of-sleep hormone release changes to a user's blood glucose level.
[0054] According to certain aspects, a controller is associated with
an Insulin Pump
Augmentation System (IPAS). An WAS can be configured in different physical
embodiments, with
three exemplary embodiments including.
1) IPAS components being completely integrated into the body of an IPAS-
enabled
insulin pump. The data from the pump's integrated IPAS sensors being processed
by an associated
Artificial Intelligence sub-system within the IPAS, and the resultant guidance
being provided to the
insulin pump's delivery system(s) to act upon (or a controller of the insulin
pump delivery
system(s)).
2) The configuration of embodiment #1, further augmented by the additional use
of a
physically separate second six-axis accelerometer and gyroscopic pitch sensor,
and a microphone
that is integrated into a wrist-worn device that is placed on an insulin-pump
user's arm or wrist
(preferably the dominant arm or wrist), either as an IPAS-enabled smart-watch
or as a proprietary
IPAS wearable device. The data output from these additional sensors is
transmitted to an IPAS-
equipped insulin pump (e.g through wireless communication means), where the
added data stream
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is combined with the data supplied from the pump's integral sensor(s), with
both data streams
subsequently being processed by an Artificial Intelligence sub-system within
the insulin pump.
3) A configuration for use with a non-IPAS enabled closed-loop insulin pump.
In this
configuration, all of the IPAS sensing elements as well as the IPAS data
processing functions are
physically integrated into the body of a "smart-watch" or other IPAS wearable
device which is
worn on the wrist or arm of an insulin pump user (e.g. the dominant wrist or
arm). An integral six-
axis accelerometer and gyroscopic pitch sensor, along with a microphone are
used as input devices.
In this embodiment, the IPAS-enabled arm-worn device itself calculates
supplemental insulin
and/or delivery modification instructions, and then wirelessly transmits said
instructions to a
'conventional' insulin pump, i.e. non-IPAS equipped insulin pump, for
execution. Said insulin
pump would also transmit "real-time" parameters such as blood-glucose levels
and circulating
insulin to the WAS device.
[0055] In a first example of what the newly-found lifestyle
awareness conveys to an insulin
pump, the augmented pump will now be capable of dynamically determining a
sleep state or an
awakened state of a user, and proactively make compensating adjustments to an
insulin delivery
rate commensurate with an estimated body's release of hormones upon awakening.
With this new
lifestyle awareness, the glucose lowering effect of insulin can now be better
timed to match the
escalating blood-glucose effects of a hormone release upon awakening with a
commensurate
insulin release upon the IPAS sensing the physically awakened state of an
insulin-pump user.
[0056] In accordance with embodiments of the present disclosure, a
controller associated with
an WAS may determine that an individual is in a sleeping state or non-sleeping
state based on the
individual's physical orientation. For example, whether said individual is
physically oriented in a
position characteristic of sleep along with a reduced state of motion for an
extended period of time,
an WAS, through its six-axis accelerometer(s) and gyroscopic pitch sensor(s)
can similarly
recognize the physical positioning and a long-term lack of motion of an
individual, and match this
data with a stored template indicative of a sleeping state for that
individual. Conversely, when the
controller associated with the IPAS detects that an individual has changed
from a limited motion,
long duration sleeping state position to an upright position through detected
multi-axis motion,
then a determination of a non-sleeping state position (or awakening state or
morning awakening)
by the IPAS can also be made. The WAS Artificial Intelligence subsystem can
determine through
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an algorithm that, for example, includes a time-weighted motion analysis (to
prevent short duration
awakening from being incorrectly interpreted as morning awakening), as well as
observing the
range and speed of detected motion, in order to filter out the typical
transient movement and
position shifting of an individual during various sleep phases from an actual
awake state.
[0057] With the inherent ability of the controller associated with
the IPAS to detect the
sleeping state of a user, IPAS has the capability to not only advance or delay
the pre-programmed
time-based basal rates, but it can also correct and align the fixed/preset
basal rates with actually
observed conditions such as is encountered when sleeping or travelling between
time zones.
Similarly, an IPAS according to embodiments of the present disclosure can
temporarily skew a
current basal rate to better align with instant or predicted near future
bodily insulin requirements.
[0058] An IPAS's sleep/awake determination can also provide critical
user-condition
determination and responses. In the instance of the controller associated with
an IPAS-equipped
insulin pump sensing an abnormally low (or excessively high) blood glucose
reading while its user
is presumed sleeping, it can both increase the volume levels of a warning al
arm(s), as well as the
duration of such alarms beyond its usual daytime parameters, as arousing a
sleeping person
experiencing low blood-glucose levels can be especially challenging. In some
embodiments, in the
event that an IPAS-equipped insulin pump, after the completion of an enhanced
alarm sequence(s)
does not sense an awakened condition, the controller associated with the IPAS
is configured to
presume that the user has lost consciousness (or is otherwise non-responsive)
and automatically
commands a nearby mobile device to place an emergency call for medical help.
Simultaneously,
the controller associated with the IPAS may cause an insulin pump to
automatically suspend
insulin delivery. In the event of a non-responsive individual along with an
observed extremely low
blood-glucose indication, IPAS may be configured to automatically suspend
insulin delivery and/or
deliver an infusion of glucose-raising medication such as Glucagon. In the
case of excessively high
blood glucose levels, IPAS may be configured to automatically deliver an
appropriate insulin bolus
to avoid or correct a ketonic situation. For example, the controller
associated with the IPAS could
command the nearby mobile device through Bluetooth wireless communication or
the like. Even
though the unconscious individual may be unable to speak, a digitized voice
message would
indicate to an emergency operator the nature of the medical emergency, as well
as relay the
location of the user through GPS or other location information technology of
the mobile device
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should that information not be available via enhanced 911 systems. Optionally,
IPAS could deliver
to the emergency operator the observed blood-glucose levels for more timely
situation awareness
and action by first responders.
[0059] In a second example, a non-IPAS enabled insulin pump is
completely ignorant as to the
'moment to moment' lifestyle activities of its user, and thus has no ability
to proactively deviate
from its preset delivery settings. It is well known that physical activity
affects a diabetic
individual's blood glucose levels, either by lowering a diabetic individual's
blood-glucose level or
raising it depending on what the blood glucose level is at the time of said
exercise. By the use of
an integrated multi-axis accelerometer and pitch sensing sensor (or separate
adjunct multi-axis
accelerometer and gyroscopic pitch sensors), an insulin pump is able to gain a
continuous (or semi-
continuous) insight into a user's exercise/physical activity, and dynamically
and proactively adjust
the user's insulin delivery rate accordingly, rather than attempting to
reactively correct a resultant
change in blood glucose level as accomplished through conventional insulin
pump devices.
[0060] According to embodiments of the present disclosure, an IPAS
may achieve
improvements in a user's "in-range" glucose readings. Changes in exercise or
physical activity can
now be immediately detected (or nearly immediately) allowing for
contemporaneous alteration to a
user's basal insulin rate immediately (or near immediately) upon the
initiation of exercise.
