U.S. patent application number 12/098108 was filed with the patent office on 2008-08-07 for closed-loop method for controlling insulin infusion.
This patent application is currently assigned to MEDTRONIC MINIMED, INC.. Invention is credited to Kerstin Rebrin, Garry M. Steil.
Application Number | 20080188796 12/098108 |
Document ID | / |
Family ID | 27385045 |
Filed Date | 2008-08-07 |
United States Patent
Application |
20080188796 |
Kind Code |
A1 |
Steil; Garry M. ; et
al. |
August 7, 2008 |
Closed-Loop Method for Controlling Insulin Infusion
Abstract
A closed loop infusion system controls the rate that fluid is
infused into the body of a user. The closed loop infusion system
includes a sensor system, a controller, and a delivery system. The
sensor system includes a sensor for monitoring a condition of the
user. The sensor produces a sensor signal, which is representative
of the condition of the user. The sensor signal is used to generate
a controller input. The controller uses the controller input to
generate commands to operate the delivery system. The delivery
system infuses a liquid into the user at a rate dictated by the
commands from the controller. Preferably, the sensor system
monitors the glucose concentration in the body of the user, and the
liquid infused by the delivery system into the body of the user
includes insulin.
Inventors: |
Steil; Garry M.; (Pasadena,
CA) ; Rebrin; Kerstin; (Alameda, CA) |
Correspondence
Address: |
MEDTRONIC MINIMED INC.
18000 DEVONSHIRE STREET
NORTHRIDGE
CA
91325-1219
US
|
Assignee: |
MEDTRONIC MINIMED, INC.
Northridge
CA
|
Family ID: |
27385045 |
Appl. No.: |
12/098108 |
Filed: |
April 4, 2008 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10816021 |
Mar 31, 2004 |
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12098108 |
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10335275 |
Dec 31, 2002 |
7267665 |
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10816021 |
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09586175 |
Jun 1, 2000 |
6558351 |
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10335275 |
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60137601 |
Jun 3, 1999 |
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60162255 |
Oct 29, 1999 |
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Current U.S.
Class: |
604/66 |
Current CPC
Class: |
A61M 5/14244 20130101;
A61B 5/1495 20130101; A61M 5/1582 20130101; A61B 5/14539 20130101;
A61M 2230/201 20130101; A61B 5/14532 20130101; G16H 20/17 20180101;
A61M 2005/1581 20130101; A61B 5/6849 20130101; A61M 2005/1726
20130101; A61B 5/4839 20130101; A61B 5/14865 20130101; A61M 5/158
20130101; A61M 5/1723 20130101; A61B 5/7242 20130101 |
Class at
Publication: |
604/66 |
International
Class: |
A61M 5/142 20060101
A61M005/142 |
Claims
1.-32. (canceled)
33. A method for calculating the amount of insulin to be infused
into a body of a user, the method comprising: obtaining a blood
glucose concentration of the user; generating a controller input
based on the blood glucose concentration; and generating infusion
calculations by a proportional plus, integral plus, derivative
(PID) controller from the controller input using at least one
preset controller gain; wherein the at least one preset controller
gain is selected such that the infusion commands generated by the
PID controller infuses insulin into the body of the user in
response to the glucose concentration at a rate similar to a rate
that beta cells would release insulin in an individual with a
healthy normally functioning pancreas; and wherein the an automatic
blood withdrawal system is used to obtain the blood glucose
concentration of the user.
34. The method according to claim 33, further comprising: infusing
insulin based on the infusion calculations from the PID controller;
wherein the insulin is infused through an IV catheter connected to
the body of the user.
35. The method according to claim 33, wherein the at least one
preset controller gain includes at least one tuning parameter that
further modifies the commands generated by the PID controller to
create an insulin concentration profile that more closely resembles
the insulin concentration profile that would be generated by the
release of insulin by beta cells in an individual with a healthy
normally functioning pancreas.
36. The method according to claim 35, wherein the at least one
tuning parameter is an integrator leak.
37. The method according to claim 35, wherein the at least one
tuning parameter is a lead/lag compensator.
38. The method according to claim 35, wherein the at least one
tuning parameter is an integrator clip.
39. The method according to claim 35, wherein the at least one
tuning parameter is a feedback of predicted plasma insulin.
40. The method according to claim 33, wherein the at least one
preset controller gain is selected by a method that includes the
step of measuring an insulin response of at least one individual
with a healthy normally functioning pancreas and calculating the at
least one controller gain that causes the infusion commands to
generally match the insulin response of the at least one
individual.
41. The method according to claim 33, wherein the PID controller is
a bilinear PID controller.
Description
RELATED APPLICATIONS
[0001] This application is continuation-in-part of U.S. application
Ser. No. 09/586,175 filed Jun. 1, 2000, entitled "Closed Loop
System For Controlling Insulin Infusion," which claims priority on
U.S. Provisional Application Ser. No. 60/137,601 filed Jun. 3,
1999, entitled "Closed Loop Algorithms For Continuous Monitoring
And Insulin Infusion," and U.S. Provisional Application Ser. No.
60/162,255 filed Oct. 29, 1999 and entitled "Closed Loop Algorithms
For Continuous Monitoring And Insulin Infusion," all of which are
specifically incorporated by reference herein.
FIELD OF THE INVENTION
[0002] This invention relates to closed loop drug delivery systems
and more specifically to systems for controlling the infusion rate
of insulin based on continuously monitored body glucose levels.
BACKGROUND OF THE INVENTION
[0003] The pancreas of a normal healthy person produces and
releases insulin into the blood stream in response to elevated
blood plasma glucose levels. Beta cells (.beta.-cells), which
reside in the pancreas, produce and secrete the insulin into the
blood stream, as it is needed. If .beta.-cells become incapacitated
or die, a condition known as Type I diabetes mellitus (or in some
cases if .beta.-cells produce insufficient quantities of insulin,
Type II diabetes), then insulin must be provided to the body from
another source.
[0004] Traditionally, since insulin cannot be taken orally, insulin
has been injected with a syringe. More recently, use of infusion
pump therapy has been increasing, especially for delivering insulin
for diabetics. For example, external infusion pumps are worn on a
belt, in a pocket, or the like, and deliver insulin into the body
via an infusion tube with a percutaneous needle or a cannula placed
in the subcutaneous tissue. As of 1995, less than 5% of Type I
diabetics in the United States were using infusion pump therapy.
Presently over 7% of the more than 900,000 Type I diabetics in the
U.S. are using infusion pump therapy. And the percentage of Type I
diabetics that use an infusion pump is growing at an absolute rate
of over 2% each year. Moreover, the number of Type I diabetics is
growing at 3% or more per year. In addition, growing numbers of
insulin using Type II diabetics are also using infusion pumps.
Physicians have recognized that continuous infusion provides
greater control of a diabetic's condition, and are also
increasingly prescribing it for patients. Although offering
control, pump therapy can suffer from several complications that
make use of traditional external infusion pumps less desirable for
the user.
SUMMARY OF THE DISCLOSURE
[0005] According to an embodiment of the invention, a closed loop
infusion system and method for controlling blood glucose
concentration in the body of a user is described. Embodiments of
the present invention include obtaining a blood glucose level from
the body of the user, generating commands by a proportional plus,
integral plus, derivative (PID) controller from the obtained
glucose level, and infusing a liquid into the body of the user in
response to the commands. In particular embodiments, the PID
controller is a bilinear PID controller.
[0006] According to another embodiment of the invention, a closed
loop infusion system is for infusing a fluid into a user. The
closed loop infusion system includes a sensor system, a controller,
and a delivery system. The sensor system includes a sensor for
monitoring a condition of the user. The sensor produces a sensor
signal, which is representative of the condition of the user, and
is used to generate a controller input. The controller uses the
controller input to generate commands that affect the operation of
the delivery system. Accordingly, the delivery system infuses a
liquid into the user. In particular embodiments, glucose
concentration is monitored by the sensor system, and the liquid
delivered to the user includes insulin. In preferred embodiments,
the sensor system sends a message, generated using the sensor
signal, to the delivery system. The message is used to generate the
controller input. In particular embodiments, the sensor is a
subcutaneous sensor in contact with interstitial fluid. In further
particular embodiments, two or more sensors are included in the
sensor system. Still in further embodiments, the blood glucose
concentration is obtained through an IV catheter or a vascular
sensor. In addition, in particular embodiments the liquid is
delivered to through an IV catheter connected to the body of the
user.
[0007] In preferred embodiments, the sensor system is predominately
external to the user's body. And the delivery system is
predominately external to the user's body. In alternative
embodiments, the sensor system is predominately internal to the
user's body. In other alternative embodiments, the delivery system
is predominately internal to the user's body.
[0008] In preferred embodiments, the controller uses a first set of
one or more controller gains when the glucose concentration is
higher than a desired basal glucose concentration and the
controller uses a second set of one or more controller gains when
the glucose concentration is lower than a desired basal glucose
concentration. In alternative embodiments, the controller uses a
first set of one or more controller gains when the glucose
concentration is increasing and a second set of one or more
controller gains when the glucose concentration is decreasing. In
further alternative embodiments, the controller uses a first set of
one or more controller gains when the glucose concentration is
higher than a desired basal glucose concentration and the glucose
concentration is increasing; and the controller uses a second set
of one or more controller gains when the glucose concentration is
higher than a desired basal glucose concentration and the glucose
concentration is decreasing; and the controller uses a third set of
one or more controller gains when the glucose concentration is
lower than a desired basal glucose concentration and the glucose
concentration is increasing; and the controller uses a fourth set
of one or more controller gains when the glucose concentration is
lower than a desired basal glucose concentration and the glucose
concentration is decreasing.
[0009] In preferred embodiments, one or more controller gains are
selected such that the commands generated by the controller cause
the delivery system to infuse insulin into the body of the user in
response to a glucose concentration at a rate similar to the rate
that beta cells would release insulin in an individual with a
healthy normally functioning pancreas. Alternatively, one or more
controller gains are selected so that the commands generated by the
controller cause the delivery system to infuse insulin into the
body of the user in response to a glucose concentration at a rate
such that the insulin concentration profile in the user's blood
stream is similar to the insulin concentration profile that would
be generated by the release of insulin beta cells in an individual
with a healthy normally functioning pancreas. In other alternative
embodiments, a post-controller lead/lag compensator is used to
modify the commands generated by the controller to cause the
delivery system to infuse insulin into the body of the user in
response to a glucose concentration at a rate such that the insulin
concentration profile in the user's blood stream is similar to the
insulin concentration profile that would be generated by the
release of insulin beta cells in an individual with a healthy
normally functioning pancreas.
[0010] In preferred embodiments, one or more controller gains are
selected by a method that includes the step of measuring an insulin
response of at least one individual with a healthy normally
functioning pancreas and calculating the controller gains that
cause the commands to generally match the insulin response of at
least one individual. In particular embodiments, the derivative
gain K.sub.D is calculated using the first phase insulin response
(.phi.1) measured from a normal glucose tolerant (NGT) individual.
In further particular embodiments, one or more controller gains are
calculated from a ratio of one or more controller gains.
[0011] In preferred embodiments, one or more controller gains
includes at least one tuning parameter. In particular embodiments,
the tuning parameter is a post-controller lead/lag compensator is
used to modify the commands generated by the controller to
compensate for an insulin delivery delay due to infusing insulin
into a user' tissue rather than directly into the user's blood
stream. In additional embodiments, the tuning parameter is an
integrator clip. Still further embodiments, the tuning parameter is
a feedback of predicted plasma insulin. Yet further embodiments,
the tuning parameter is an integrator leak.
[0012] In alternative embodiments, the controller is influenced by
inputs of more than one measured body characteristic. For example,
measured body characteristics that might be used to influence the
controller include one or more amino acid concentrations, one or
more gastrointestinal hormone concentrations, one or more other
hormone concentrations, blood pH, interstitial fluid (ISF) pH, one
or more blood glucose concentrations, and one or more interstitial
fluid (ISF) glucose concentrations. In particular embodiments, the
sensor is a multi-sensor that measures both glucose concentration
and pH.
[0013] In preferred embodiments, the sensor system produces a
diagnostic signal in addition to the sensor signal, and the
diagnostic signal is used to indicate when the sensor signal
accuracy has diminished.
[0014] Other features and advantages of the invention will become
apparent from the following detailed description, taken in
conjunction with the accompanying drawings which illustrate, by way
of example, various features of embodiments of the invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] A detailed description of embodiments of the invention will
be made with reference to the accompanying drawings, wherein like
numerals designate corresponding parts in the several figures.
[0016] FIG. 1 is a block diagram of a closed loop glucose control
system in accordance with an embodiment of the present
invention.
[0017] FIG. 2 is a front view of closed loop hardware located on a
body in accordance with an embodiment of the present invention.
[0018] FIG. 3 (a) is a perspective view of a glucose sensor system
for use in an embodiment of the present invention.
[0019] FIG. 3 (b) is a side cross-sectional view of the glucose
sensor system of FIG. 3 (a).
[0020] FIG. 3 (c) is a perspective view of a sensor set of the
glucose sensor system of FIG. 3 (a) for use in an embodiment of the
present invention.
[0021] FIG. 3 (d) is a side cross-sectional view of the sensor set
of FIG. 3 (c).
[0022] FIG. 4 is a cross sectional view of a sensing end of the
sensor of FIG. 3 (d).
[0023] FIG. 5 is a top view of an infusion device with a reservoir
door in the open position, for use in an embodiment of the present
invention.
[0024] FIG. 6 is a side view of an infusion set with the insertion
needle pulled out, for use in an embodiment of the present
invention.
[0025] FIG. 7 is a circuit diagram of a sensor and its power supply
in accordance with an embodiment of the present invention.
[0026] FIG. 8 (a) is a diagram of a single device and its
components in accordance with an embodiment of the present
invention.
[0027] FIG. 8 (b) is a diagram of two devices and their components
in accordance with an embodiment of the present invention.
[0028] FIG. 8 (c) is another diagram of two devices and their
components in accordance with an embodiment of the present
invention.
[0029] FIG. 8 (d) is a diagram of three devices and their
components in accordance with an embodiment of the present
invention.
[0030] FIG. 9 is a table listing the devices of FIGS. 8 (a-d) and
their components.
[0031] FIG. 10 is a block diagram of the glucose sensor system of
FIG. 3 (a).
[0032] FIG. 11 (a) is a detailed block diagram of an A/D converter
for the glucose sensor system of FIG. 10 in accordance with an
embodiment of the present invention.
[0033] FIG. 11 (b) is a detailed block diagram of the A/D converter
for the glucose sensor system of FIG. 10 with a pulse duration
output selection option in accordance with an embodiment of the
present invention.
[0034] FIG. 12 is a circuit diagram of an I-F A/D converter of FIG.