Artificial Intelligence (Al.) logic may be employed to both analyze a user's
current blood-glucose
levels as well as determine the (presently) circulating insulin levels (as
provided by the insulin
pump) to make appropriate insulin adjustments by the pump as needed. If the
instantaneous
circulating insulin level at the time of exercise is deemed adequate and the
detected blood glucose
level is within a 'normal' range (or within a predetermined range), then the
controller associated
with the IPAS may be configured to bias the insulin pump to stop or lower the
insulin delivery
basal rate commensurate with the sensed level and duration of exercise. If at
the time of exercise
commencement, the detected blood glucose level is well above normal (or is
above a
predetermined threshold) and/or there is a low level of circulating insulin
(or is below a
predetermined threshold), then the controller associated with the IPAS may be
configured to cause
the insulin pump to either bolus and/or increase its basal rate to compensate
for the exercise so as
to prevent a further increase in blood glucose levels caused by the exercise.
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[0061] A determination of exercise or other strenuous activities
(such as playing tennis) may
be made through an A.I. motion algorithm, which may base the determination on
how many active
axes are reporting motion above a predetermined motion threshold level, the
excursion ranges of
said reporting axes, and any repeating cadence patterns (to detect running or
other specific
activities). The algorithm may be designed to filter out 'false' exercise
reporting situations, such as
when an individual is riding in a car (repeated rising up and down) so as not
to confuse said
vertical 'bouncing' up and down with the vertical motions one might associate
with running. The
motion algorithm would note that while there were vertical (and potentially
other motions), the
excursion distances were limited from what one would expect from exercise,
with forward
movements and other axis readings missing along with a very different cadence
pattern.
[0062] The Insulin Pump Augmentation System (IPAS) is not limited to
the lifestyle examples
described herein. Conventional insulin pumps have no direct means for
lifestyle awareness, and as
a result of this deficiency, the pump is completely unaware of a user's food
ingestion. Without a
"real-time" method to sense an ingested carbohydrate load, conventional closed-
loop pumps are
oblivious to food being ingested, and merely indirectly and reactively sense
that the user's blood
glucose levels are rising toward or beyond a target range or rate before
initiating corrective action.
Even in the case where an insulin-pump user manually boluses insulin prior to
food consumption,
this action is just a guess as to how much carbohydrate may or may not
subsequently get
consumed.
[0063] With the present invention, an IPAS-equipped insulin pump is
not only
contemporaneously presented with real-time information indicative of food
ingestion, but in many
cases, even the precise type of food, the actual quantity of food consumed,
the resultant calculated
ingested carbohydrate load, the glycemic index of said food, and a
compensating insulin bolus
amount and release timing for that ingestion may be estimated and provided to
the pump. This
allows an insulin pump to immediately (or near immediately) and
contemporaneously proactively
match supplemental insulin dosages to the amount as well as type of food being
consumed, as
opposed to a non IPAS-equipped pump needing to reactively compensate for said
food ingestion in
an imperfect "after the fact" manner.
[0064] As an example, in the case of a person eating popcorn, the
dominant hand (or non-
dominant hand) wearing an IPAS sensor(s) repeatedly moves in a distinct
pattern while taking food
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from a fixed "supply container" and bringing the popcorn to their mouth. By
analyzing the data
from one or more of the six-axis accelerometer sensors and/or one or more of
the gyroscopic
pitch/yaw/roll sensors during this activity, a distinctive repetition pattern
allows the controller (for
example, with an incorporated A.I. algorithm) to record the detected arm and
hand movements,
which can be accurately saved as a template representative of that particular
food being ingested.
The controller / Al. system may not only analyze the repeated multi-axial
positional locations,
speed, and cadence of said movements, but it may also generate a digitized
audio file from the
wrist-mounted microphone when the wrist worn device is determined to be at the
closest position
to the mouth of the user. The audio file may further assist the A.I. algorithm
in differentiating
between, for example, a person eating popcorn and a person eating potato chips
by differentiating
between their distinctive chewing sounds, as well as the duration of chewing
sounds.
[0065] By determining and analyzing the -linger" time that a hand
is held at or near a mouth,
as well as the number and type of sequential angular movements of the hand and
wrists before
moving away from the mouth, this allows a further quantitative determination
of what has been
ingested, and by supplemental simple calculation, the instantaneous
carbohydrate ingestion level
for each such movement cycle may be calculated, and a determination as to a
compensatory insulin
"bolus". is made By infusing insulin proximate (and at the appropriate
compensating level) to
ingestion taking place, as tempered by the glycemic index of the identified
food, a superior
proactive match of insulin and carbohydrate load may be made.
[0066] The variation in types of foods is quite extensive. By
having an individual -record"
various foods being eaten, as well as data labeling of the recorded foods, a
controller associated
with an IPAS according to embodiments of the present disclosure can easily
match and reference
the carbohydrate value, the glycemic index, calories, etc. to precisely tailor
the delivery values
necessary for an insulin pump to match the insulin need and timing to
compensate for a glucose
level increase in the blood caused by that food when ingested.
[0067] The physical motions and cadences typically associated with
eating various foods can
be quite distinctive for certain foods. Examples of this include, without
limitation, the eating an
ear of corn, the eating an apple (with distinctive 'snap back' after each
bite), the licking of an ice
cream cone, the peeling and eating of a banana, etc. Because of unique
physical movements while
eating and/or eating sounds associated with each food, a series of specialized
food templates may
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be generated and/or pre-stored in the controller associated with the IPAS.
Additionally, manually
inputting the food type into the IPAS by a user, for example by pressing a
button on the wrist-worn
device and speaking the name of a particular food, the carbohydrate and
caloric information may
be recalled (or identified) for foods that have difficulty in being
automatically recognized based on
a food template, and the IPAS will monitor the ingestion amount to resolve (or
determine) a
carbohydrate load and insulin bolus. For low-carbohydrate food such as meat,
the IPAS may
recognize the unique motions of meat cutting before ingesting (if the user
prepares the food for
ingestion).
[0068] The sound characteristics of not only the actual ingestion of
a beverage, but also the
sounds (or lack ot) created by the actual bottle or container may be
especially important in
identifying what the beverage (and its carbohydrate content) is. For example,
disposable plastic
water bottles, since they do not need to handle the pressures of carbonation,
are typically
constructed of much thinner plastic material than 'soda' bottles, and as such
they produce a
characteristically unique "plastic flexing/crackling" sound when handled and
being consumed
from. This unique plastic water bottle sound would be used by IPAS to
determine that a non-
caloric/zero carbohydrate ingestion was taking place. Conversely, a carbonated
beverage would use
a different type of bottle as well as producing different
ingestion/carbonation sounds With regard
to determining whether the carbonated beverage is "diet" or regular (with
their corresponding
vastly different carbohydrate amounts), the IPAS algorithm merely needs to
analyze the user's
blood glucose level at the time of ingestion to make a logical
differentiation. Since an IPAS user is
presumed to be a diabetic, then unless the user's glucose level was low at the
time of ingestion
(which would make the ingestion of a 'regular" soda or the like desirable in
that situation), then the
beverage is always assumed to be "diet".
[0069] Every food when ingested has a unique combination of
positional and rotational
presentations to the mouth, a distinct biting pattern and sound, juice sucking
sounds, chewing
noises, hand retraction rotation and positioning, etc.
[0070] In some embodiments, the controller associated with the IPAS
may not directly identify
a type of food based on a pre-stored food template, but rather using a
matching process wherein
individual food templates are recorded and saved by the user during ingestion,
with the user then
manually identifying and registering each different food. Subsequent food
identification may be
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accomplished by the IPAS automatically comparing in real-time active food
ingestion with the
saved digital motion and sound patterns of the saved templates. When a match
is made, the
carbohydrate levels, glycemic indices, caloric information, and other
information is provided to the
insulin delivery system for determining insulin delivery amount(s) and timing
of said delivery
amount(s).
[0071] The algorithm that the controller associated with the IPAS
used to determine ingested
food types may incorporate one or more validation methods to increase
accuracy. One of these
methods is to only allow food audio matching (as captured by the wrist-worn
device) during
periods when the IPAS motion analysis determines that a user's hand is in a
position proximate to
their mouth. By the use of such 'audio gating', the IPAS may prevent false
analysis when multiple
people are eating either the same type, or other food types in close proximity
to the subject IPAS.
Said audio gating also inherently provides a level of privacy due to the wrist
microphone being
muted whenever the system does not detect a hand being raised and brought
proximate to the
mouth. Accordingly, the IPAS may not record audio data from the microphone
when the IPAS is
determined to not be at a proximate position to a mouth of the IPAS user, or
disregard the recorded
audio data if the PAS is recording the audio data.
[0072] In some embodiments, the controller associated with the IPAS
is configured to initially
contain a number of 'generic' motion templates to immediately allow for
recognition of
awakening, running, or other activity. The IPAS is configured to not only
allow a user to generate
and replace said 'generic' templates with their own custom individualized
templates to further
increase both event recognition and accuracy, but also to supplement the range
of stored templates.
The custom personalized templates may also replace the generic motion
templates or be used in
addition thereto for recognition of awakening, running, or other activity.
[0073] Another benefit of a controller associated with an IPAS
according to embodiments of
the present disclosure comes into play during episodes of hypoglycemia. In
some circumstances,
individuals typically over-compensate their carbohydrate ingestion to treat
the immediate
symptoms of hypoglycemia. In some embodiments, the IPAS is configured to
monitor an instant
blood-glucose level, the amount of circulating insulin, as well as the amount
of carbohydrate being
ingested. The controller associated with the IPAS may be configured to provide
the user with an
'overshoot' protection alert to guard against excessive carbohydrate ingestion
subsequently
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resulting in hyperglycemia. By the IPAS comparing said ingestion against both
the instant glucose
level as well as the amount of circulating insulin, it can calculate (or
determine) the appropriate
amount of carbohydrate needed to normalize the user's blood-glucose level by
monitoring the
instant carbohydrate ingestion and sound an alert at a point of over-
compensation.
[0074] In some embodiments, the controller may be associated with a
Pump Augmented
System (PAS). The PAS may also be used for delivery of other infusible
medications or other
infusible materials, such as, for example and without limitation, medications
for treating
Parkinson's disease. In this usage example, infused medication delivery
time(s) and amount(s) can
be matched with an instant need, as determined, for example, by an increased
tremor level which a
PAS would detect.
[0075] For the purposes of the present disclosure, while the primary
disclosed application is
for the augmentation of an insulin pump, the same or similar hardware
configuration, with minor
software modification, may also be used for other purposes. In a further
embodiment of the
controller, the automatic food ingestion sensing may also be used as an
'ingestion' caloric monitor
as opposed to current devices that only report calories that were 'burned',
rather than consumed.
In some embodiments, a controller configured for caloric ingestion monitoring
may optionally be
configured to provide tactile or visual alarms or other guidance notification
once a target caloric
ingestion has been achieved or failed to be achieved by a certain time of day.
[0076] The present disclosure provides a controller associated with
a system for sensing and
determining "lifestyle" activities.
[0077] According to the present disclosure a Pump Augmentation
System (PAS) 10 for sensing
and determining "lifestyle" activities of a drug delivery pump user is
provided. Referring to FIGS.
1 and 2, the PAS 10 could be specifically implemented as an Insulin Pump
Augmentation System
(IPAS) or as an Intelligent Drug Delivery System (IDDS).
[0078] According to certain specific embodiments, an Insulin Pump
Augmentation System
(IPAS) for sensing and determining "lifestyle" activities of an insulin pump
user is provided. As
shown in FIG. 1, the Insulin Pump Augmentation System 10 in accordance with
embodiments of
the present disclosure is integrated into, and/or operatively in communication
with a drug delivery
pump, such as an insulin pump, 100 having a pump body 12. The IPAS 10 includes
a controller
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14, an accelerometer sensor 16, a gyroscopic pitch sensor 18, an indicator
emitting device 20 and a
transmitter 22. The accelerometer sensor may be a multi-axis accelerometer
sensor, for example, a
six-axis accelerometer sensor.
[0079] The controller 14 is operatively connected to the six-axis
accelerometer sensor 16, the
gyroscopic pitch sensor 18, the indicator emitting device 20 and the
transmitter 22. While the
controller 14 is shown as being physically connected to the six-axis
accelerometer sensor 16, the
gyroscopic pitch sensor 18, the indicator emitting device 20 and the
transmitter 22, the controller
14 may be "connected" to these elements through wireless communication methods
and
connections.
[0080] The six-axis accelerometer sensor 16 is configured to detect
motion (or movement) and
output motion data (or movement data). The controller 14 is configured to
receive and/or record or
store the motion data from the six-axis accelerometer sensor 16. The
gyroscopic pitch sensor 18 is
configured to detect orientation and output orientation data. The controller
14 is configured to
receive and/or record the orientation data from the gyroscopic pitch sensor
18. The indicator
emitting device 20 is configured to emit one or more sounds (for example, an
alarm sound) at
various sound levels and/or to display one or more visual indicators (for
example, a flashing light).
The controller 14 is operatively connected to the indicator emitting device
20. The transmitter 22
is configured to communication with one or more communication devices.
[0081] The controller 14 is configured to communicate with the
insulin pump 100 and receive
various insulin pump 100 data. For example, and without limitation, the
controller 14 may receive
circulating insulin level data of a user of the insulin pump 100, a reported
blood glucose level data
of the user of the insulin pump 100 and/or a current or scheduled insulin
delivery rate data of the
insulin pump 100. The controller 14 is operatively connected with a host
insulin pump 100. The
controller 14 is also operatively connected to the transmitter 22 to cause the
transmitter 22 to
trigger an automatic emergency call or message if one or more predetermined
criteria is satisfied
based on the motion data, orientation data, audio data, circulating insulin
level data, reported blood
glucose level data and/or current or scheduled insulin delivery rate data.
[0082] As shown in FIG. 2, the IPAS 10 is further integrated into,
and/or operatively in
communication with a wearable device 24. In this embodiment, the wearable
device 24 is a wrist
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worn device. The IPAS 10 includes a six-axis accelerometer sensor 25 and
gyroscopic pitch sensor
26 located in the wearable device 24. The IPAS 20 further contains a
microphone 28. The
microphone 28 is configured to detect audio and output audio data. The
controller 14 is configured
to receive the audio data from the microphone 28 and/or the wearable device 24
includes an
additional controller(s) which is configured to distribute the motion data,
orientation data and/or
audio data to the controller 14. It should be readily understood that the
microphone 28 may be
arranged in other positions of the wearable device 24 and/or there be
additional microphones.