10 accompanied by charts of node signals in accordance with an
embodiment of the present invention.
[0035] FIG. 13 is another circuit diagram of an I-F A/D converter
of FIG. 10 accompanied by charts of node signals in accordance with
an embodiment of the present invention.
[0036] FIG. 14 is still another circuit diagram of an I-F A/D
converter of FIG. 10 accompanied by charts of node signals in
accordance with an embodiment of the present invention.
[0037] FIG. 15 is a circuit diagram of an I-V A/D converter of FIG.
10 in accordance with an embodiment of the present invention.
[0038] FIG. 16 is a block diagram of the glucose sensor system of
FIG. 10 with a pre-filter and a filter in accordance with an
embodiment of the present invention.
[0039] FIG. 17 is a chart of an example of a pre-filter of FIG. 16
and its effects on digital sensor values Dsig in accordance with an
embodiment of the present invention.
[0040] FIG. 18 is frequency response chart for a filter of FIG. 16
in accordance with an embodiment of the present invention.
[0041] FIG. 19 (a) is a plot of a filtered and an unfiltered sensor
signal over time in accordance with an embodiment of the present
invention.
[0042] FIG. 19 (b) is close up of a section of the plot of FIG. 19
(a) in accordance with an embodiment of the present invention.
[0043] FIG. 20 is a cross-sectional view of a sensor set and an
infusion set attached to the body in accordance with an embodiment
of the present invention.
[0044] FIG. 21 is a frequency response chart of a time delay
correcting Weiner filter in accordance with an embodiment of the
present invention.
[0045] FIG. 22 is a plot of a digital sensor values Dsig before and
after time delay correction compared to actual glucose measurements
over time in accordance with an embodiment of the present
invention.
[0046] FIG. 23 (a) is a diagram of a glucose clamp (glucose level
with respect to time).
[0047] FIG. 23 (b) is a plot of insulin concentration in a normal
glucose tolerant (NGT) individual in response to various magnitudes
of glucose clamps of FIG. 23 (a).
[0048] FIG. 24 (a) is a diagram of a glucose clamp.
[0049] FIG. 24 (b) is a diagram of a proportional insulin response
to the glucose clamp of FIG. 24 (a) in accordance with an
embodiment of the present invention.
[0050] FIG. 24 (b) is a diagram of a proportional insulin response
to the glucose clamp of FIG. 24 (a) in accordance with an
embodiment of the present invention.
[0051] FIG. 24 (c) is a diagram of an integral insulin response to
the glucose clamp of FIG. 24 (a) in accordance with an embodiment
of the present invention.
[0052] FIG. 24 (d) is a diagram of a derivative insulin response to
the glucose clamp of FIG. 24 (a) in accordance with an embodiment
of the present invention.
[0053] FIG. 24 (e) is a diagram of a combined proportional,
integral, and derivative insulin response to the glucose clamp of
FIG. 24 (a) in accordance with an embodiment of the present
invention.
[0054] FIG. 25 (a) is a plot of insulin responses to a glucose
clamp for exercise trained and normal individuals.
[0055] FIG. 25 (b) is a bar chart of glucose uptake rates for
exercise trained and normal individuals.
[0056] FIG. 26 is a block diagram of a closed loop system to
control blood glucose levels through insulin infusion based on
glucose level feedback in accordance with an embodiment of the
present invention.
[0057] FIG. 27 is a detailed block diagram of the portion of the
control loop of FIG. 26 that is in the body in accordance with an
embodiment of the present invention.
[0058] FIGS. 28 (a and b) are plots of measured insulin responses
of two different normal glucose tolerant (NGT) individuals to a
glucose clamp for use with an embodiment of the present
invention.
[0059] FIG. 29 (a) is a plot of two different glucose sensor
outputs compared to glucose meter readings during a glucose clamp
in accordance with an embodiment of the present invention.
[0060] FIG. 29 (b) is a plot of actual insulin concentration in
blood compared to a controller commanded insulin concentration in
response to the glucose clamp of FIG. 29 (a) in accordance with an
embodiment of the present invention.
[0061] FIG. 30 is a top view of an end of a multi-sensor for
measuring both glucose concentration and pH in accordance with an
embodiment of the present invention.
[0062] FIG. 31 (a) is a representative drawing of blood glucose
compared to sensor measured blood glucose over time in accordance
with an embodiment of the present invention.
[0063] FIG. 31 (b) is a representative drawing of sensor
sensitivity over the same period of time as FIG. 31 (a) in
accordance with an embodiment of the present invention.
[0064] FIG. 31 (c) is a representative drawing of sensor resistance
over the same period of time as FIG. 31 (a) in accordance with an
embodiment of the present invention.
[0065] FIG. 32 is a block diagram using the derivative of sensor
resistance to determine when to recalibrate or replace the sensor
in accordance with an embodiment of the present invention.
[0066] FIG. 33 (a) is a plot of an analog sensor signal Isig over
time in accordance with an embodiment of the present invention.
[0067] FIG. 33 (b) is a plot of sensor resistance over the same
period of time as FIG. 32 (a) in accordance with an embodiment of
the present invention.
[0068] FIG. 33 (c) is a plot of the derivative of the sensor
resistance of FIG. 32 (b) in accordance with an embodiment of the
present invention.
[0069] FIG. 34 (a) is a bottom view of a telemetered characteristic
monitor in accordance with an embodiment of the present
invention.
[0070] FIG. 34 (b) is a bottom view of a different telemetered
characteristic monitor in accordance with an embodiment of the
present invention.
[0071] FIG. 35 (a) is a drawing of a blood plasma insulin response
to a glucose clamp in a normal glucose tolerant (NGT) individual in
accordance with an embodiment of the present invention.
[0072] FIG. 35 (b) is a drawing of the blood plasma insulin
response of FIG. 35 (a) when delayed due to insulin being delivered
to the subcutaneous tissue instead of directly into the blood
stream in accordance with an embodiment of the present
invention.
[0073] FIG. 36 (a) is a drawing of blood plasma insulin
concentration over time after an insulin bolus is delivered
directly into the blood stream in accordance with an embodiment of
the present invention.
[0074] FIG. 36 (b) is a drawing of a blood plasma insulin
concentration over time after an insulin bolus is delivered into
the subcutaneous tissue in accordance with an embodiment of the
present invention.
[0075] FIG. 37 is a block diagram of the closed loop system of FIG.
26 with the addition of a post-controller compensator and a
derivative filter in accordance with an embodiment of the present
invention.
[0076] FIG. 38 (a) is a plot of sensor signal measurements and Via
measurements with respect to time in accordance with an embodiment
of the present invention.
[0077] FIG. 38 (b) is a plot of a measured counter electrode
voltage Vcnt with respect to time in accordance with an embodiment
of the present invention.
[0078] FIG. 38 (c) is a plot of calculated sensor sensitivity with
respect to time in accordance with an embodiment of the present
invention.
[0079] FIG. 38 (d) is a plot of a calculation of sensor resistance
Rs.sub.1 with respect to time in accordance with an embodiment of
the present invention.
[0080] FIG. 38 (e) is a plot of another calculation of sensor
resistance Rs.sub.2 with respect to time in accordance with an
embodiment of the present invention.
[0081] FIG. 38 (f) is a plot of the derivative of sensor resistance
Rs.sub.1 of FIG. 38 (d) with respect to time in accordance with an
embodiment of the present invention.
[0082] FIG. 38 (g) is a plot of the derivative of the sensor
resistance Rs.sub.2 of FIG. 38 (e) with respect to time in
accordance with an embodiment of the present invention.
[0083] FIG. 38 (h) is a plot of when sensors were replaced with
respect to time in accordance with an embodiment of the present
invention.
[0084] FIGS. 39 (a) and (b) are a block diagrams of a closed loop
glucose control system in accordance with embodiments of the
present invention.
[0085] FIG. 40 is a block diagram of auto blood withdrawal and
return in accordance with an embodiment of the present
invention.
[0086] FIG. 41(a) is a plot actual blood glucose concentration in
accordance with an embodiment of the present invention.
[0087] FIG. 41(b) is a plot of actual insulin concentration in
blood compared to a controller commanded insulin concentration in
response to the blood glucose in FIG. 41(a) in accordance with an
embodiment of the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0088] As shown in the drawings for purposes of illustration, the
invention is embodied in a closed loop infusion system for
regulating the rate of fluid infusion into a body of a user based
on feedback from an analyte concentration measurement taken from
the body. In particular embodiments, the invention is embodied in a
control system for regulating the rate of insulin infusion into the
body of a user based on a glucose concentration measurement taken
from the body. In preferred embodiments, the system is designed to
model a pancreatic beta cell (.beta.-cell). In other words, the
system controls an infusion device to release insulin into a body
of a user in a similar concentration profile as would be created by
fully functioning human .beta.-cells when responding to changes in
blood glucose concentrations in the body.
[0089] Thus, the system simulates the body's natural insulin
response to blood glucose levels and not only makes efficient use
of insulin, but also accounts for other bodily functions as well
since insulin has both metabolic and mitogenic effects. However,
the algorithms must model the .beta.-cells closely, since
algorithms that are designed to minimize glucose excursions in the
body, without regard for how much insulin is delivered, may cause
excessive weight gain, hypertension, and atherosclerosis. In
preferred embodiments of the present invention, the system is
intended to emulate the in vivo insulin secretion pattern and to
adjust this pattern consistent with the in vivo .beta.-cell
adaptation experienced by normal healthy individuals. The in vivo
.beta.-cell response in subjects with normal glucose tolerance
(NGT), with widely varying insulin sensitivity (S.sub.1), is the
optimal insulin response for the maintenance of glucose
homeostasis.
[0090] Preferred embodiments include a glucose sensor system 10, a
controller 12 and an insulin delivery system 14, as shown in FIG.
1. The glucose sensor system 10 generates a sensor signal 16
representative of blood glucose levels 18 in the body 20, and
provides the sensor signal 16 to the controller 12. The controller
12 receives the sensor signal 16 and generates commands 22 that are
communicated to the insulin delivery system 14. The insulin
delivery system 14 receives the commands 22 and infuses insulin 24
into the body 20 in response to the commands 22.
[0091] Generally, the glucose sensor system 10 includes a glucose
sensor, sensor electrical components to provide power to the sensor
and generate the sensor signal 16, a sensor communication system to
carry the sensor signal 16 to the controller 12, and a sensor
system housing for the electrical components and the sensor
communication system.
[0092] Typically, the controller 12 includes controller electrical
components and software to generate commands for the insulin
delivery system 14 based on the sensor signal 16, and a controller
communication system to receive the sensor signal 16 and carry
commands to the insulin delivery system 14.
[0093] Generally, the insulin delivery system 14 includes an
infusion device and an infusion tube to infuse insulin 24 into the
body 20. In particular embodiments, the infusion device includes
infusion electrical components to activate an infusion motor
according to the commands 22, an infusion communication system to
receive the commands 22 from the controller 12, and an infusion
device housing to hold the infusion device.
[0094] In preferred embodiments, the controller 12 is housed in the
infusion device housing and the infusion communication system is an
electrical trace or a wire that carries the commands 22 from the
controller 12 to the infusion device. In alternative embodiments,
the controller 12 is housed in the sensor system housing and the
sensor communication system is an electrical trace or a wire that
carries the sensor signal 16 from the sensor electrical components
to the controller electrical components. In other alternative
embodiments, the controller 12 has its own housing or is included
in a supplemental device. In another alternative embodiment, the
controller is located with the infusion device and the sensor
system all within one housing. In further alternative embodiments,
the sensor, controller, and/or infusion communication systems may
utilize a cable, a wire, fiber optic lines, RF, IR, or ultrasonic
transmitters and receivers, or the like instead of the electrical
traces.
System Overview
[0095] Preferred embodiments of the invention include a sensor 26,
a sensor set 28, a telemetered characteristic monitor 30, a sensor
cable 32, an infusion device 34, an infusion tube 36, and an
infusion set 38, all worn on the body 20 of a user, as shown in
FIG. 2. The telemetered characteristic monitor 30 includes a
monitor housing 31 that supports a printed circuit board 33,
batteries 35, antenna (not shown), and a sensor cable connector
(not shown), as seen in FIGS. 3 (a) and 3 (b). A sensing end 40 of
the sensor 26 has exposed electrodes 42 and is inserted through
skin 46 into a subcutaneous tissue 44 of a user's body 20, as shown
in FIGS. 3 (d) and 4. The electrodes 42 are in contact with
interstitial fluid (ISF) that is present throughout the
subcutaneous tissue 44. The sensor 26 is held in place by the
sensor set 28, which is adhesively secured to the user's skin 46,
as shown in FIGS. 3 (c) and 3 (d). The sensor set 28 provides for a
connector end 27 of the sensor 26 to connect to a first end 29 of
the sensor cable 32. A second end 37 of the sensor cable 32
connects to the monitor housing 31. The batteries 35 included in
the monitor housing 31 provide power for the sensor 26 and
electrical components 39 on the printed circuit board 33. The
electrical components 39 sample the sensor signal 16 and store
digital sensor values (Dsig) in a memory and then periodically
transmit the digital sensor values Dsig from the memory to the
controller 12, which is included in the infusion device.
[0096] The controller 12 processes the digital sensor values Dsig
and generates commands 22 for the infusion device 34. Preferably,
the infusion device 34 responds to the commands 22 and actuates a
plunger 48 that forces insulin 24 out of a reservoir 50 located
inside the infusion device 34, as shown in FIG. 5. In particular
embodiments, a connector tip 54 of the reservoir 50 extends through
the infusion device housing 52 and a first end 51 of the infusion
tube 36 is attached to the connector tip 54. A second end 53 of the
infusion tube 36 connects to the infusion set 38. Insulin 24 is
forced through the infusion tube 36 into the infusion set 38 and
into the body 16. The infusion set 38 is adhesively attached to the
user's skin 46, as shown in FIG. 6. As part of the infusion set 38,
a cannula 56 extends through the skin 46 and terminates in the
subcutaneous tissue 44 completing fluid communication between the
reservoir 50 and the subcutaneous tissue 44 of the user's body
16.
[0097] In alternative embodiments, the closed-loop system can be a
part of a hospital-based glucose management system. Given that
insulin therapy during intensive care has been shown to
dramatically improve wound healing, reduce blood stream infections,
renal failure, and polyneuropathy mortality, irrespective of
whether subjects previously had diabetes (See Van den Berghe G. et
al. NEJM 345: 1359-67, 2001, which is incorporated by reference
herein), the present invention can be used in this hospital setting
to control the blood glucose level of a patient in intensive care.
In these alternative embodiments, since an IV hookup is typically
implanted into a patient's arm while the patient is in an intensive
care setting (e.g. ICU), a closed loop glucose control can be
established which piggy-backs off the existing IV connection. Thus,
in a hospital based system, intravenous (IV) catheters which are
directly connected to a patient vascular system for purposes of
quickly delivering IV fluids, can also be used to facilitate blood
sampling and direct infusion of substances (e.g. insulin,
anticoagulants) into the intra-vascular space. Moreover, glucose
sensors may be inserted through the IV line to give realtime
glucose levels from the blood stream. Therefore, depending on the
type of hospital based system, the alternative embodiments would
not necessarily need the described system components such as the
sensor 26, the sensor set 28, the telemetered characteristic
monitor 30, the sensor cable 32, the infusion tube 36, and the
infusion set 38 as described in the preferred embodiments. Instead,
standard blood glucose meters or vascular glucose sensors as
described in co-pending provisional application entitled
"Multi-lumen Catheter," filed Sep. 27, 2002, Ser. No. 60/414,248,
which is incorporated herein in its entirety by reference, can be
used to provide the blood glucose values to the infusion pump
control and the existing IV connection can be used to administer
the insulin to the patient.
[0098] It is important to appreciate that numerous combinations of
devices in the hospital-based system can be used with the closed
loop controller of the present invention. For example, as described
in FIG. 39b compared to the preferred system in FIG. 39a, an auto
blood glucose/intravenous insulin infusion system can automatically
withdraw and analyze blood for glucose concentration at fixed
intervals (preferably 5-20 minutes), extrapolate the blood glucose
values at a more frequent interval (preferably 1 minute), and use
the extrapolated signal for calculating an iv-insulin infusion
according to the controller described below. The modified auto
blood glucose/intravenous insulin infusion system would eliminate
the need for subcutaneous sensor compensation and subcutaneous
insulin compensation (as described with regards to the lead-lag
compensator below). The automatic withdrawal of blood, and
subsequent glucose determination can be accomplished with existing
technology (e.g. VIA or Biostator like blood glucose analyzer) or
by the system described in FIG. 40. The system in FIG. 40 uses a
peristaltic pump 420 to withdraw blood across an amperometric
sensor 410 (the same technology as used in sensor 26) and then
return the blood with added flush (0.5 to 1.0 ml) from the
reservoir 400. The flush can consist of any makeup of saline,
heparin, glucose solution and/or the like. If the blood samples are
obtained at intervals longer than 1 minute but less than 20
minutes, the blood glucose determinations can be extrapolated on a
minute-to-minute basis with extrapolation based on the present (n)
and previous values (n-1) to work with the logic of the controller
as described in detail below. For blood samples obtained at
intervals greater than 20 minutes, a zero-order-hold would be used
for the extrapolation. Based on these blood glucose values, the
infusion device can administer insulin based on the closed loop
controller described in greater detail below.
[0099] In other modifications to the system, a manual blood
glucose/intravenous insulin infusion system can be used where
frequent manual entry of blood glucose values from a standard blood
glucose meter (e.g. YSI, Beckman, etc) and extrapolate the values
at more frequent intervals (preferably 1 min) to create a surrogate
signal for calculating IV-insulin infusion. Alternatively, a sensor
blood glucose/intravenous insulin infusion system can use a
continuous glucose sensor (e.g. vascular, subcutaneous, etc.) for
frequent blood glucose determination. Moreover, the insulin
infusion can be administered subcutaneously rather than
intravenously in any one of the previous examples according to the
controller described below.
[0100] In still further alternative embodiments, the system
components may be combined in a smaller or greater number of
devices and/or the functions of each device may be allocated
differently to suit the needs of the user.
Controller
[0101] Once the hardware for a closed loop system is configured,
such as in the preferred embodiments described above, the affects
of the hardware on a human body are determined by the controller.
In preferred embodiments, the controller 12 is designed to model a
pancreatic beta cell (.beta.-cell). In other words, the controller
12 commands the infusion device 34 to release insulin 24 into the
body 20 at a rate that causes the insulin concentration in the
blood to follow a similar concentration profile as would be caused
by fully functioning human .beta.-cells responding to blood glucose
concentrations in the body 20.
[0102] A controller that simulates the body's natural insulin
response to blood glucose levels not only makes efficient use of
insulin but also accounts for other bodily functions as well since
insulin has both metabolic and mitogenic effects. Controller
algorithms that are designed to minimize glucose excursions in the
body without regard for how much insulin is delivered may cause
excessive weight gain, hypertension, and atherosclerosis. In
preferred embodiments, of the present invention, the controller 22
is intended to emulate the in vivo insulin secretion pattern and to
adjust this pattern to be consistent with in vivo .beta.-cell
adaptation. The in vivo .beta.-cell response in subjects with
normal glucose tolerance (NGT), with widely varying insulin
sensitivity (S.sub.1), is the optimal insulin response for the
maintenance of glucose homeostasis.
The .beta.-cell and PID Control
[0103] Generally, the in vivo p-cell response to changes in glucose
is characterized by "first" and "second" phase insulin responses.
This biphasic insulin response is clearly seen during hyperglycemic
clamps applied to NGT subjects, as shown in FIG. 23 (b). During a
hyperglycemic clamp the glucose level is rapidly increased from a
basal level G.sub.B to a new higher level G.sub.C and then held
constant at the higher-level G.sub.C as shown in FIG. 23 (a). The
magnitude of the increase in glucose (.DELTA.G) affects the insulin
response. Four insulin response curves are shown for four different
glucose clamp levels in FIG. 23 (b).
[0104] The biphasic insulin response of a .beta.-cell can be
modeled using components of a proportional, plus integral, plus
derivative (PID) controller. A PID controller is selected since PID
algorithms are stable for a wide variety of non-medical dynamic
systems, and PID algorithms have been found to be stable over
widely varying disturbances and changes in system dynamics.
[0105] The insulin response of .beta.-cells during a hyperglycemic
clamp is diagrammed in FIGS. 24 (a-e) using the components of a PID
controller to model the .beta.-cell. A proportional component
U.sub.P and a derivative component U.sub.D of the PID controller
may be combined to represent a first phase insulin response 440,
which lasts several minutes. A integral component U.sub.I of the
PID controller represents a second phase insulin response 442,
which is a steady increase in insulin release under hyperglycemic
clamp conditions. The magnitude of each component's contribution to
the insulin response is described by the following equations:
[0106] Proportional Component Response:
U.sub.P=K.sub.P(G-G.sub.B),
[0107] Integral Component Response:
U I = K I .intg. t a t ( G - G B ) t + I B , and ##EQU00001##
[0108] Derivative Component Response:
U D = K D G t , ##EQU00002## [0109] Where U.sub.P is the
proportional component of the command sent to the insulin delivery
system, [0110] U.sub.I is the integral component of the command
sent to the insulin delivery system, [0111] U.sub.D is the
derivative component of the command sent to the insulin delivery
system, [0112] K.sub.P is a proportional gain coefficient, [0113]
K.sub.1 is a integral gain coefficient, [0114] K.sub.D is a
derivative gain coefficient. [0115] G is a present blood glucose
level, [0116] G.sub.B is a desired basal glucose level, [0117] t is
the time that has passed since the last sensor calibration, [0118]
t.sub.0 is the time of the last sensor calibration, and [0119]
I.sub.B is a basal insulin concentration at to or can also be
described as U.sub.I(t.sub.0) The combination of the PID components
that model the two phases of insulin response by a .beta.-cell is
shown in FIG. 24 (e) as it responds to the hyperglycemic clamp of
FIG. 24 (a). FIG. 24 (e) shows that the magnitude of the first
phase response 440 is driven by the derivative and proportional
gains, K.sub.D and K.sub.P. And the magnitude of the second phase
response 442 is driven by the integral gain K.sub.I.
[0120] The components of the PID controller can also be expressed
in its discrete form:
[0121] Proportional Component Response:
P.sub.con.sup.n=K.sub.P(SG.sub.f.sup.n-G.sub.sp),
[0122] Integral Component Response:
I.sub.con.sup.n=I.sub.con.sup.n-1+K.sub.I(SG.sub.f.sup.nG.sub.sp);I.sub.-
con.sup.0=I.sub.b, and
[0123] Derivative Component Response:
D.sub.con.sup.n=K.sub.DdGdt.sub.f.sup.n, [0124] Where K.sub.P,
K.sub.I, and K.sub.D are the proportional, integral, and derivative
gain coefficients, SG.sub.f and dGdt.sub.f are the filtered sensor
glucose and derivative respectively, and the superscript n refers
to discrete time.
[0125] An acute insulin response is essential for preventing wide
postprandial glycemic excursions. Generally, an early insulin
response to a sudden increase in glucose level results in less
total insulin being needed to bring the glucose level back to a
desired basal glucose level. This is because the infusion of
insulin increases the percentage of glucose that is taken up by the
body. Infusing a large amount of insulin to increase the percentage
of glucose uptake while the glucose concentration is high results
in an efficient use of insulin. Conversely, infusing a large amount
of insulin while the glucose concentration is low results in using
a large amount of insulin to remove a relatively small amount of
glucose. In other words, a larger percentage of a big number is
more than a larger percentage of a small number. The infusion of
less total insulin helps to avoid development of insulin resistance
in the user. As well, first-phase insulin is thought to result in
an early suppression of hepatic glucose output.
[0126] Insulin sensitivity is not fixed and can change dramatically
in a body depending on the amount of exercise by the body. In one
study, for example, insulin responses in highly exercise-trained
individuals (individuals who trained more than 5 days a week) were
compared to the insulin responses in subjects with normal glucose
tolerance (NGT) during a hyperglycemic clamp. The insulin response
in exercise-trained individuals 444 was about 1/2 of the insulin
response of the NGT subjects 446, as shown in FIG. 25(a). But the
glucose uptake rate for each of the individuals (exercise-trained
448 or normal 450) was virtually identical, as shown in FIG. 25
(b). Thus, it can be speculated that the exercise-trained
individuals have twice the insulin sensitivity and half of the
insulin response leading to the same glucose uptake as the NGT
individuals. Not only is the first phase insulin response 440
reduced due to the effects of exercise, but the second phase
insulin response 442 has also been shown to adjust to insulin
sensitivity, as can be seen in FIG. 25(a).
[0127] In preferred embodiments, a closed loop control system may
be used for delivering insulin to a body to compensate for
.beta.-cells that perform inadequately. There is a desired basal
blood glucose level G.sub.B for each body. The difference between
the desired basal blood glucose level G.sub.B and an estimate of
the present blood glucose level G is the glucose level error
G.sub.E that must be corrected. The glucose level error G.sub.E is
provided as an input to the controller 12, as shown in FIG. 26.
[0128] If the glucose level error G.sub.E is positive (meaning that
the present estimate of the blood glucose level G is higher than
the desired basal blood glucose level G.sub.B) then the controller
12 generates an insulin delivery command 22 to drive the infusion
device 34 to provide insulin 24 to the body 20. In terms of the
control loop, glucose is considered to be positive, and therefore
insulin is negative. The sensor 26 senses the ISF glucose level and
generates a sensor signal 16. The sensor signal 16 is filtered and
calibrated to create an estimate of the present blood glucose level
452. In particular embodiments, the estimate of the present blood
glucose level G is adjusted with correction algorithms 454 before
it is compared to the desired basal blood glucose level G.sub.B to
calculate a new glucose level error G.sub.E to start the loop
again.
[0129] If the glucose level error G.sub.E is negative (meaning that
the present estimate of the blood glucose level is lower than the
desired basal blood glucose level G.sub.B) then the controller 12
reduces or stops the insulin delivery depending on whether the
integral component response of the glucose error G.sub.E is still
positive.
[0130] If the glucose level error G.sub.E is zero, (meaning that
the present estimate of the blood glucose level is equal to the
desired basal blood glucose level G.sub.B) then the controller 12
may or may not issue commands to infuse insulin depending on the
derivative component (whether the glucose level is raising or
falling) and the integral component (how long and by how much
glucose level has been above or below the basal blood glucose level
G.sub.B).
[0131] To more clearly understand the effects that the body has on
the control loop, a more detailed description of the physiological
affects that insulin has on the glucose concentration in the
interstitial fluid (ISF) is needed. In preferred embodiments, the
infusion device 34 delivers insulin through the cannula 56 of the
infusion set 38 into the ISF of the subcutaneous tissue 44 of the
body 20. And the insulin 24 diffuses from the local ISF surrounding
the cannula into the blood plasma and then spreads throughout the
body 20 in the main circulatory system, as described in the block
diagram of FIG. 27. The insulin then diffuses from the blood plasma
into the interstitial fluid ISF substantially through out the
entire body. The insulin 24 binds with and activates membrane
receptor proteins on cells of body tissues. This facilitates
glucose permeation into the activated cells. In this way, the
tissues of the body 20 take up the glucose from the ISF. As the ISF
glucose level decreases, glucose diffuses from the blood plasma
into the ISF to maintain glucose concentration equilibrium.
Finally, the glucose in the ISF permeates the sensor membrane and
affects the sensor signal 16.
[0132] In addition, insulin has direct and indirect affects on
liver glucose production. Increased insulin concentration decreases
liver glucose production. Therefore, acute and immediate insulin
response not only helps the body to efficiently take up glucose but
also substantially stops the liver from adding to the glucose in
the blood stream. In alternative embodiments, insulin is delivered
more directly into the blood stream instead of into the
interstitial fluid, such as delivery into veins, arteries, the
peritoneal cavity, or the like. And therefore, any time delay
associated with moving the insulin from the interstitial fluid into
the blood plasma is diminished. In other alternative embodiments,
the glucose sensor is in contact with blood or body fluids other
than interstitial fluid, or the glucose sensor is outside of the
body and measures glucose through a non-invasive means. The
embodiments that use alternative glucose sensors may have shorter
or longer delays between the blood glucose level and the measured
blood glucose level.
Selecting Controller Gains
[0133] In preferred embodiments, the controller gains K.sub.P,
K.sub.I, and K.sub.D, are selected so that the commands from the
controller 12 cause the infusion device 34 to release insulin 24
into the body 20 at a rate, that causes the insulin concentration
in the blood to follow a similar concentration profile, as would be
caused by fully functioning human .beta.-cells responding to blood
glucose concentrations in the body. In preferred embodiments, the
gains may be selected by observing the insulin response of several
normal glucose tolerant (NGT) individuals, with healthy normally
functioning .beta.-cells. The first step in determining a set of
controller gains is to take periodic measurements of blood glucose
and blood insulin concentrations from the group of NGT individuals.