[0083] In some embodiments, the controller 14 is arranged in or on
the wearable device 24. In
some embodiments the controller 14 is arranged in or on the insulin pump 100
as shown in FIG. 1,
and a second controller is arranged in or on the wearable device 24. The
second controller being
configured to communicate with the first controller 14 and/or a dedicated
controller of the insulin
pump 100.
[0084] Referring to FIG. 3, a flow diagram 30 shows an exemplary
method of operation of the
IPAS 10 of FIG 1 in accordance with embodiments of the present disclosure At
block 32, the
controller 14 monitors for motion data received from one or more of the six-
axis accelerometer
sensors 16, 25 and for orientation data from one or more of the gyroscopic
pitch sensors 18, 26. At
block 34, the controller 14 determines if the motion data and/or orientation
data has changed. If
the controller 14 determines that there is no change in the motion data and/or
orientation data, then
the controller 14 returns to block 32 for monitoring. If the controller 14
determines there is a
change in the motion data and/or orientation data, the controller 14 proceeds
to block 36 where the
change in motion data and orientation data is analyzed by the controller 14.
The controller 14
proceeds to block 38 where the controller 14 compares the motion data and
orientation data, which
may be time-weighted, for similarities with a profile template stored in the
IPAS 10. If the
controller 14 determines that the motion data and/or orientation data is not
similar to a stored
profile template, the controller 14 returns to block 32 for monitoring. If the
controller 14
determines that the motion data and/or orientation data is similar to a stored
template, the controller
14 determines that the motion and orientation detected is associated with the
ingestion of food and
proceeds to the identified profile template method.
[0085] Referring to FIG. 4, a flow diagram 39 shows an exemplary
profile template method of
operation of the IPAS 10 of FIG. 1 when the motion data and/or orientation
data is determined as
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being similar to a food ingestion profile at block 38 (FIG. 3) in accordance
with embodiments of
the present disclosure. The controller 14 proceeds to block 40, where the
controller 14 optionally
receives audio input 42 from the microphone 28 (FIG. 2). The controller 14
compares the motion
data, orientation data and/or audio data corresponding to the time period
determined to be
contemporaneous with ingestion of food for a similarity with one or more
stored food ingestion
templates. If the controller 14 determines that the data is similar to a
stored food ingestion
template, the controller proceeds to block 48, which is discussed in greater
detail later herein. If
the controller 14 determines that the data is not similar to a stored food
ingestion template, the
controller proceeds to block 44 and requests user input for food type of food
being ingested. If no
user input is received, the controller 14 returns to block 32 for monitoring.
If user input is
received, the controller 14 proceeds to block 46 and stores the motion data,
orientation data and/or
audio data as corresponding to a new food ingestion template of the input
provided. The new food
ingestion template is stored (e.g. in a memory associated with the controller)
for future food
ingestion template comparisons at block 40. Then the controller 14 proceeds to
block 48.
[0086] At block 48, the controller 14 determines a particular food
type identified as being
indicative of the food being ingested by the user. The controller 14 proceeds
to block 50 where the
controller 14 checks for a reported blood glucose level of the user (e.g. by
querying the insulin
pump 100). If the reported blood glucose level is greater than or equal to a
predetermined
threshold (e.g. 100 mg/di), then the controller 14 generates a pump
instruction signal at block 52
causing the insulin pump 100 to bolus insulin to the user based on the amount
of carbohydrate load
ingested (or consumed) as determined by the controller 14, thereby changing
the current or
scheduled insulin delivery rate of the insulin pump 100. If the reported blood
glucose level is less
than a predetermined threshold (e.g 100 mg/di), then at block 54 the
controller 14 checks a
circulating insulin level within the user (e.g-. by querying the insulin pump
100). If the circulating
insulin level is below a predetermined threshold, at block 56 the controller
14 generates a pump
instruction signal to bolus insulin to the user based on the amount of
carbohydrate load ingested (or
consumed) as determined by the controller 14. If the circulating insulin level
is above a
predetermined threshold, then at block 58, the controller 14 does not generate
a pump instruction
signal or generates a pump instruction signal that reduces the insulin
delivery rate from the current
or scheduled insulin delivery rate. Then the controller 14 returns to block 32
for monitoring.
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[0087] Advantageously, the controller 14 being configured to request
and receive input from a
user at blocks 44, 46 allows the controller 14 to repeatedly learn the
physical characteristics and/or
mannerisms unique to the user. The stored patterns are individualized to the
user allowing the
controller 14 to identify food templates (or other templates) more accurately.
The controller 14
may be configured to store any number of templates input by the user giving
the controller 14 the
ability to store virtually infinite patterns unique to the user. The ability
to store patterns unique to
the user advantageously allows for the controller 14 to "learn" the user
tendencies (or previously
entered pattern data) that correspond to a food template (or other template).
For example, a user
may tend to generate one or more unique motions, orientations or sounds when
engaging in a
physical lifestyle event that the controller 14 can identify as a particular
template once stored.
Thus, when the user again engages in that lifestyle event, such as eating
potato chips in a particular
physical manner, the controller 14 is configured to identify the lifestyle
event and generate a pump
instruction signal accordingly as disclosed herein.
[0088] Referring to FIG 5, a flow diagram 60 shows an exemplary
method of operation of the
IPAS 10 of FIG. 1 when the motion and/or orientation data is determined as
being similar to an
exercise profile at block 38 (FIG. 3) in accordance with embodiments of the
present disclosure. At
block 62, the controller 14 compares the motion data and/or orientation data
for similarity with a
particular exercise profile. At block 64, if the controller 14 determines that
the motion data and/or
orientation data does not correspond to a particular exercise profile, then
the controller 14 returns
to block 32 monitoring. If the controller 14 determines the data does
correspond to a particular
exercise profile, the controller 14 proceeds to block 66 where the controller
14 checks for a
reported blood glucose level. If the reported blood glucose level is below a
first threshold, the
controller 14 proceeds to block 68 and generates a pump instruction signal
instructing the insulin
pump 100 to suspend insulin delivery or decrease insulin delivery. If the
reported blood glucose
level is above the first threshold but below a second threshold (e.g. 250
mg/di), the controller 14
proceeds to block 70 and checks a circulating insulin level within the user.
If the circulating
insulin level is below a first insulin threshold, the controller 14 proceeds
to block 72 and maintains
the existing insulin delivery rate (or at least does not cause the insulin
delivery rate to change
significantly). If the circulating insulin level is above a second insulin
threshold, the controller
proceeds to block 74 and reduces the insulin basal rate. Referring back to
block 66, if the blood
glucose level is greater than a third threshold, the controller 14 proceeds to
block 76 and
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determines an increase in an insulin delivery rate and/or an insulin bolus
commensurate with the
particular exercise profile, the controller 14 generates a pump instruction
signal to cause the insulin
pump 100 to deliver the determined commensurate insulin rate or bolus.
[0089] Similar to the method discussed above in connection with FIG.