Second, each individual in the group is subjected to a
hyperglycemic clamp, while continuing to periodically measure and
record the blood glucose and blood insulin concentrations. Third, a
least squares curve fit is applied to the recorded blood insulin
concentrations measured over time for each individual. The result
is a set of curves representing the insulin responses to the
hyperglycemic clamp for each individual of the group. Fourth, the
curves are used to calculate the controller gains K.sub.P, K.sub.I,
and K.sub.D, for each individual. And finally, the proportional
gains from each of the individuals are averaged together to obtain
an average proportional gain, K.sub.P, to be used in a controller
12. Similarly, the integral gains, K.sub.I, and the derivative
gains, K.sub.D, are averaged to obtain an average integral gain,
K.sub.I, and an average derivative gain, K.sub.D, for the
controller 12. Alternatively, other statistical values may be used
instead of averages such as, maximums, minimums, the high or low
one, two or three sigma standard deviation values, or the like. The
gains calculated for various individuals in a group may be filtered
to remove anomalous data points before statistically calculating
the gains to be used in a controller.
[0134] In an example, a least squares curve-fitting method is used
to generate representative insulin response curves from two fasted
individuals in a group, as shown in FIGS. 28 (a and b). Then the
controller gains were calculated from the insulin response curves
of the two representative individuals and are shown in Table 1.
When calculating the controller gains, the insulin clearance rate
(k), was assumed to be 10 (ml of insulin)/min/(kg. of body weight).
The insulin clearance rate k is the rate that insulin is taken out
of the blood stream in a body. Finally, the average value for each
type of gain is calculated using the measurements from the group,
as shown in Table 1.
TABLE-US-00001 TABLE 1 PID Controller Gains Calculated From The
Insulin Response Curves Of Two NGT Individuals. Proportional
Individuals Gain, K.sub.P Integral Gain, K.sub.I Derivative Gain,
K.sub.D a 0.000406 0.005650 0.052672 b 0.000723 0.003397 0.040403
Average 0.000564 0.004523 0.046537
[0135] The controller gains may be expressed in various units
and/or may be modified by conversion factors depending on
preferences for British or S. I. Units, floating-point or integer
software implementation, the software memory available, or the
like. The set of units for the controller gains in Table 1 is:
K.sub.P: (mU of insulin)/min/(Kg of body weight) per (mg of
glucose)/(dl of plasma); K.sub.I: (mU of insulin)/min/(Kg of body
weight) per (mg of glucose)/(dl of plasma) min.; and K.sub.D: (mU
of insulin)/min/(Kg of body weight) per (mg of glucose)/(dl of
plasma)/min.
[0136] In alternative embodiments, other curve fitting methods are
used to generate the insulin response curves from the measurements
of blood insulin concentrations.
[0137] An estimate of an insulin clearance rate (k), the
individual's body weight (W), and the insulin sensitivity S.sub.I
are needed to calculate the controller gains from the insulin
response curves for each NGT individual. The insulin clearance rate
(k) is generally proportional to body weight and is well documented
in literature. The individual's insulin sensitivity S.sub.I may be
measured using an intravenous glucose tolerance test, a
hyperinsulinemic clamp, or in the case of a diabetic, comparing the
individual's daily insulin requirement to their daily carbohydrate
intake.
[0138] In particular embodiments, two parameters, the insulin
sensitivity S.sub.I and the insulin clearance rate k, are measured
for each individual. In other embodiments, the insulin clearance
rate k is estimated from literature given the individual's body
weight. In other particular embodiments, longer or shorter insulin
clearance times are used. In still other embodiments, all of the
parameters are estimated. In additional embodiments, one or more
parameters are measured, while at least one parameter is estimated
from literature.
[0139] In other alternative embodiments, the controller gains are
calculated using a group of individuals with similar body types.
For example, the insulin response to a hyperglycemic clamp may be
measured for several tall, thin, NGT, males in order to calculate
the controller insulin response gains for each individual in the
group. Then the gains are statistically combined to generate a set
of representative controller gains for tall, thin, NGT, males. The
same could be done for other groups such as, but not limited to,
short, heavy, NGT, females; medium height, medium weight, highly
exercised trained, females; average height and weight 10 year olds;
or the like. Then the controller gains are selected for each
individual user based on the group that best represents them. In
further alternative embodiments, controller gains are uniquely
selected for each individual user. In particular embodiments, the
controller gains for a user are selected based on measurements of
insulin sensitivity, insulin clearing time, insulin appearance
time, insulin concentration, body weight, body fat percentage, body
metabolism, or other body characteristics such as pregnancy, age,
heart conditions, or the like.
[0140] In other alternative embodiments, the controller gains are
estimated as a function of a user's body weight W and insulin
sensitivity S.sub.I. A series of observations are used to justify
this method. The first observation is that the controller gains are
proportional to each other. In other words, small changes in
glucose concentration cause a small derivative response U.sub.D, a
small proportional response U.sub.P and a small integral response
U.sub.I. And larger changes in glucose concentration cause a
proportionally larger derivative response U.sub.D, a proportionally
larger proportional Up response and a proportionally larger
integral response U.sub.I, as shown in FIG. 23 (b). Changes in the
glucose concentration proportionally affect all three components of
the controller response U.sub.PID. The second observation is that
the first phase insulin response (.phi.1) is proportional to the
derivative gain K.sub.D. And the third observation is that two
constants may be readily obtained form information in published
literature or may be measured from a cross-section of the general
population. The two constants are the insulin clearance rate (k)
for a human given a body weight and the disposition index (DI) for
a human given a change in glucose concentration.
[0141] While there are multiple sources for the information needed
to calculate the insulin clearance rate k, one source is the
article "Insulin clearance during hypoglycemia in patients with
insulin-dependent diabetes mellitus", written by Kollind M et al.,
published in Horm Metab Res, 1991 July; 23(7):333-5. The insulin
clearance rate k is obtained from the insulin infused divided by
the steady state plasma insulin concentration. An insulin clearance
constant A.sub.k, which is independent of an individual's body
weight, may be obtained by dividing the insulin clearance rate k
(measured from a particular individual) by the individual's body
weight. The insulin clearance constant A.sub.k is generally the
same for all humans, except under extenuating circumstances such as
after an individual has contracted HIV, other metabolic affecting
diseases, or the like.
[0142] The disposition index (DI) for a human given a change in
glucose concentration is available from information presented in
the article "Quantification of the relationship between insulin
sensitivity and beta-cell function in human subjects. Evidence for
a hyperbolic function", written by Khan SE et al., published in
Diabetes, 1993 November; 42(11):1663-72.
[0143] Both, the disposition index DI and the insulin clearance
rate k may be measured directly from tests. The disposition index
DI may be calculated given the first phase insulin response
measured form a glucose clamp test and the individual's insulin
sensitivity measured from an insulin sensitivity test. The insulin
clearance rate k may be measured from an insulin clearance test.
The glucose clamp test and the insulin clearance test are described
in the above-mentioned articles and are well known in the art. The
insulin sensitivity S.sub.I may be measured using an intravenous
glucose tolerance test or a hyperinsulinemic clamp test.
[0144] Given these observations, then the following parameters may
be measured from an NGT individual's insulin response to a glucose
clamp: a desired first phase insulin response .phi.1, the ratio of
K.sub.D to K.sub.p, and the ratio of K.sub.D to K.sub.I. Then the
derivative gain K.sub.D may be calculated from the first phase
insulin response .phi.1 using the constants k and DI. And finally
K.sub.p and K.sub.I may be calculated using the ratios of K.sub.D
to K.sub.p and K.sub.D to K.sub.I.
[0145] The first phase insulin response .phi.1 may be observed in a
NGT individual as the area under the insulin response curve during
approximately the first 10 minutes of a glucose clamp. The increase
in the glucose concentration during the glucose clamp is
.DELTA.G=(G-G.sub.B), [0146] where G is equal to G.sub.C, the
glucose concentration during the clamp, and G.sub.B is the basal
glucose concentration before the clamp.
[0147] The importance of the first phase insulin response .phi.1
has been emphasized by studies indicating that, in subjects with
normal glucose tolerance (NGT), the product of first phase insulin
response .phi.1 and insulin sensitivity (S.sub.I) is a constant
known as the disposition index,
DI=.phi.1S.sub.1.
[0148] Therefore,
.phi.1 = DI S I . ##EQU00003##
For a different .DELTA.G there is a different .phi.1 and therefore
a different DI. But, the ratio DI/.DELTA.G is substantially
constant even for different individuals with different insulin
sensitivities.
[0149] The insulin sensitivity S.sub.I is defined as the percentage
of the glucose concentration that the body tissues will take up for
a given amount of insulin. The .beta.-cell naturally adapts to
changes in insulin sensitivity by adjusting the amount of insulin
it secretes during the first phase insulin response .phi.1. This
suggests that the body naturally seeks an optimal level of glucose
tolerance. A controller that mimics this characteristic of the
.beta.-cell more accurately simulates the body's natural insulin
response.
[0150] The instantaneous insulin response (RI) may be calculated
given the insulin clearance rate (k) and the first phase insulin
response .phi.1,
R.sub.I=k.phi.1
[0151] The insulin clearance rate k is proportional to body weight
(W), therefore substituting a proportional constant A.sub.k and the
user's body weight W for k and replacing .phi.1 with the ratio of
DI over S.sub.I yields the following equation:
R I = A k W DI S I . ##EQU00004##
[0152] The instantaneous insulin response R.sub.I may also be
expressed as the product of the derivative gain K.sub.D and the
change in glucose concentration .DELTA.G,
R.sub.I=K.sub.D.DELTA.G.
[0153] Setting the two equations for R.sub.I equal to each other
and solving for K.sub.D yields,
K D = W S I A k 2 DI .DELTA. G ##EQU00005##
[0154] As mentioned above, DI/.DELTA.G and A.sub.k are constants
available or calculated from data in published literature.
Combining the constants into a single constant, Q,
Q = A k DI .DELTA. G , ##EQU00006##
yields an equation for the derivative gain K.sub.D that is a
function of the user's body weight W and the user's insulin
sensitivity S.sub.I,
K D = W S I Q . ##EQU00007##
Once the derivative gain K.sub.D is calculated, the proportional
and integral gains are calculated using ratios. The ratio of
K.sub.D/K.sub.P can be set to the dominant time constant for
insulin action, ranging from 10-60 minutes, but more typically
20-40 minutes and preferably 30 minutes. For example, calculating
K.sub.P given K.sub.D using a time constant of 30 minutes, yields
the following relationship:
K D K P = 30 K P = K D 30 . ##EQU00008##
In a similar fashion, the ratio of K.sub.D/K.sub.I can be set to
the average ratio measured from a population of NGT individuals.
And K.sub.I can be calculated from K.sub.D.
[0155] In particular embodiments, the user enters their body weight
W and insulin sensitivity S.sub.I into the device that contains the
controller. Then the controller gains are automatically calculated
and used by the controller. In alternative embodiments, an
individual enters the user's body weight W and insulin sensitivity
S.sub.I into a device and the device provides the information to
the controller to calculate the gains.
[0156] A study was conducted to confirm that the insulin response
for an individual could be reproduced using the glucose sensor as
an input. In the study, glucose and insulin measurements were taken
while a hyperglycemic clamp was applied to a NGT individual. The
glucose level measurements, shown in FIG. 29 (a), were used as the
inputs to a mathematical model created to simulate a PID insulin
response controller. The insulin dosing commanded by the controller
in response to the glucose clamp very closely approximates the
actual insulin appearance in the NGT individual, as shown in FIG.
29 (b). The insulin concentration measured from periodic blood
samples 456 taken from the individual during the test are
represented by dots in FIG. 29 (b). The output from the
mathematical model simulating the insulin response commanded by the
controller is shown as a solid line 458 in FIG. 29 (b).
[0157] Three different devices were used to measure the
individual's blood glucose during the study. Blood glucose meter
readings 460 from periodic blood samples taken from the individual
are represented by the dots in FIG. 29 (a). Two MiniMed sensors
(such as those described in the section entitled "sensor", below)
were placed in the individual's subcutaneous tissue, and the sensor
readings 462, 464 are shown as lines in FIG. 29 (a). The sensor
readings 462, 464 are slightly delayed compared to the meter
readings 460. The delay is most likely due to the delay between
blood glucose and interstitial fluid (ISF) glucose and can be
substantially corrected through the use of a filter if needed. In
this study, the delay was not corrected by a filter and did not
significantly affect the controller's ability to command an insulin
response that matches the natural response of the NGT individual.
This study indicates that the PID insulin response controller model
is a good minimal model of insulin secretion that captures the
biphasic response of healthy .beta.-cells. Correction of the delay
is only expected to increase the accuracy of the model.
Fuzzy Logic to Select Between Multiple Sets of Controller Gains
[0158] In preferred embodiments, one set of controller gains is
used for a particular individual. In alternative embodiments, more
than one set of controller gains is used, and fuzzy logic is used
to select between sets of controller gains and to determine when to
change from one set of controller gains to another. In particular
alternative embodiments, the controller gains are different if the
glucose level is above or below the desired glucose basal level. In
other alternative embodiments, the controller gains are different
if the glucose level is increasing or decreasing. A justification
for different sets of gains comes from physiological studies that
indicate that .beta.-cells turn off faster than they turn on. In
still other alternative embodiments, the controller gains are
different depending on whether the glucose level is above or below
the desired glucose basal level and whether the glucose level is
increasing or decreasing, which results in four sets of controller
gains. In additional alternative embodiments, the controller gains
change depending on the magnitude of the hypoglycemic excursion. In
other words, the controller gains for small changes in glucose are
different than those for large changes in glucose.
Self-Tuning Controller Gains
[0159] Further embodiments may include a controller that self tunes
one or more the gains, K.sub.P, K.sub.I, K.sub.D to accommodate
changes in insulin sensitivity. In particular embodiments, previous
measurements of glucose levels are compared to the desired basal
glucose level G.sub.B. For example, the desired basal glucose level
G.sub.B is subtracted from the previous glucose level measurements.
Then any negative values, within a predefined time window, are
summed (in essence integrating the glucose level measurements that
were below the basal glucose level G.sub.B). If the resulting sum
is greater than a pre-selected hypoglycemic integral threshold,
then the controller gains are increased by a factor (1+.alpha.).
Conversely, if the integral of the glucose level measurements that
were measured above the basal glucose level G.sub.B within the
predefined time window is greater than a pre-selected hyperglycemic
integral threshold, then the controller gains are decreased by a
factor (1-.alpha.).
[0160] In particular embodiments, the predefined time window over
which the glucose concentration integrals are evaluated is
generally 24 hours, and the controller gains are adjusted if needed
at the end of each predefined time window. In alternative
embodiments, the integrals of the glucose level measurements are
continuously calculated over a moving window of time, and if either
integral exceeds a threshold, the gains are immediately adjusted.
In particular embodiments, the moving time window is one hour, and
the time window may be restarted whenever the gains are adjusted.