4, the controller 14 may
be configured to request that the user enter an exercise template to be stored
as corresponding to a
recorded exercise profile. In some embodiments, the controller 14 does not
need to request that the
user enter an exercise or food template. The user can enter the corresponding
template even when
not requested by the controller 14. The entered template is stored with
recorded data from the
IPAS 10. In some embodiments the recorded data stored as the template
corresponds to the data
recorded during a predetermined amount of time before the entering of the
template by the user, for
example and without limitation, one minute, two minutes or three minutes. In
some embodiments,
the user can choose which recorded data is associated with the entered
template. For example, the
user can choose the amount of time prior to the entering of the template, or
the user can choose a
period of recorded data that occurred earlier in the day, e.g. if the user
played tennis from 1:00 PM
to 2:00 PM, later that day at 6:00 PM when the user is not playing tennis, the
user could choose the
time playing tennis as being stored as the tennis exercise profile or template
[0090] Referring to FIG. 6, a flow diagram 78 shows an exemplary
method of operation of the
IPAS 10 of FIG. 1 when the motion and/or orientation data is determined as
being similar to a sleep
profile at block 38 (FIG. 3) in accordance with embodiments of the present
disclosure. At block
80, the controller 14 determines a sleep state is detected. The controller 14
proceeds to block 82,
where the controller 14 continues to monitor the motion data and/or
orientation data for a
determination of a sleep to awake transition, which may be based on a time-
weighted evaluation of
the data. If no sleep to awake transition is detected, the controller returns
to block 80 to check the
data is similar to a sleep profile and, if in the sleep state, returns to
block 82 for determining if a
sleep to awake transition has occurred. If the controller 14, determines that
a sleep to awake
transition has occurred (e.g. by the motion data indicating that the user is
moving or walking, or the
orientation data indicating that the orientation the IPAS 10 has changed),
then the controller 14
proceeds to block 84 to check for a reported blood glucose level of the user.
If the reported blood
glucose level is below a first threshold, the controller 14 proceeds to block
86 where the controller
14 determines that no insulin bolus is necessary to compensate for hormone
release associated with
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a transition to an awakened state as discussed herein. If the reported blood
glucose level is above a
second threshold, the controller 14 proceeds to block 88 where the controller
14 determines an
increase in an insulin delivery rate and/or an insulin bolus to compensate for
the user hormone
release, then the controller 14 generates a pump instruction signal to cause
the insulin pump 100 to
release the appropriate insulin at the appropriate delivery rate. Then the
controller 14 returns to
block 32 for monitoring.
[0091] In some embodiments, an IPAS 10 is located entirely in or on
an insulin pump 100 (e.g.
FIG. 1). In some embodiments, an IPAS 10 is located in or on an insulin pump
100 and in or on a
wearable device(s) 24 (e.g. FIGS. I and 2) and, as disclosed herein, the WAS
10 elements in the
wearable device 24 are configured to communicate and work with the WAS 10
elements in the
insulin pump 100. In some embodiments, an WAS 10 is located entirely in or on
a wearable device
24 (e.g. FIG. 2) and is configured to communicate and work with a non-
integrated WAS insulin
pump (i.e. does not have any IPAS functionality by itself), where the IPAS 10
in the wearable
device 24 supplements or overrides at least some control of the non-integrated
WAS insulin pump
functions so that the insulin pump operates like an integrated WAS insulin
pump. In some
embodiments, a user might wear one or more wearable devices containing IPAS 10
elements, for
example and without limitation, a wearable device on each wrist of the user.
[0092] Advantageously, IPAS enabled pumps are configured to provide
advantages over
non-IPAS enabled pumps. For example, without an IPAS providing an insulin pump
a teal-time
indication of a user's sleep status, a conventional insulin pump may generate
unnecessary alarms
without regard to context. As an example, some insulin pumps may keep track of
the amount of
remaining insulin in its reservoir, and at various insulin remaining levels
the pump may sound an
alarm indicating the situation. As a result of this, insulin pump users are
often awoken to take
certain actions such as to change reservoirs even though the situation is not
yet critical and such
actions are ill-advised to be done when just woken up in the middle of the
night. In some
embodiments, an IPAS enabled insulin pump may determine whether a user is
sleeping, and, if
an alarm is determined as being merely advisory rather than time or situation-
critical, the IPAS
enabled insulin pump may delay such alarms and/or notifications until the user
is awake and/or
until the status of the alarm becomes time-critical.
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[0093] Features and elements of the PAS and IPASs 10 described above
are applicable to an
intelligent drug delivery system (IDDS) 10 for treating diseases such as
Parkinson's disease and,
therefore, will not be repeated in detail here. Instead of delivering insulin,
an IDDS (or PAS)
may be configured to alter the delivery rate of an anti-tremor medication or
other medication for
treating a patient with Parkinson's disease.
[0094] Quantitative measurable factors are not available for
Parkinson's disease as are
available for other diseases, such as glucose level, blood oxygen
concentration level, blood
pressure reading, EKG reading, body temperature, etc. Parkinson's disease
differs in that there is
no direct and continuous measurable universal reference values upon which to
alter medicine
delivery rates. Clinicians typically judge the progression of the disease
based on visual
observation(s) of a patient, and make subjective dosage changes therein.
[0095] The motion and/or orientation data collected by the IDDS
device 10 is analyzed by
the controller 14 to determine the presence of even subtle changes in physical
movement
symptoms A high resolution Micro-Electromechanical Sensor(s) (MEMS) of the
IDDS 10, e g
six-axis motion tracking device which may include a three-axis gyroscope with
a three-axis
accelerometer, which allows for fine resolution detection of patient motions,
which include
tremor symptoms. Such resolution provides for accurate pitch, roll and yaw
motion sensing
capability in addition to the traditional three Cartesian coordinate axis
measurements. Thus, an
IDDS 10 device according to the present disclosure is configured, for
instance, to monitor
motions of a wrist/hand that is in a resting (or fixed) position having an
X/Y/Z axis position, but
whose fingers are rhythmically active, which are detected by the sensor(s) of
the device 10,
indicating a tremor incident of a detectable intensity and duration that may
be recorded and
stored in a local or remote storage. Embodiments using more advanced or higher
resolution
sensors may also be used.
[0096] With the use of a body-worn or internal to a medication pump
sensor, the device 10
may be configured to differentiate from a normal upright position and a prone
resting/sleeping
position.
[0097] Each Parkinson's disease patient has individualized physical
and/or cadence tremor
characteristics throughout each stage of the disease. Thus, the ability to
record and store tremor
incidents allows for the comparison of motion for determining whether there is
a change in
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duration and/or intensity of tremors, either increases or decreases, beyond a
predetermined
threshold, e.g. an increase of 10% duration or an increase of 25% force of
tremor movements. In
some embodiments, a device 10 is worn on each wrist of the patient (and/or a
device 10 on one
or more ankles of the patient). In some embodiments, a device 10 is worn on a
general body
location, such as on the torso.
[0098] A closed loop IDDS in operation with a patient, such as for
treating a patient with
Parkinson's disease, is configured to utilize the at least one body worn (e.g.
wrist and/or general
body location) motion and orientation sensor to operationally supplement or
completely replace
conventional infusion rate settings used by conventional non-intelligent
continuous fusion pumps
(e.g. fixed dosage delivery or particular time of day delivery infusion rate
settings).
[0099] The term "continuous" as it is used in the context of the
present disclosure will be
understood by those of skill in the art to not literally mean drug delivery on
a non-stop basis, but a
continual repetition of delivery doses, with the spacing between dosing and
the duration of each
dose being dosage variables In a similar fashion, it may not be advantageous
to make
observations of the patient literally every second as this non-stop
observation may not provide
significantly more data benefits as compared to data sampling with some length
of time between
data collection.
[00100] Advantageously, IDDS s allow for an infusion pump to provide dynamic
timing and
delivery rate adjustment settings of medication infusion flow rate(s) based on
real-time observation
of presented Parkinson's Disease symptom intensity levels. IDDSs according to
the present
disclosure may be configured to continually monitor, analyze, and adjust the
basal rate of infusion
pump medication in response to observed patient motion feedback. The
observation may include
monitoring body tremors, Dystonia, Dyskinesia, gait, and/or freezing as
detected by one or more
six-axis motion sensors.
[00101] Since each Parkinson's Disease patient throughout each stage of
symptoms may have
individualized physical and/or cadence tremor characteristics, an advantageous
feature of IDDSs
according to the present disclosure is the periodic recording and subsequent
periodic matching and
analysis between earlier individualized patterns and present patterns to
determine if pattern
excursions have changed in any metric (e.g. intensity, duration, type of
motion, etc.). In some
embodiments, an IDDS may function through a single wrist-worn sensor,
typically on the body
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side presenting the greatest or more frequent abnormal symptoms. In some
embodiments, an
IDDS may function through two sensors, one on a wrist of the patient and one
body worn for a
greater number of data collection points that communicates with the controller
of the infusion
pump to make a determinations regarding pharmacological delivery rate changes
based on the data
from one or both sensor controllers. In some embodiments, an IDDS may function
through a
wrist-worn sensors and an additional body worn sensor for even more data
collection points, e.g. a
sensor that is worn around the waist or torso of the user (such as a sensor
that comprises a belt or
attaches to a belt). Various combinations of sensor numbers and locations may
be used. In some
embodiments, the drug infusion pump unit of the IDDS may have an integrated
gyroscopic and/or
orientation position sensor to provide positional information and/or to
supplement the data from
other sensors.
[00102] The controller 14 may be configured to analyze body movements
attributed to a -base"
or starting point movement level, and from this base level determination a
pharmacological
delivery rate is initially established/stored by the controller 14 with the
movement data obtained
from the one or more worn sensors through sensor input channels of the
controller 14. By
analyzing this data, the controller 14 is configured to generate an
individualized baseline
pharmacological delivery rate A baseline deviation ratio is selected which
applies a percent rate
change to the pharmacological delivery rate (or other rate change, e.g.
absolute volume rate
change) to either increase or decrease the delivery amount based on sensed
excursion position
changes detected by the one or more worn sensors. Sensed positional data may
normally be
recorded and stored while the user is in a resting position to better filter
out "noise" from the
relevant positional data input channels. The controller 14 may analyze a
subset of the data input
channels for subsequent comparisons. Nevertheless, the system would continue
to monitor all
input channels (and non-relevant movement) in order to equalize the overall
body movement
context and prevent unnecessary data "noise" or influence.
[00103] The recording/analytical comparison interval periods may be selected
by a clinician to
reflect a meaningful or useful diagnostic comparison period. However, the
controller 14 may be
configured to delay any recordings/analysis until the overall body movement
context is determined
to be the same as during a previous recording. This delay would prevent data
external to the body
positional motion from falsely skewing the data collected.
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[00104] In some embodiments, the IDDS is configured to determine whether a
movement delta
exists between a hand-worn sensor and a non-hand worn sensor (or reference
sensor) on certain
data input channels. By utilizing one or more non-wrist-worn six-axis sensors
(such as one that
may be integrated into the pump itself) to compare against a wrist-worn
sensor, this would provide
useful "external" (to a wrist-worn sensor) positional information and would be
used to null or filter
out any external to the body movement "noise", such as a person bouncing up
and down while
traveling in a car. If the same data input channels from both a wrist-worn
sensor and a non-wrist
sensor were detecting the same or similar data, the system or controller 14
would be able to
determine that the data was not being created by the body itself and, thus,
should not be attributed
to a tremor. If just a wrist-worn sensor was sensing certain movement data
without a -check"
sensor also supplying positional data, there would not be a way to determine
whether sensed body
movement was separate from any external movement applied to the user and thus
the detected
movement would always be validly considered organic movement generated by the
user.
[00105] In addition to random abnormal body movements (which would be
recorded), one of
the most common Parkinson's Disease symptoms is a constant tremor. A constant
tremor is a
rhythmical movement typical in each individual with Parkinson's Disease and
may have an
individual distinctive cadence. The individual distinctive cadence may be
identified by the
controller 14 through repeated detections of the movement or by manual
calibration and
identification by the user or clinician in the IDDS, and the IDDS is
configured to record its
existence. By empirically matching an instant comparison of the excursion
limits of movements
containing this cadence movement with a reference recording, a reliable
measure of the
progression of Parkinson's disease may be established. Any recorded and stored
cadence examples
also serve to filter the desired cadence movement information from normal
lifestyle movement
data that does not contain a known repetition rate to avoid extraneous data
"noise."
[00106] Timely reporting of movement changes to a clinician is of substantial
importance as it
may indicate a needed change in dosage level or medication brand or type. An
advantageous
aspect to IDDS embodiments according to the present disclosure is the
inclusion of outgoing data
reporting capability. In other words, the IDDS is configured to communicate
with a clinician
computer system through wired or wireless communication means. For example,
the IDDS may
be configured to wirelessly connect with a cell phone of the user and cause
the cell phone to
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transmit a message through cellular or internet network(s) to a clinician
computer system. This
allows the IDDS controller 14 upon sensing a continuing excessive (i.e. "out
of range")
abnormality to automatically contact a clinician. In some embodiments, the
message to the
clinician computer system may be to merely communicate a report of the
detected excessive
changes to the clinician. However, in some embodiments, the IDDS has the added
ability to be
remotely adjusted so a clinician may make an immediate dosage change(s) during
or after any
reporting session. The IDDS communications capability may include the use of
WI-FT, cellular, or
other communications methods or protocols in common use.
[00107] An IDDS according to the present disclosure may also have the
capability to
autonomously make dosage changes, to either increase or decrease, in response
to detected
symptomatic changes. The changes would be analyzed by the controller 14, for
instance, on the
basis of a patient exceeding a preset level of instant or averaged abnormal
excursion increases, on
the basis of exceeding a preset level of abnormal excursion decreases, a time
of day context, etc.
The range of automatic dosage delivery changes would be limited by a pre-set
dosage (change)
"collar" restraint with such autonomous limits determined by the clinician for
each user.
[00108] Advantageously, an IDDS may be configured to continuously (or at
desired intervals)
record relevant data, make periodic comparisons between that data and previous
data records,
and/or take action upon the detection of physiological significant data
changes. The comparisons
may include individual sequential recording comparisons, or an averaging and
comparison
between timely groups of recordings.