In other alternative embodiments, the time window is longer or
shorter depending on the sensor accuracy, the rate at which an
individual's insulin sensitivity changes, the computational
capabilities of the hardware, or the like.
[0161] In particular embodiments, the adjustment amount (.alpha.)
is 0.01. In alternative embodiments, the adjustment amount .alpha.
is greater or smaller depending on the sensor accuracy, the rate at
which an individual's insulin sensitivity changes, the rate at
which the sensor sensitivity S.sub.I changes, or the like. In still
other alternative embodiments, the adjustment amount .alpha. is
made larger or smaller depending on the amount that the integral of
the measured glucose levels exceeds a threshold. In this way, the
gains are adjusted by greater amounts if the measured glucose level
G is significantly deviating from the desired blood glucose level
G.sub.B and less if the measured glucose level G is closer to the
desired blood glucose level G.sub.B. In additional alternative
embodiments, the controller employs a Kalman filter.
Modifying the PID Controller to Incorporate an Integrator Leak
[0162] In preferred embodiments, the PID control response was
described with constant gain components, K.sub.P, K.sub.I, K.sub.D.
Although the preferred control response guarantees zero
steady-state error (i.e. steady state glucose minus a desired basal
glucose (G.sub.B)=0), inherently, the integral component,
U I = K I .intg. t o t ( G - G B ) t + U I ( t 0 ) ,
##EQU00009##
destabilizes feedback control because there is no temporal wind
down of the insulin response while the integral component models
the increase in the insulin response. Without any correction, the
integral component has a tendency to over-estimate the increase in
the insulin response. Since a small difference between steady-state
glucose and G.sub.B is typically acceptable in insulin response
control, an alternative modeling of the integral component can
incorporate an integrator leak to reduce the magnitude of the
destabilizing effect. Specifically, changes in U.sub.I(t) can be
described by a term proportional to the error in glucose and a term
that leaks in proportion to the magnitude of U.sub.I. This can be
expressed in the formula:
U I t = K I ( G - G B ) - K LEAK U I ; with initial condition U I (
t 0 ) ##EQU00010##
The parameter K.sub.LEAK is the reciprocal time constant of the
rate of leaking (.tau..sub.LEAK in min=1/K.sub.LEAK), where
.tau..sub.LEAK is a tuning parameter that can be set based on
empirical data, and be tied with the other gain components K.sub.P,
K.sub.I, K.sub.D. However, the current realization of the
artificial .beta.-cell has .tau..sub.LEAK as a user input. U.sub.I
can also be expressed in discrete form by standard methods.
Post-Controller (Lead/Lag) Compensator
[0163] In preferred embodiments, commands are issued from the
controller without regard to where in the body the insulin delivery
system will infuse the insulin. In essence, the assumption is that
the insulin is either delivered directly into the blood stream for
immediate use by the body, or that any time delays caused by
delivering the insulin somewhere in the body other than the blood
stream can be compensated for by adjusting K.sub.P, K.sub.I, and
K.sub.D. In this case, the commands generally model a .beta.-cell
insulin secretion profile, an example of which is shown in FIG. 35
(a). And since the .beta.-cells secrete insulin directly into the
blood stream, the .beta.-cell insulin secretion profile is the
intended blood plasma insulin concentration profile. However, an
insulin delivery delay may distort the intended blood plasma
insulin concentration profile, as shown in FIG. 35 (b). The insulin
delivery delay is the amount of time between the instant that the
command is given to the insulin delivery system to infuse insulin
and the time that insulin reaches the blood plasma. An insulin
delivery delay may be caused by a diffusion delay, represented by a
circle with an arrow 528 in FIG. 20, which is the time required for
insulin that has been infused into a tissue to diffuse into the
blood stream. Other contributors to insulin delivery delay may
include, time for the delivery system to deliver the insulin to the
body after receiving a command to infuse insulin, time for the
insulin to spread through out the circulatory system once it has
entered the blood stream, and/or by other mechanical or
physiological causes. In addition, the body clears insulin even
while an insulin dose is being delivered from the insulin delivery
system into the body. Since insulin is continuously cleared from
the blood plasma by the body, an insulin dose that is delivered to
the blood plasma too slowly or is delayed is at least partially, if
not significantly, cleared before the entire insulin dose fully
reaches the blood plasma. And therefore, the insulin concentration
profile in the blood plasma never achieves the same peak (nor
follows the same profile) it would have achieved if there were no
delay. Given an insulin dose delivered all at once into the blood
plasma at time zero, the insulin concentration in the blood plasma
is raised virtually instantaneously (not shown) and then would
decrease exponentially over time as the body clears (uses or
filters out) the insulin, as shown in FIG. 36 (a) per equation:
C P = I 0 V P - P 1 t ##EQU00011## [0164] Where C.sub.P is the
concentration of insulin in the blood plasma, [0165] I.sub.0 is a
mass of the insulin dose delivered directly to the blood plasma at
time zero, [0166] V.sub.P is a volume of the blood plasma in the
body, [0167] P.sub.I is a reciprocal time constant for insulin
clearance, and [0168] t is the time that has passed since the
delivery of the insulin dose directly into the blood plasma. The
time constant for insulin clearance P.sub.I may be calculated using
the following equation:
[0168] P 1 = - k V P ##EQU00012## [0169] Where [0170] k is the
volume insulin clearance rate, and [0171] V.sub.P is a volume of
the blood plasma in the body. Or the time constant for insulin
clearance P.sub.I may be obtained by providing insulin to an
individual that does not generate his own insulin, and then
periodically testing blood samples from the individual for insulin
concentration. Then, using an exponential curve fitting routine,
generate a mathematical expression for a best-fit curve for the
insulin concentration measurements, and observe the time constant
in the mathematical expression.
[0172] Given the same insulin dose (delivered at time zero all at
once) into the subcutaneous tissue, instead of directly into the
blood plasma, the concentration of insulin in the blood plasma
would begin to rise slowly as insulin diffuses from the
interstitial fluid ISF into the blood plasma, as shown in FIG. 36
(b). At the same time that insulin is entering the blood plasma,
the body is clearing insulin from the blood. While the rate at
which insulin is entering the blood plasma exceeds the insulin
clearance rate, the insulin concentration in the blood plasma
continues to increase. When the insulin clearance rate exceeds the
rate at which insulin is entering the blood plasma from the
interstitial fluid ISF, the insulin concentration in the blood
plasma begins to decrease. So, the result of delivering insulin
into the interstitial fluid ISF instead of directly into the blood
stream is that the insulin concentration in the blood plasma is
spread over time rather than increased virtually instantaneously to
a peak followed by a decay.
[0173] A bi-exponential equation may be used to model the insulin
concentration in blood plasma given an insulin dose delivered to
the subcutaneous tissue:
C P = I 0 D V p V ISF ( P 3 - P 2 ) ( - P 2 t - - P 3 t )
##EQU00013##
Where C.sub.P is the concentration of insulin in the blood plasma,
[0174] I.sub.0 is the mass of the insulin dose delivered to the
subcutaneous tissue at time zero, [0175] D is a diffusion
coefficient (the rate at which insulin diffuses from the
interstitial fluid ISF into the blood glucose) [0176] V.sub.P is a
volume of the blood plasma in the body, [0177] V.sub.SIF is a
volume of interstitial fluid ISF that the insulin is delivered to,
[0178] P.sub.2 is a time constant [0179] P.sub.3 is a time constant
greater than or equal to P.sub.2, and [0180] t is time since the
delivery of the insulin dose into the interstitial fluid ISF. The
time constants may be calculated using the quadratic formula:
[0180] P 2 , P 3 = - a 1 .+-. a 1 2 - 4 a 0 2 ##EQU00014## Where
##EQU00014.2## a 1 = D + K V P + D V ISF , and ##EQU00014.3## a 0 =
( D + K V P ) ( D V ISF ) - D 2 V ISF V P . ##EQU00014.4##
[0181] In alternative embodiments, a post-controller lead-lag
compensator 522 is used to modify the commands (U.sub.PID) to
compensate for the insulin delivery delay and/or the insulin
clearance rate k, as shown in FIG. 37. The post-controller lead-lag
compensator 522 is of the form
U COMP U PHD = s + .alpha. s + .gamma. ##EQU00015##
where 1/.alpha. and 1/.gamma. are the lead and lag constants
respectively, s is the Laplace variable, and U.sub.COMP is the
compensated commands calculated by the lead-lag compensator
522.
[0182] The PID controller generates commands (U.sub.PID) for a
desired insulin delivery rate into the blood plasma. The commands
U.sub.PID are calculated and issued periodically depending on the
update rate for the control loop, which is selected based on a
maximum anticipated rate of change of the blood glucose level, an
insulin delivery system minimum insulin dosage, insulin
sensitivity, a maximum and a minimum acceptable glucose
concentration, or the like. The commands U.sub.PID are used as
inputs to the post-controller lead-lag compensator 522.
[0183] In particular embodiments, the compensated commands
(U.sub.comp) issued from the post-controller lead-lag compensator
522 uses more than one value from the controller. In particular
embodiments, post-controller lead-lag compensator 522 uses the
present command (U.sub.PID.sup.n) and the previous command
(U.sub.PID.sup.n-1) to calculate a compensated command U.sub.comp
per a compensation equation:
U.sub.COMP.sup.n=(1-.gamma.)U.sub.COMP.sup.n-1+(1-.alpha.)U.sub.PID.sup.-
n-1
[0184] Where U.sub.PID.sup.n is the present command
[0185] U.sub.PID.sup.n-1 is the previous command,
[0186] U.sub.COMP.sup.n-1 is the previous compensated control
output,
[0187] .alpha. is the reciprocal lead time constant in min.sup.-1,
and
[0188] .gamma. is the reciprocal lag time constant in
min.sup.-1.
[0189] This is a first forward difference equation. However, other
forms can be used alternatively (e.g. first backward or bilinear),
but all result in a compensated control output (U.sub.COMP) that is
comprised of a weighted history of both past PID outputs
(U.sub.PID), and past compensated outputs (U.sub.COMP).
[0190] An alternative method of modifying the commands (U.sub.PID)
to compensate for the insulin delivery delay and/or the insulin
clearance can be performed based on a weighted history of past
insulin delivery. By giving the most recent delivery history more
weight, the weighted history of the previous insulin delivered can
then be subtracted from the present PID control output to yield a
compensated control output. Expressed in Laplace domain this
results in:
U COMP = PID E - .lamda. s + .alpha. U COMP ##EQU00016##
[0191] Where E is the Laplace transformed error signal (G-G.sub.B),
.lamda. determines how much the PID output is reduce in proportion
to the weighted history of past control outputs, and .alpha. is the
reciprocal time constant determining how long a history is weighted
(the preferred value of .alpha. would be equal to the reciprocal
dominant time constant or subcutaneous insulin appearance,
P.sub.2). Solving the compensated signals as a function of the
error results in:
U ( s ) E ( s ) = PID s + .alpha. w s + ( .alpha. + .lamda. ) = PID
s + .alpha. w s + .gamma. ##EQU00017##
[0192] which is identical to the previously described lead-lag
compensation.
[0193] In other alternative embodiments, additional previous
command values may be used. In still other alternative embodiments,
the compensation equation compensates for both time constants
P.sub.2 and P.sub.3.
[0194] In still more alternative embodiments, the controller gains
are modified to include the effects of the post-controller lead/lag
compensator so that the post-controller lead/lag compensator is not
needed to modify the commands to account for the insulin delivery
delay.
[0195] In particular embodiments, the insulin delivery system
provides finite insulin doses into the body in response to commands
from the controller. The smallest amount of insulin that the
insulin delivery system can deliver is the minimum finite insulin
dose. The controller may generate commands for a dose of insulin to
be delivered that is not a whole number multiple of the minimum
finite insulin dose. Therefore, either too much or too little
insulin is delivered by the insulin delivery system in response to
the commands. In particular alternative embodiments, the
post-controller lead-lag compensator truncates the command to the
nearest whole number multiple of the minimum finite insulin dose
and adds the remaining commanded volume of insulin to the next
command. In other alternative embodiments, a compensator rounds the
command to the nearest whole number multiple of the minimum finite
insulin dose. In still other alternative embodiments, other methods
are used to compensate for the difference between the commands and
the nearest whole number multiple of the minimum finite insulin
dose. In other embodiments, no compensation is needed.
Eliminating the Lead-Lag Compensator with Feedback of Predicted
Plasma Insulin
[0196] Yet in another alternative embodiment, the PID control
commands may be modified to emulate the effect of plasma insulin on
a .beta.-cell to determine optimal insulin administration by
feeding back a predicted plasma insulin based on the subcutaneous
insulin infusion. The net effect of such feedback is to replace an
undesired dynamic with a more desirable one and achieve a plasma
insulin profile that a .beta.-cell would achieve. This can be seen
as follows (using Laplace transformed variables). Assume the
relation between glucose above basal (G-G.sub.B) and insulin
delivery (ID) is described by a linear transfer function
ID(s)=C(s)(G(s)-G.sub.B)
where, C(s) may be, but is not necessarily, described by the PID
controller transfer function. If the .beta.-cell is using
peripheral insulin (I.sub.P(s)) levels to suppress insulin
secretion the predicted rate of insulin delivery would be modified
as:
ID(s)=C(s)(G(s)-G.sub.B)-k1.sub.P(s)
For portal insulin delivery the relation between ID(s) and plasma
insulin I.sub.P(s) is known to be approximated by a single time
delay:
I p ( s ) = k 1 s + .alpha. ID ( s ) ##EQU00018##
Substituting I.sub.P(s) value into the previous formula and making
k large results in:
ID ( s ) = C ( s ) ( G ( s ) - G B ) 1 + kk 1 s + .alpha. .apprxeq.
C ( s ) s + .alpha. kk 1 ( G ( s ) - G B ) ; ##EQU00019## 1
<< kk 1 s + .alpha. ##EQU00019.2##
Which would completely cancel the undesirable time constant
1/.alpha.. In practice a lower value of k would be used resulting
in:
ID ( s ) = C ( s ) ( G ( s ) - G B ) - kk 1 s + .alpha. ID ( s ) =
C ( s ) s + .alpha. s + .gamma. ( G ( s ) - G B ) ##EQU00020##
where .gamma.=.alpha.+kk.sub.1 (i.e. something greater than
.alpha.). Thus, the effect for the .beta.-cell, of adding a plasma
insulin feedback is to replace the portal insulin delivery time
constant (.alpha.) with a faster time constant
(.gamma.=.alpha.+kk.sub.1; .gamma.>.alpha.). In block diagram
form:
##STR00001##
To apply this mechanism to subcutaneous insulin delivery all that
is needed is the transfer function between sc insulin delivery and
plasma insulin. This transfer function is well approximated by a
bi-exponential time course (bolus response) or:
I P ( s ) IDsc ( s ) = k 2 ( s + .alpha. 1 ) ( s + .alpha. 2 )
##EQU00021## thus , ID ( s ) = C ( s ) ( G ( s ) - G B ) - kk 2 ( s
+ .alpha. 1 ) ( s + .alpha. 2 ) ID ( s ) = C ( s ) 1 1 + kk 2 ( s +
.alpha. ) ( s + .alpha. 2 ) ( G ( s ) - G B ) ##EQU00021.2##
in the limiting case as
kk.sub.2/(s+.alpha..sub.1)(s+.alpha..sub.2)>>1 this is
approximately equal
ID ( s ) = C ( s ) ( s + .alpha. 1 ) ( s + .alpha. 2 ) kk 2 ( G ( s
) - G B ) ##EQU00022##
where again, the undesirable time constants associated with
subcutaneous insulin delivery have been eliminated. In practice
they would just be replaced with more desirable rate constants
(i.e. faster time constants).