[00109] In embodiments according to the present disclosure, the generation and
storage of data
readings for later analysis and action goes beyond the recording of "simple"
or "raw" motion data.
For example, an IDDS may use linked "metadata-, or data that links the primary
motion data
values within context of other values which brings sub-context to the main
data. This allows, for
instance, the historical "raw" motion data to be directly linked to additional
information such as
time/date stamps, the pharmacological delivery rate at the time of recording,
the estimated
circulating medicine level at the time of recording, the medication type, the
medication strength,
the body activity level at the time of recording, the sleep/awake state at the
time of recording, etc.
This allows the associated physical body movement data to provide a much more
meaningful and
rich context. With such metadata, extensive reports, charts, and detailed
analyses may be
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automatically generated for each patient, thereby creating a far more useful
dynamic picture of
dosage efficacy, etc. for each user/patient on an individualized level.
[00110] In some embodiments, an IDDS contains Artificial Intelligence (Al)
which learns from
the recording analysis of a user/patient relative to the results of prior
automatic dose correction
actions. The system's motion and orientation sensor(s), in addition to
monitoring abnormal body
movements also function as a lifestyle input sensor(s) to determine whether a
person is sleeping,
exercising, etc. Since individuals spend the majority of their day in an
upright position whether
standing, sitting, etc., the IDDS controller 14 assumes that this is the
normal lifestyle position to
differentiate against to determine whether a body is in a prone or
resting/sleeping position.
[00111] As its name implies, IDDS is an intelligent drug delivery system that
is capable of
learning when and if various lifestyle conditions need dosage alterations to
occur. Based on the
analysis of a patient's historic reaction (or lack of a reaction) to certain
level changes of infused
medication, an IDDS is capable of reporting to a patient's clinician which
dosage change(s)
resulted in the most desirable balance between mitigation of symptoms and
occurrence of side
effects, and what minimum infusion rate(s) were required to achieve the
desired changes for this
balance to occur at.
[00112] A determination of a specific lifestyle event change would bias the
automatic
pharmacological delivery adjustment algorithm(s) to allow for appropriate
remedial actions such as
providing a non-planned medication rate increase should the IDDS detect, for
instance, a user
awakening from sleep, or reducing a medication basal rate should the IDDS
detect the user falling
asleep, etc. The lifestyle detection also plays an important role so as not to
confuse the artificial
intelligence, for instance, between sensing a reduction in physical symptoms
caused by a
medicine's resultant therapeutic action and a user sleeping with its inherent
abnormal movement
reduction typical of natural sleep paralysis While people are typically
creatures of habit and
generally go to sleep about the same time each day, there are numerous outside
factors and
circumstances that can alter their schedule and dynamically require a dosage
change to occur. An
IDDS overcomes the time of day limitations of a conventional/non-intelligent
continuous infusion
pumps dosing rate schedule by allowing the IDDS to intelligently and
dynamically base an instant
dosage rate change by reacting to real-time sensing and lifestyle event
determination. If a selected
periodic recording time was reached and there was a data-skewing short-term
lifestyle event taking
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place (e.g., exercising) the system would automatically enter a "try again
later" mode which would
delay and prevent any atypical recording or analysis, for instance, for a
predetermined amount of
time (e.g. 15 minutes or whatever time frame is determined to be appropriate
by the controller's
artificial intelligence or selected from a preconfigured amount of time
selections).
[00113] An IDDS according to the present disclosure generates extended
historical sensor
recorded data, from which dosage "cause and effect- record data is stored
within the IDDS pump
controller 14 itself (or other memory). The IDDS allows the data to be able to
be remotely
accessed at any time by one or more medical professionals for the purpose of
both clinically
analyzing historic results, as well as allowing a post-analysis IDDS dosage
change to be made
remotely by a physician/clinician. This feature is especially important for
patients located in areas
remote to medical care, as well as overcoming the progressive inability of
many Parkinson disease
patients to be able to travel to a clinical setting. Even with clinical
evaluations there is typically a
progressive cognitive decline with Parkinson's disease patients that results
in patients increasingly
being unable to either observe their own true medical condition and/or
adequately respond to
medical questioning by a clinician. With an IDDS this problem is addressed by
having most or all
of the relevant data able to be completely accessible in an empirical fashion
from among the stored
data
[00114] By continually monitoring a patient's movements, an IDDS is capable of
noticing and
analyzing any clinically relevant changes in movement excursions on an
absolute basis, which for
the first time allows a truly objective determination of Parkinson's disease
progression to be made
for any given time frame. An IDDS can also monitor on an absolute empirical
basis the systemic
and physiological effects of exercise, certain therapies, etc. on a patient so
as to truly gauge what
therapeutic efforts are working effectively or not.
[00115] An IDDS also uniquely provides new opportunities for clinicians to
perform proactive
range-bound medication changes in order to precisely and efficiently observe
real-world cause and
effect studies to determine the optimal dosaging for each patient. For
example, an IDDS may be
configured to do automatic dosage bracketing of pharmacologicals to
empirically ascertain an
optimum dosage level(s). For a given time period, which is selectable by a
clinician, the IDDS will
bias the overall dosing by a selectable percentage above or below a current
baseline. For example,
the IDDS would skew the average dosing a selectable step lower and then make
an analysis of any
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resultant abnormal movement symptoms presented during the altered/skewed
dosage period and
compare the data results to the prior baseline. If the symptoms have generally
stayed the same, the
system would again repeat the stepped dosage reduction and continue with this
until an increase in
presented symptoms are noted and then return to the most recent previous
dosage levels. The
automatic bracketing may also be used in the opposite dosing direction to
determine if there is
symptom reduction with a higher dosage regime. Although the previous example
was directed to
an overall daily dosage study, an IDDS is also capable of automatic bracketing
and analysis ofjust
specific times of the day and/or days of the week. Since the metadata recorded
by the IDDS
includes the type/brand or analog information of the medication that was being
infused (e.g. either
inputted by the user or the clinician), it is relatively simple to conduct
relative efficacy comparisons
on an individual patient (or for that matter a group of patients) to
empirically determine which of
the available medications provide the best/most desired results as measured,
for instance, by the
total number of recorded abnormal movements within the same time frame and
relative dosage for
each medication. Similarly, an IDDS is a valuable platform for the empirical
field-trial results of
new Parkinson's medications as well.
[00116] Advantageously, since the actual infusion pump as well as the motion
sensors are
designed to nm on battery power, medication infusion as well as tremor
monitoring are able to
continue despite commercial power outages or while traveling.
[00117] At times when the medication reservoir and infusion set are being
changed, with one or
more system components being taken offline to be recharged, etc., the infusion
pump and/or the
controller 14 would note this activity and either exclude any medication
delivery logging
information from that time period's recorded data, or annotate the data from
that time period via
metadata so as not to falsely skew the subsequent recorded data analysis.
[00118] At times when a body worn sensor is not being worn or the data from a
device is
otherwise unavailable (e.g. the sensor is undergoing a battery replacement or
recharge, etc.) the
controller 14 (or infusion pump controller) would discontinue its dynamic
delivery rate
determination method and instead proceed/continue with the last known dynamic
infusion rate(s).
During periods of extended loss of sensor data, the IDDS may operate in
accordance with self-
generated historical time-contextual infusion rates generated via recent pump
activity. In the event
the pump has not had sufficient operating activity such as in the case with a
new pump, the system
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may operate in accordance with various traditional time of day non-dynamic
dosage patterns that
are typically based upon and altered strictly according to a daily time
schedule so as not to allow a
complete diminishment of circulating medication to occur. The IDDS would
typically include a
processor with an integral real time clock built into the system or functional
equivalent.
[00119] In some embodiments, each IDDS component are serialized to ensure
multiple sensors
in a given area are uniquely linked to the appropriate serialized infusion
pump, which would ensure
data from a body worn sensor(s) is not mistakenly provided to a nearby
infusion pump of a
different user.
[00120] In some embodiments, the infusion pump of an IDDS allows for the
release of both an
active pharmacological medication as well as an adjunctive precursor
medication (agonist) that
IDDS would automatically and appropriately infuse prior to the infusion of the
primary
pharmacological agent.
[00121] In some embodiments, the IDDS continually calculates the level of
circulating
Levodopa (or other pharmacological agent) at any given time with said
calculation based on the
infusion timing and dosing levels of the pharmacological agent and attaches
that circulation level
as metadata. Additionally, the IDDS tracks and records the peak and minimum
circulating levels
of said pharmacological for any given time frame in order to be able to
retroactively analyze these
levels against the sensed abnormal movements such as tremors, freezing onset,
dystonia, Gait
abnormalities, and/or dyskinesia in the same time frame in order to further
clinical evaluation
This essentially eliminates the need for a patient to maintain a "motor diary"
which is of limited
value relative to IDDS in that it cannot provide critical details such as the
circulating level of a
pharmaceutical during each episode or for any given time.
[00122] In some embodiments, an overall goal of the IDDS is to provide an
optimized level of
medication that minimizes or curtails instant tremors or other body motion
abnormalities. In the
context of Parkinson's Disease control, an optimized level of medication
provides for just the
minimum level of daily medication infusion that is consistent with abnormal
motion control in
order to avoid over-medicating the patient. Without dynamic dosing control, it
is inevitable that
excess medication dosaging will occur at times, along with times of sub-
optimal medication levels.
This results in "off' periods wherein insufficient pharmacological levels
cause a lack of abnormal
movement control. Without a dynamic control of pharmacological levels as
provided by IDDS,
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inevitably there are numerous times when the pharmacological levels are much
higher than are
necessary, with this hyper-dosing causing further complications such as the
onset of dyskinesia.
[00123] A body worn sensor may be adhesively attached to a body in order to
ensure the sensor
orientation is indicative of a certain body orientation.
[00124] IDDS may also include an ambient light sensor to further aid in the
detection of a
lifestyle event such as sleeping.
[00125] The use of a wireless charging grid that may be an integral part of a
blanket, bed-sheet,
etc. may allow wireless charging of the controller and/or body sensors.
[00126] The IDDS controller may employ Digital Signal Processing (DSP) in its
determination
of position and/or acceleration data results.
[00127] IDDS provides for dosage delivered feedback from a infusion pump to
the controller.
[00128] Referring to FIG. 7, a flow diagram 90 shows an exemplary method of
operation of the
IDDS of FIGS 1 and 2 in accordance with embodiments of the present disclosure.
At block 92, the
controller 14 monitors for motion data received from one or more of the six-
axis accelerometer
sensors 16, 25 and for orientation data from one or more of the pitch sensors
18, 26. At block 94,
the controller 14 determines if motion data and/or orientation data has
changed. If the controller 14
determines that there is no change in the motion data and/or orientation data,
then the controller 14
returns to block 92 for monitoring. If the controller 14 determines there is a
change in motion data
and/or orientation data, the controller 14 proceeds to block 96 where the
change in motion data
and/or orientation data is analyzed by the controller 14 The controller 14
proceeds to block 98
where the controller 14 compares the motion data and orientation data, which
may be time-
weighted, with previously recorded motion data and orientation data of the
user associated with
abnormal behavior movements (or tremor incidents) or compares the data with
other baseline data,
in order to determine an intensity and/or frequency of abnormal movements. If
the controller 14
determines that the intensity and/or frequency of the abnormal movements are
within a
predetermined threshold and/or have not changed by a predetermined amount (or
percentage) from
previous data of the user (or baseline data) then the controller 14 determines
that the current dosage
regimen of the current pharmacological drug should be maintained and the
controller 14 proceeds
to block 100. At block 100, the controller 14 generates a pump instruction
signal to continue or
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maintain the current dosage regimen, e.g. by maintaining the current delivery
rate of the
pharmacological drug.
[00129] If the controller 14 determines that the intensity and/or frequency is
above a
predetermined threshold, or if the intensity and/or frequency has increased
from previous data (or
other baseline data) beyond a predetermined amount (or percentage), then the
controller 14
determines that the dosage regimen needs to be increased and the controller 14
proceeds to block
102. At block 102, the controller 14 generates a pump instruction signal to
increase the dosage
regimen, e.g. by increasing the current delivery rate of the pharmacological
drug.
[00130] If the controller 14 determines that the intensity and/or frequency is
below a
predetermined threshold, or if the intensity and/or frequency has decreased
from previous data (or
other baseline data) beyond a predetermined amount (or percentage), then the
controller 14
determines that the dosage regimen may be decreased or that it is an
appropriate time to perform
dosage bracketing and the controller 14 proceeds to block 104. At block 104,
the controller 14
generates a pump instruction signal to decrease the dosage regimen and/or
perform bracketing, e.g.
by decreasing the current delivery rate of the pharmacological drug.
[00131] Following blocks 100, 102 and 104, the controller 14 proceeds to
monitoring motion
and orientation data at block 92 in order to repeat the above described
process or to perform dosage
bracketing as discussed above
[00132] An advantage of IDDSs according to the present disclosure is the
ability to provide
long-term recording storage, and analysis of data involving the relationship
between observed
abnormal body movements within the context of historical medication dose(s)
that was delivered to
a patient in order to precisely observe the instantaneous dosage requirements
of a patient with the
historically delivered medication rate(s) of an infusion pump while also
tracking and observing any
trending progression of the disease.
[00133] In certain embodiments, the motion sensors of an IPAS enabled insulin
pump serve as
an adjunct to the direct continuous measurement of a trackable value (e.g.
blood glucose) to
augment the insulin pump delivery rate in response to the existence of a
"Lifestyle" event while in
some embodiments the motion sensors in an IDDS serve as the primary means of
controlling the
delivery rate of medication.
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[00134] The foregoing description of embodiments of the present disclosure has
been presented
for the purpose of illustration and description. It is not intended to be
exhaustive or to limit the
invention to the form disclosed. While the exemplary application has focused
on the treatment of
Parkinson's disease, with minor programming and/or hardware modification, both
the monitoring
and closed-loop capability of IDDS may also be used with other neurological
conditions and
treatment, thus obvious modifications and variations are possible in light of
the above disclosure
and should be considered to be within the scope and spirit of the present
disclosure The
embodiments described were chosen to best illustrate the principles of the
invention and practical
applications thereof to enable one of ordinary skill in the art to utilize the
invention in various
embodiments and with various modifications as suited to the particular use
contemplated.
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