Correction of Hypoglycemic Excursion Around.about.200 Minutes
(Wind-down)
[0197] Previous modeling of .beta.-cells using a PID controller
gave excellent predictability of the "first" and "second" phase
insulin responses during prolonged periods of increased glucose
appearance. However, if the periods of increased glucose appearance
is followed by a rapid decrease in glucose appearance, the PID
controller would not be able to correctly predict the wind down of
the insulin response to lower glucose levels. FIG. 41(b)
illustrates the insulin response to the blood glucose level of FIG.
41(a) based on the clinical data (shown as data points), the PID
modeling (shown as a solid line), and correction of the PID for the
hypoglycemic excursion (shown as a dashed line).
[0198] In preferred embodiments, the hypoglycemic excursion is
corrected by modifying the PID controller to a PD control with
Adaptive Proportional Gain (or Bilinear PID controller), which is
modified form of the original PID equations. As described
previously, the discrete PID algorithm is as follows:
[0199] Proportional Component Response:
P.sub.con.sup.n=K.sub.P(SG.sub.f.sup.n-G.sub.sp),
[0200] Integral Component Response:
I.sub.con.sup.n=I.sub.con.sup.n-1+K.sub.1(SG.sub.f.sup.n-G.sub.sp);I.sub-
.con.sup.0=I.sub.b, and
[0201] Derivative Component Response:
D.sub.con.sup.n=K.sub.DdGdt.sub.f.sup.n, [0202] Where K.sub.P,
K.sub.I, and K.sub.D are the proportional, integral, and derivative
gain coefficients, SG.sub.f and dGdt.sub.f are the filtered sensor
glucose and derivative respectively, and the superscript n refers
to discrete time.
[0203] In the Bilinear PID controller, the proportional gain
K.sub.P is based on the integrated error term. The magnitude of
each component's contribution to the insulin response is described
by the following equations:
P.sub.con.sup.n=K.sub.p.sup.n(SG.sub.f.sup.n-INT)
D.sub.con.sup.n=K.sub.DdGdt.sub.f.sup.n
K.sub.p.sup.n=K.sub.p.sup.n-1+K.sub.I(SG.sub.f.sup.n-G.sup.sp), and
L.sub.p.sup.0=K.sub.P0
Where the proportional gain now integrates at rate K.sub.I(initial
value K.sub.P0) and the proportional component is related to an
intercept value (INT where (INT<G.sub.sp). The modified
formulation can be seen to fit the hypoglycemic glucose excursion
without systematic error as the adaptive PD line shown as a dashed
line in FIG. 39.
[0204] In additional embodiments, the Bilinear PID controller can
also incorporate an integrator leak by modifying the formula to
multiply the previous K.sub.P with a value such as .alpha. as
follows:
K.sub.p.sup.n=.alpha.K.sub.p.sup.n-1+K.sub.I(SG.sub.f.sup.n-G.sub.sp),
where .alpha..apprxeq.0.99
[0205] An alternative method of correcting the hypoglycemic glucose
excursion can be performed by integrator clip into the PID control.
PID controllers generally have integrator-reset rules that prevent
excessive "winding" and such a rule can be used to correct the
hypoglycemic glucose excursion. For example, the integrator can be
clipped as follows:
If (SG.ltoreq.60 mg/dl AND I.sub.con.sup.n-1>K.sub.P(SP-60))
then I.sub.con.sup.n-1=K.sub.P(SP-60)
This equation resets the integrator such that if the sensor glucose
falls below 60 mg/dl the insulin delivery is zero for all stable or
falling sensor glucose signals. The clipping limit represents an
absolute threshold, similar to the human counter regulatory
response.
[0206] However, other approaches that may emulate the .beta.-cell
more accurately include the use of piecewise continuous functions.
For example, the following function allows for progressive clipping
to be tuned:
.gamma. ( SG ) = .gamma. 0 + ( 1 - .gamma. 0 ) [ T 1 + SG T 1 - 60
] ##EQU00023## if ( SG .ltoreq. T 1 mg / dl AND I con n - 1 >
.gamma. K P ( SP - 60 ) ) then I con n - 1 = .gamma. K P ( SP - 60
) ##EQU00023.2##
This equation introduces two additional tuning parameters
(.gamma..sub.0 and T.sub.1) and starts to check the integrator
output at a higher threshold. For example, if .gamma..sub.0=5 and
T.sub.1=100 mg/dl, the integrator output would be clipped to 4
K.sub.P60 if glucose fell to 90 mg/dl, 3 K.sub.P60 if glucose fell
to 80 mg/dl and so forth until glucose reached 60 where it would be
clipped at K.sub.P60. Other functions than that proposed in the
above equation (e.g. functions based on the rate of fall of
glucose, or percent decrease in I.sub.con) may alternatively be
used.
System Configurations
[0207] The following sections provide exemplary, but not limiting,
illustrations of components that can be utilized with the
controller described above. Various changes in components, layout
of various components, combinations of elements, or the like may be
made without departing from the scope of the embodiments of the
invention.
[0208] Before it is provided as an input to the controller 12, the
sensor signal 16 is generally subjected to signal conditioning such
as pre-filtering, filtering, calibrating, or the like. Components
such as a pre-filter, one or more filters, a calibrator and the
controller 12 may be split up or physically located together, and
may be included with a telemetered characteristic monitor
transmitter 30, the infusion device 34, or a supplemental device.
In preferred embodiments, the pre-filter, filters and the
calibrator are included as part of the telemetered characteristic
monitor transmitter 30, and the controller 20 is included with the
infusion device 34, as shown in FIG. 8(b). In alternative
embodiments, the pre-filter is included with the telemetered
characteristic monitor transmitter 30 and the filter and calibrator
are included with the controller 12 in the infusion device, as
shown in FIG. 8(c). In other alternative embodiments, the
pre-filter may be included with the telemetered characteristic
monitor transmitter 30, while the filter and calibrator are
included in the supplemental device 41, and the controller is
included in the infusion device, as shown in FIG. 8(d). To
illustrate the various embodiments in another way, FIG. 9 shows a
table of the groupings of components (pre-filter, filters,
calibrator, and controller) in various devices (telemetered
characteristic monitor transmitter, supplemental device, and
infusion device) from FIGS. 8(a-d). In other alternative
embodiments, a supplemental device contains some of (or all of) the
components.
[0209] In preferred embodiments, the sensor system generates a
message that includes information based on the sensor signal such
as digital sensor values, pre-filtered digital sensor values,
filtered digital sensor values, calibrated digital sensor values,
commands, or the like. The message may include other types of
information as well such as a serial number, an ID code, a check
value, values for other sensed parameters, diagnostic signals,
other signals, or the like. In particular embodiments, the digital
sensor values Dsig may be filtered in the telemetered
characteristic monitor transmitter 30, and then the filtered
digital sensor values may be included in the message sent to the
infusion device 34 where the filtered digital sensor values are
calibrated and used in the controller. In other embodiments, the
digital sensor values Dsig may be filtered and calibrated before
being sent to the controller 12 in the infusion device 34.
Alternatively, the digital sensor values Dsig may be filtered, and
calibrated and used in the controller to generate commands 22 that
are then sent from the telemetered characteristic monitor
transmitter 30 to the infusion device 34.
[0210] In further embodiments, additional optional components, such
as a post-calibration filter, a display, a recorder, and a blood
glucose meter may be included in the devices with any of the other
components or they may stand-alone. Generally, if a blood glucose
meter is built into one of the devices, it will be co-located in
the device that contains the calibrator. In alternative
embodiments, one or more of the components are not used.
[0211] In preferred embodiments, RF telemetry is used to
communicate between devices, such as the telemetered characteristic
monitor transmitter 30 and the infusion device 34, which contain
groups of components. In alternative embodiments, other
communication mediums may be employed between devices such as
wires, cables, IR signals, laser signals, fiber optics, ultrasonic
signals, or the like
Filtering
[0212] In preferred embodiments, the digital sensor values Dsig
and/or the derivative of the digital sensor values are processed,
filtered, modified, analyzed, smoothed, combined, averaged,
clipped, scaled, calibrated, or the like, to minimize the effects
of anomalous data points before they are provided as an input to
the controller. In particular embodiments, the digital sensor
values Dsig are passed through a pre-filter 400 and then a filter
402 before they are passed to the transmitter 70, as shown in FIG.
16. The filters are used to detect and minimize the effects of
anomalous digital sensor values Dsig. Some causes of anomalous
digital sensor values Dsig may include temporary signal transients
caused by sensor separation from the subcutaneous tissue, sensor
noise, power supply noise, temporary disconnects or shorts, and the
like. In particular embodiments, each individual digital sensor
value Dsig is compared to maximum and minimum value-thresholds. In
other particular embodiments, the differences between consecutive
pairs of digital sensor values Dsig are compared with
rate-of-change-thresholds for increasing or decreasing values.
[0213] Pre-Filter [0214] In particular embodiments, the pre-filter
400 uses fuzzy logic to determine if individual digital sensor
values Dsig need to be adjusted. The pre-filter 400 uses a subset
of a group of digital sensor values Dsig to calculate a parameter
and then uses the parameter to determine if individual digital
sensor values Dsig need to be adjusted in comparison to the group
as a whole. For example, the average of a subset of a group of
digital sensor values Dsig may be calculated, and then noise
thresholds may be placed above and below the average. Then
individual digital sensor values Dsig within the group are compared
to noise thresholds and eliminated or modified if they are outside
of the noise thresholds. [0215] A more detailed example is provided
below to more clearly illustrate, but not limit, an embodiment of a
pre-filter. A group of eight digital sensor values Dsig are shown
in FIG. 17 including a most recently sampled value, labeled L,
sampled from the analog sensor signal Isig at time i, and the seven
previous values K, H, G, F, E, D, and C sampled at times (i-1)
through (i-7). An average value is calculated using the four
temporally middle values in the group, H, G, F, and E sampled at
times (i-2) through (i-5). The calculated average value is
represented as a dashed/dotted average line 404. A high noise
threshold 406 is established at 100% above the average line 404. In
other words, the magnitude of the high noise threshold 406 is two
times the magnitude of the average line 404. A negative noise
threshold 408 is established at 50% below the average line 404. In
other words, the magnitude of the negative noise threshold 408 is
one half of the magnitude of the average line 404. The individual
magnitudes of each of the eight values, L, K, H, G, F, E, D, and C
are compared to the high and negative noise thresholds 406 and 408.
If a value is above the high noise threshold 406 or below the
negative noise threshold 408 then the value is considered anomalous
and the anomalous value is replaced with the magnitude of the
average line 404. In the example shown in FIG. 17, the value K is
above the high noise threshold 406 so it is replaced with the
average value M. Also, the value D is below the negative noise
threshold 408 so it is replaced with the average value N. In this
way noisy signal spikes are reduced. Therefore, in the example,
values L, K, H, G, F, E, D, and C are inputs to the pre-filter 400
and values L, M, H, G, F, E, N, and C are outputs from the
pre-filter 400. In alternative embodiments, other noise threshold
levels (or percentages) may be used. In other alternative
embodiments, values outside of the thresholds may be replaced with
values other than the average value, such as the previous value,
the value of the closest threshold, a value calculated by
extrapolating a trend line through previous data, a value that is
calculated by interpolation between other values that are inside
the thresholds, or the like. [0216] In preferred embodiments, when
any of a group's values are outside of the noise thresholds 406 or
408 then a warning flag is set. If one to three values are outside
of the noise thresholds 406 or 408, a `noise` flag is set. If more
than three values are outside of the noise thresholds 406 or 408, a
`discard` flag is set which indicates that the whole group of
values should be ignored and not used. In alternative embodiments,
more or less values need be outside of the thresholds 406 or 408 to
trigger the `noise` flag or the `discard` flag. [0217] In preferred
embodiments, each digital sensor value Dsig is checked for
saturation and disconnection. To continue with the example of FIG.
17, each individual value is compared to a saturation threshold
410. If a value is equal to or above the saturation threshold 410
then a `saturation` flag is set. In particular embodiments, when
the `saturation` flag is set, a warning is provided to the user
that the sensor 26 may need calibration or replacement. In further
particular embodiments, if an individual digital sensor value Dsig
is at or above the saturation threshold 410, the individual digital
sensor value Dsig may be ignored, changed to a value equal to the
average line 404, or the entire group of values associated with the
individual digital sensor value Dsig may be ignored. In preferred
embodiments, the saturation threshold 410 is set at about 16% below
the maximum value of the range of digital sensor values that may be
generated. In preferred embodiments, the maximum digital sensor
value represents a glucose concentration greater than 150 mg/dl. In
alternative embodiments, the maximum digital sensor value may
represent larger or smaller a glucose concentrations depending on
the range of expected glucose concentrations to be measured, the
sensor accuracy, the sensor system resolution needed for closed
loop control, or the like. The full range of values is the
difference between the maximum and the minimum digital sensor value
that may be generated. Higher or lower saturation threshold levels
may be used depending on an expected signal range of the sensor,
sensor noise, sensor gains, or the like. [0218] Similarly, in
preferred embodiments, if a digital signal value Dsig is below a
disconnect threshold 412, then a `disconnect` flag is set
indicating to a user that the sensor is not properly connected to
the power supply and that the power supply or sensor may need
replacement or recalibration. In further particular embodiments, if
a digital sensor value Dsig is below the disconnect threshold 412,
the individual value may be ignored, changed to a value equal to
the average line 404, or the entire group of values associated with
the individual digital sensor value Dsig may be ignored. In
preferred embodiments, the disconnect threshold 410 is set at about
20% of the full range of values. Higher or lower disconnect
threshold levels may be used depending on an expected signal range
of the sensor, sensor system noise, sensor gains, or the like.
[0219] In alternative embodiments, other methods are used to
pre-filter the digital sensor values Dsig such as rate-of-change
thresholds, rate-of-change squared thresholds, noise thresholds
about a least squares fit line rather than about the average of a
subset of a group's values, higher or lower noise threshold lines,
or the like.
[0220] Noise Filter [0221] After the digital sensor values Dsig are
evaluated, and if necessary, modified by the pre-filter 400, the
digital sensor values Dsig are passed to the filter 402. The filter
402 may be used to reduce noise in particular frequency bands.
Generally the body's blood glucose level 18 changes relatively
slowly compared to a rate at which digital sensor values Dsig are
collected. Therefore, high frequency signal components are
typically noise, and a low pass filter may be used to improve the
signal to noise ratio. [0222] In preferred embodiments, the filter
402 is a finite impulse response (FIR) filter used to reduce noise.
In particular embodiments, the FIR filter is a 7.sup.th order
filter tuned with a pass band for frequencies from zero to 3 cycles
per hour (c/hr) and a stop band for frequencies greater than about
6 c/hr, as shown in an example frequency response curve 414 in FIG.
18. However, typically FIR filters tuned with a pass band for
frequencies from zero up to between about 2 c/hr and 5 c/hr and a
stop band beginning at 1.2 to three times the selected pass band
frequency will sufficiently reduce noise while passing the sensor
signal. In particular embodiments, FIR filters tuned with a pass
band for frequencies from zero up to between about 2 c/hr and 10
c/hr and a stop band beginning at 1.2 to three times the selected
pass band frequency will sufficiently reduce noise. In the 7.sup.th
order filter, unique weighting factors are applied to each of eight
digital sensor values Dsig. The digital sensor values Dsig include
the most recently sampled value and the seven previous values. The
effects of a low pass filter on a digital sensor values collected
at one minute intervals is shown in FIGS. 19 (a) and (b). An
unfiltered sensor signal curve 416 of digital sensor values is
contrasted with a curve of the same signal after the effects of a
7.sup.th order FIR filter 418. The filtered signal curve 418 is
delayed and the peaks are smoother compared to the unfiltered
sensor signal curve 416. In other particular embodiments, higher or
lower order filters may be used. In still other particular
embodiments, filter weighting coefficients may be applied to
digital sensor values Dsig collected at time intervals shorter or
longer than one minute depending on the desired sensor sample rate
based on the body's physiology, the computational capabilities of
the telemetered characteristic monitor transmitter 30, the sensor's
response time, or the like. In alternative embodiments, filters
with other frequency responses may be used to eliminate other noise
frequencies depending on the type of sensor, noise from the power
supply or other electronics, the sensor's interaction with the
body, the effects of body motion on the sensor signal, or the like.
In still other alternative embodiments, the filter is an infinite
impulse response (IIR) filter.
[0223] Delay Compensation Filter [0224] Aside from noise reduction,
a filter may used to compensate for time delays. Ideally, a sensor
would provide a real time, noise-free measurement of a parameter
that a control system is intended to control, such as a blood
glucose measurement. However, realistically there are
physiological, chemical, electrical, and algorithmic sources of
time delays that cause the sensor measurement to lag behind the
present value of blood glucose. [0225] A physiological delay 422 is
due to the time required for glucose to move between blood plasma
420 and interstitial fluid (ISF). The delay is represented by the
circled double headed arrow 422 in FIG. 20. Generally, as discussed
above, the sensor 26 is inserted into the subcutaneous tissue 44 of
the body 20 and the electrodes 42 near the tip of the sensor 40 are
in contact with interstitial fluid (ISF). But the desired parameter
to be measured is the concentration of blood glucose. Glucose is
carried throughout the body in blood plasma 420. Through the
process of diffusion, glucose moves from the blood plasma 420 into
the ISF of the subcutaneous tissue 44 and vice versa. As the blood
glucose level 18 changes so does the glucose level in the ISF. But
the glucose level in the ISF lags behind the blood glucose level 18
due to the time required for the body to achieve glucose
concentration equilibrium between the blood plasma 420 and the ISF.
Studies show the glucose lag times between blood plasma 420 and ISF
vary between 0 to 30 minutes. Some parameters that may affect the
glucose lag time between blood plasma 420 and ISF are the
individual's metabolism, the current blood glucose level, whether
the glucose level is rising, or falling, or the like. [0226] A
chemical reaction delay 424 is introduced by the sensor response
time, represented by the circle 424 surrounding the tip of the
sensor 26 in FIG. 20. The sensor electrodes 42 are coated with
protective membranes that keep the electrodes 42 wetted with ISF,
attenuate the glucose concentration, and reduce glucose
concentration fluctuations on the electrode surface. As glucose
levels change, the protective membranes slow the rate of glucose
exchange between the ISF and the electrode surface. In addition,
there is a chemical reaction delay simply due to the reaction time
for glucose to react with glucose oxidase GOX to generate hydrogen
peroxide, and the reaction time for a secondary reaction, the
reduction of hydrogen peroxide to water, oxygen and free electrons.
[0227] There is also a processing delay as the analog sensor signal
Isig is converted to digital sensor values Dsig. In preferred
embodiments, the analog sensor signal Isig is integrated over
one-minute intervals and then converted to a number of counts. In
essence an A/D conversion time results in an average delay of 30
seconds. In particular embodiments, the one-minute values are
averaged into 5-minute values before they are sent to the
controller. The resulting average delay is two and one half
minutes. In alternative embodiments, longer or shorter integration
times are used resulting in longer or shorter delay times. In other
embodiments the analog sensor signal current Isig is continuously
converted to an analog voltage Vsig and a A/D converter samples the
voltage Vsig every 10 seconds. Then six 10-second values are
pre-filtered and averaged to create a one-minute value. Finally,
five 1-minute values are filtered and then averaged creating a
five-minute value resulting in an average delay of two and one half
minutes. Other embodiments use other electrical components or other
sampling rates and result in other delay periods. [0228] Filters
also introduce a delay due to the time required to acquire a
sufficient number of digital sensor values Dsig to operate the
filter. Higher order filters, by definition, require more digital
sensor values Dsig. Aside from the most recent digital sensor value
Dsig, FIR filters use a number of previous values equal to the
order of the filter. For example, a 7.sup.th order filter uses 8
digital sensor values Dsig. There is a time interval between each
digital sensor value Dsig. To continue with the example, if the
time interval between digital sensor values Dsig is one minute,
then the oldest digital sensor value Dsig used in a 7.sup.th order
FIR filter would be seven minutes old. Therefore, the average time
delay for all of the values used in the filter is three and a half
minutes. However, if the weighting factors associated with each of
the values are not equal then the time delay may be longer or
shorter than three and one half minutes depending on the effects of
the coefficients. [0229] Preferred embodiments of the invention
include a FIR filter that compensates for both the various time
delays, of up to about 30 minutes as discussed above, and high
frequency noise, greater than about 10 c/hr also discussed above.
Particular embodiments employ a 7.sup.th order Weiner type FIR
filter. The coefficients for the filter are selected to correct for
time lags while simultaneously reducing high frequency noise. An
example of a frequency response curve 426 is shown in FIG. 21. The
example frequency response curve 416 is generated for a Weiner
filter with a pass band for frequencies from zero up to about 8
c/hr and a stop band for frequencies greater than about 15 c/hr for
a sensor with a sensitivity of about 20 .mu.A/100 mg/dl. A study
conducted with sensors in dogs demonstrates that a FIR filter may
be used to compensate for time delays. During the study a filter
was used to compensate for a time delay of about 12 minutes. The
results, presented in FIG. 22, show dots 428 representing actual
blood plasma glucose levels measured with a blood glucose meter, a
broken line 430 representing sensor measurements without delay
compensation, and a solid line 432 representing sensor measurements
with delay compensation. The sensor in the test was abnormally low
in sensitivity. Studies with average sensitivity sensors in humans
are indicating a time delay of about 3 to 10 minutes is more
normal. Other filter coefficients and other orders of filters may
be used to compensate for the time delay and/or noise. [0230] In
alternative embodiments, other types of filters may be used as long
as they remove a sufficient portion of the noise from the sensor
signal. In other alternative embodiments, no time compensation is
used if the rate of change in the blood glucose level is slow
compared to the time delay. For example, a five-minute delay
between blood plasma glucose and a sensor measurement does not have
to be corrected for a closed loop glucose control system to
function.
[0231] Derivative Filter [0232] Further embodiments may include a
filter to remove noise from the derivative of the sensor signal
before the controller uses it. A derivative is taken from the
digital sensor values Dsig, which results in digital derivative
sensor values (dDsig/dt). The digital derivative sensor values
dDsig/dt are passed through a FIR filter. In particular
embodiments, the derivative filter is at least a 7.sup.th order FIR
filter tuned to remove high frequency noise. In alternative
embodiments, higher or lower order filters may be used and the
filters may be tuned to remove various frequencies of noise. In
other alternative embodiments, a derivative is taken from the
glucose level error G.sub.E values and then passed through a
derivative filter 526, as shown in FIG. 37. In further alternative
embodiments, a derivative is taken of an analog sensor signal Isig
and a hardware filter is used to remove noise.
Calibration
[0233] In preferred embodiments, after filtering, the digital
sensor values Dsig are calibrated with respect to one or more
glucose reference values. The glucose reference values are entered
into the calibrator and compared to the digital sensor values Dsig.
The calibrator applies a calibration algorithm to convert the
digital sensor values Dsig, which are typically in counts into
blood glucose values. In particular embodiments, the calibration
method is of the type described in U.S. patent application Ser. No.
09/511,580, filed on Feb. 23, 2000, entitled "GLUCOSE MONITOR
CALIBRATION METHODS", which is incorporated by reference herein. In
particular embodiments, the calibrator is included as part of the
infusion device 34 and the glucose reference values are entered by
the user into the infusion device 34. In other embodiments, the
glucose reference values are entered into the telemetered
characteristic monitor transmitter 30 and the calibrator calibrates
the digital sensor values Dsig and transmits calibrated digital
sensor values to the infusion device 34. In further embodiments,
the glucose reference values are entered into a supplemental device
where the calibration is executed. In alternative embodiments, a
blood glucose meter is in communication with the infusion device
34, telemetered characteristic monitor transmitter 30 or
supplemental device so that glucose reference values may be
transmitted directly into the device that the blood glucose meter
is in communication with. In additional alternative embodiments,
the blood glucose meter is part of the infusion device 34,
telemetered characteristic monitor transmitter 30 or supplemental
device such as that shown in U.S. patent application Ser. No.
09/334,996, filed on Jun. 17, 1999, entitled "CHARACTERISTIC
MONITOR WITH A CHARACTERISTIC METER AND METHOD OF USING THE SAME",
which is incorporated by reference herein.
[0234] In preferred embodiments, to obtain blood glucose reference
values, one or more blood samples are extracted from the body 20,
and a common, over-the-counter, blood glucose meter is used to
measure the blood plasma glucose concentration of the samples. Then
a digital sensor value Dsig is compared to the blood glucose
measurement from the meter and a mathematical correction is applied
to convert the digital sensor values Dsig to blood glucose values.
In alternative embodiments, a solution of a known glucose
concentration is introduced into the subcutaneous tissue
surrounding the sensor 26 by using methods and apparatus such as
described in U.S. patent application Ser. No. 09/395,530, filed on
Sep. 14, 1999, entitled "METHOD AND KIT FOR SUPPLYING A FLUID TO A
CUBCUTANEOUS PLACEMENT SITE", which is incorporated by reference
herein, or by using injection, infusion, jet pressure, introduction
through a lumen, or the like. A digital sensor value Dsig is
collected while the sensor 26 is bathed in the solution of known
glucose concentration. A mathematical formula such as a factor, an
offset, an equation, or the like, is derived to convert the digital
sensor value Dsig to the known glucose concentration. The
mathematical formula is then applied to subsequent digital sensors
values Dsig to obtain blood glucose values. In alternative
embodiments, the digital sensor values Dsig are calibrated before
filtering. In additional alternative embodiments, the digital
sensor values Dsig are calibrated after pre-filtering and before
filtering. In other alternative embodiments, the sensors are
calibrated before they are used in the body or do not require
calibration at all.
Sensor Signal Processing Systems
[0235] Before filtering and calibrating, generally the sensor
signal is processed to convert the sensor signal from a raw form
into a form acceptable for use in the filters and/or calibrator. In
preferred embodiments, as shown in FIG. 10, an analog sensor signal
Isig is digitally quantified through an A/D converter 68 resulting
in digital sensor values Dsig that are transmitted by a transmitter
70 from the telemetered characteristic monitor transmitter 30 to
another device. In particular embodiments, the analog sensor signal
Isig is an analog current value that is converted to a digital
sensor value Dsig in the form of a digital frequency measurement,
as shown in FIG. 11 (a). The general circuit includes an integrator
72, a comparator 74, a counter 76, a buffer 78, a clock 80 and the
transmitter 70. The integrator 72 generates a substantially ramped
voltage signal (A), and the instantaneous slope of the ramped
voltage signal is proportional to the magnitude of the
instantaneous analog sensor signal Isig. The comparator 74 converts
the ramped voltage signal (A) from the integrator 72 into square
wave pulses (B). Each pulse from the comparator 74 increments the
counter 76 and also resets the integrator 72. The clock 80
periodically triggers the buffer 78 to store the present value from
the counter 76 and then resets the counter 76. The values stored in
the buffer 78 are the digital sensor values Dsig. The clock 80 may
also periodically signal the transmitter 70 to send a value from
the buffer 78. In preferred embodiments, the clock period is one
minute. However, in alternative embodiments, the clock period may
be adjusted based on how often measurements are needed, sensor
signal noise, sensor sensitivity, required measurement resolution,
the type of signal to be transmitted, or the like. In alternative
embodiments, a buffer is not used.
A/D Converters
[0236] Various A/ID converter designs may be used in embodiments of
the present invention. The following examples are illustrative, and
not limiting, since other A/D converters may be used.
[0237] I to F (current to frequency (counts)), Single Capacitor,
Quick Discharge [0238] In preferred embodiments, the integrator 72
consists of a first Op-Amp 92 and a capacitor 82, shown in FIG. 12.
The integrator 72 sums the analog sensor signal Isig current by
charging the capacitor 82 until the capacitor voltage (A') achieves
a high reference voltage (VrefH). The capacitor voltage (A') is
measured at the output of the first Op-Amp 92. A second Op-Amp 94
is used as a comparator. When the capacitor voltage (A') reaches
VrefH, the comparator output (B') changes from low to high. The
high comparator output (B') closes a reset switch 84 that
discharges the capacitor 82 through a voltage source (V+). The high
comparator output (B') also triggers a reference voltage switch 88
to close, while substantially simultaneously an inverter 86 inverts
the comparator output (B'). And the inverter output (C') triggers a
reference voltage switch 90 to open. The result is that the
reference voltage of the comparator is changed from VrefH to the
low reference voltage (VrefL). [0239] When the capacitor voltage
(A') is discharged to VrefL, the comparator output (B') returns to
low, thus forming a pulse. The low comparator output (B') opens the
reset switch 84 allowing the capacitor 82 to begin charging again.
[0240] Virtually simultaneously, the low comparator output (B')
also triggers the reference voltage switch 88 to open and the
inverter output (C') triggers reference voltage switch 90 to close
resulting in changing the comparator reference voltage from VrefL
back to VrefH.
[0241] I to F, Single Reversible Capacitor [0242] In alternative
embodiments, two or more integrator switches are used to control
the polarity of one or more capacitors. A particular embodiment is
shown in FIG. 13. Generally, only one of the two
integrator-switches 110 and 112 is closed and the other integrator
switch is open. When the first integrator switch 110 is closed, the
second integrator switch 112 is open and an integrator Op-Amp 114
sums the analog sensor signal Isig current by charging a capacitor
116 until the capacitor voltage (A'') achieves a high reference
voltage (VrefH). The comparator 120 compares the integrator output
(A'') to the reference voltage VrefH. And when the capacitor
voltage (A'') reaches VrefH, the comparator output (B'') shifts
from low to high, initiating a pulse. [0243] The high comparator
output (B'') pulse causes the capacitor polarity to reverse using
the following method. The high comparator output (B'') triggers the
second integrator switch 112 to close while virtually
simultaneously the inverter 118 inverts the comparator output
(B''). And the low inverter output (C'') pulse triggers the first
integrator switch 110 to open. Once the capacitor's polarity is
reversed, the capacitor 116 discharges at a rate proportional to
the analog sensor signal Isig. The high comparator output (B'')
pulse also triggers the reference voltage of the comparator to
change form VrefH the low reference voltage (VrefL). When the
capacitor voltage (A'') is discharged to VrefL, the comparator
output (B'') returns to low. The low comparator output (B'') opens
the second integrator switch 112 and virtually simultaneously the
high inverter output (C'') closes the first integrator switch 110
allowing the capacitor 116 to begin charging again. The low
comparator output (B'') also triggers the comparator reference
voltage to change from VrefL back to VrefH. [0244] An advantage of
this embodiment is that sensor signal errors, which may be created
due to capacitor discharge time, are reduced since the magnitude of
the analog sensor signal Isig drives both the charging and the
discharging rates of the capacitor 116.
[0245] I to F, Dual Capacitor [0246] In further alternative
embodiments, more than one capacitor is used such that as one
capacitor is charging, at a rate proportional to the magnitude of
the analog sensor signal Isig, another capacitor is discharging. An
example of this embodiment is shown in FIG. 14. A series of three
switches are used for each capacitor. A first group of switches 210
is controlled by a latch voltage C''', and a second group of
switches 212 are controlled by voltage D''', which is the inverse
of C'''. Substantially, only one group of switches is closed at a
time. When the first group of switches 210 is closed, the voltage
across a first capacitor 216 increases at a rate proportional to
the analog sensor signal Isig until the integrator voltage (A''')
at the output of Op-Amp 214 achieves a reference voltage (Vref). At
the same time one of the switches shorts the circuit across a
second capacitor 222 causing it to discharge. A comparator 220
compares the integrator output (A''') to the reference voltage
Vref. And when the integrator output (A''') reaches Vref, the
comparator output (B''') generates a pulse. The comparator output
pulse increments a counter 76, and triggers the latch output
voltage C''' from a latch 221 to toggle from a low voltage to a
high voltage. The change in the latch voltage C''' causes the
second group of switches 212 to close and the first group of
switches 210 to open. One of the switches from the second group of
switches 212 shorts the circuit across the first capacitor 216
causing it to discharge. At the same time the voltage across the
second capacitor 222 increases at a rate proportional to the analog
sensor signal Isig until the integrator voltage (A''') at the
output of Op-Amp 214 achieves a reference voltage (Vref). Again,
the comparator 220 compares the integrator output (A''') to the
reference voltage Vref. And when the integrator output (A''')
reaches Vref, the comparator output (B''') generates a pulse. The
comparator output pulse increments the counter 76, and triggers the
latch output voltage C''' to toggle from a high voltage to a low
voltage, which causes the switches to return to their initial
position with the first group of switches 210 closed and the second
group of switches 212 to open. [0247] In summary, as the blood
glucose level 18 increases, the analog sensor signal Isig
increases, which causes the voltage coming out of the integrator 72
to ramp up faster to the high reference voltage VrefH, which causes
the comparator 74 to generate pulses more often, which adds counts
to the counter 76 faster. Therefore, higher blood glucose levels
generate more counts per minute. [0248] The charge storage capacity
for the capacitors used in the integrator 72, and the reference
voltages VrefH, and VrefH, are selected such that the count
resolution for counts collected in a one-minute period at a glucose
level of 200 mg/dl represents a blood glucose measurement error of
less than 1 mg/dl. In particular embodiments, VrefH is 1.1 volts
and VrefL is 0.1 volts. Higher or lower reference voltages may be
selected based on the magnitude of the analog sensor signal Isig,
the capacity of the capacitors, and the desired measurement
resolution. The source voltage V+ is set to a voltage sufficiently
high to discharge one or more capacitors quickly enough that the
discharge times do not significantly reduce the number of counts
per minute at a blood glucose level of 200 mg/dl.
[0249] Pulse Duration Output Feature [0250] In preferred
embodiments, the transmitter 70 transmits the digital sensor values
Dsig from the buffer 78 whenever triggered by the clock 80.
However, in particular embodiments, the user or another individual
may use a selector 96 to choose other outputs to be transmitted
from the transmitter 70, as shown in FIG. 11(b). In preferred
embodiments, the selector 96 is in the form of a menu displayed on
a screen that is accessed by the user or another individual by
using buttons on the surface of the telemetered characteristic
monitor transmitter 30. In other embodiments, a dial selector,
dedicated buttons, a touch screen, a signal transmitted to the
telemetered characteristic monitor transmitter 30, or the like, may
be used. Signals that may be selected to be transmitted, other than
the digital sensor values Dsig, include, but are not limited to, a
single pulse duration, digital sensor values before pre-filtering,
digital sensor values after pre-filtering but before filtering,
digital sensor values after filtering, or the like. [0251] In
particular embodiments, a pulse duration counter 98 counts clock
pulses from a pulse duration clock 100 until the pulse duration
counter 98 is reset by a rising or falling edge of a pulse from the
comparator 74, as shown in FIG. 11(b). The accumulated count at the
time that the pulse duration counter 98 is reset represents the
pulse duration for a portion of a single pulse from the comparator
74. The accumulated count from the pulse duration counter 98 is
stored in the single pulse buffer 102 when triggered by the reset
signal. When an individual selects the single pulse output, the
transmitter 70 transmits the values from the single pulse buffer
102. The pulse duration clock 100 period must be sufficiently
shorter than the period between individual pulse edges from the
comparator 74 given a high analog sensor signal Isig to have
sufficient resolution to quantify different pulse durations from
the comparator 74.
[0252] I to V (current to voltage), Voltage A/D [0253] Alternative
methods may be used to convert the analog sensor signal Isig from
an analog current signal to a digital voltage signal. The analog
sensor signal Isig is converted to an analog voltage Vsig using an
Op Amp 302 and a resistor 304, as shown in FIG. 15. And then
periodically a clock 308 triggers an A/D converter 306 to take a
sample value from the analog voltage Vsig and convert it to a
digital signal representing the magnitude of the voltage. The
output values of the A/D converter 306 are digital sensor values
Dsig. The digital sensor values Dsig are sent to a buffer 310 and
then to the transmitter 70. In particular embodiments, the resistor
304 may be adjusted to scale the Vsig to use a significant portion
of the range of the voltage A/D converter 306 depending on the
sensor sensitivity, the maximum glucose concentration to be
measured, the desired resolution from the voltage A/D converter
306, or the like. [0254] In alternative embodiments, a buffer 310
is not needed and the digital sensor values Dsig are sent from the
A/D converter directly to the transmitter 70. In other alternative
embodiments, the digital sensor values Dsig are processed,
filtered, modified, analyzed, smoothed, combined, averaged,
clipped, scaled, calibrated, or the like, before being sent to the
transmitter 70. In preferred embodiments, the clock 308 triggers a
measurement every 10 seconds. In alternative embodiments, the clock
308 runs faster or slower triggering measurements more or less
frequently depending on how quickly the blood glucose level can
change, the sensor sensitivity, how often new measurements are
needed to control the delivery system 14, or the like. [0255]
Finally, in other alternative embodiments, other sensor signals
from other types of sensors, as discussed in the section "Sensor
and Sensor Set" below, are converted to digital sensor values Dsig
if necessary before transmitting the digital sensor values Dsig to
another device.
Additional Controller Inputs
[0256] Generally, the proportional plus, integral plus, derivative
(PID) insulin response controller uses only glucose (digital sensor
values Dsig) as an input. Conversely, in a normally glucose
tolerant human body, healthy .beta.-cells benefit from additional
inputs such as neural stimulation, gut hormone stimulation, changes
in free fatty acid (FFA) and protein stimulation etc. Thus in other
alternative embodiments, the PID controller, as discussed above,
can be augmented with one or more additional inputs. In particular
alternative embodiments, the user may manually input supplemental
information such as a start of a meal, an anticipated carbohydrate
content of the meal, a start of a sleep cycle, an anticipated sleep
duration, a start of an exercise period, an anticipated exercise
duration, an exercise intensity estimation, or the like. Then, a
model predictive control feature assists the controller to use the
supplemental information to anticipate changes in glucose
concentration and modify the output commands accordingly. For
example, in a NGT individual, neural stimulation triggers the
.beta.-cells to begin to secrete insulin into the blood stream
before a meal begins, which is well before the blood glucose
concentration begins to rise. So, in alternative embodiments, the
user can tell the controller that a meal is beginning and the
controller will begin to secrete insulin in anticipation of the
meal.
[0257] In other alternative embodiments, the user or another
individual may manually override the control system or select a
different controller algorithm. For instance, in particular
alternative embodiments, an individual may select to normalize to a
basal glucose level immediately, and instead of using the
.beta.-cell emulating PID controller another controller would take
over such as a PID controller with different gains, a PD controller
for rapid glucose adjustment, or the like.
[0258] Additional alternative embodiments allow an individual to
turn off the integral component of the PID controller once the
glucose level is normalized and no meals are anticipated. In other
particular alternative embodiments, the user may select to turn off
the controller entirely, therefore disengaging the closed loop
system. Once the closed loop system is not controlling insulin
dosing, the user may program the infusion device with a basal rate,
variable basal rates, boluses, or the like, or the user may
manually enter each individual dosage when it is needed. In still
other alternative embodiments, more than one body characteristic is
measured, and the measurements are provided as inputs to a
controller. Measured body characteristics that may be used by the
controller include, but are not limited to, the blood glucose
level, blood and/or ISF pH, body temperature, the concentration of
amino acids in blood (including arginine and/or lysine, and the
like), the concentration of gastrointestinal hormones in blood or
ISF (including gastrin, secretin, cholecystokinin, and/or gastro
inhibitory peptide, and the like), the concentration of other
hormones in blood or ISF (including glucagons, growth hormone,
cortisol, progesterone and/or estrogen, and the like), blood
pressure, body motion, respiratory rate, heart rate, and other
parameters.
[0259] In NGT individuals, the glucose-induced secretion of insulin
by healthy .beta.-cells may be as much as doubled in the presence
of excess amino acids. Yet, the presence of excess amino acids
alone, without elevated blood glucose, only mildly increases
insulin secretions according to the Textbook of Medical Physiology,
Eighth Edition, written by Arthur C. Guyton, published by W. B.
Saunders Company, 1991, Ch. 78, pg. 861, section "Other Factors
That Stimulate Insulin Secretion". In particular alternative
embodiments, amino acid concentrations are estimated or measured,
and the controller's insulin response increases when amino acid
concentrations are sufficiently high.
[0260] In NGT individuals, the presence of sufficient quantities of
gastrointestinal hormones in the blood causes an anticipatory
increase in blood insulin, which suggests that .beta.-cells release
insulin before increases in blood glucose due to an individual's
anticipation of a meal. In particular alternative embodiments, the
concentration of gastrointestinal hormones is measured or
estimated, and when concentrations are high enough to indicate that
a meal is anticipated, the controller commands are adjusted to
cause insulin introduction into the body even before the blood
glucose level changes. In other alternative embodiments, the
controller uses measurements or estimates of other hormones to
modify the rate of insulin secretion.
[0261] In NGT individuals, the body's cells take up glucose during
periods of heavy exercise with significantly lower levels of
insulin. In alternative embodiments, physiologic parameters such as
body motion, blood pressure, pulse rate, respiratory rate, or the
like, are used to detect periods of heavy exercise by the body and
therefore provide inputs to the controller that decreases (or
eliminates) the amount of insulin infused into the body to
compensate for glucose concentrations.
[0262] Sensor Compensation and End-of-Life Detection [0263] In
particular embodiments, the sensor sensitivity 510 may degrade over
time, as shown in FIG. 31(b). As the sensor sensitivity 510 changes
the sensor signal accuracy degrades. If the sensor sensitivity 510
changes significantly then the sensor must be recalibrated or
replaced. A diagnostic signal may be used to evaluate whether
sensor signal accuracy has changed and/or may be used to adjust the
signal or to indicate when to recalibrate or replace the sensor. As
the sensor sensitivity 510 decreases, the measured glucose level
512 using the sensor signal underestimates the actual blood glucose
level 514, and the measurement error 516 between the measured
glucose level 512 and the actual blood glucose level 514 becomes
greater over time, as shown in FIG. 31 (a). The sensor sensitivity
510 decreases due to increases in sensor resistance Rs, as shown in
FIG. 31 (c). The sensor resistance Rs is the resistance provided by
the body between the working electrode VRK and the counter
electrode CNT, shown as the sum or R1 and R2 in the circuit diagram
of FIG. 7. The sensor resistance Rs can be obtained indirectly by
measuring the analog sensor signal Isig and the counter electrode
voltage Vcnt and then calculating the resistance,
[0263] Rs=Vcnt/Isig.
[0264] As the sensor resistance Rs increases, the analog sensor
signal Isig response to a given glucose concentration decreases. In
preferred embodiments, the decrease in the analog sensor signal
Isig may be compensated for by identifying the amount that the
sensor resistance Rs has changed since the last calibration and
then using the change in resistance in a correction algorithm 454
to adjust the analog sensor signal value. A compensation value
calculated by the correction algorithm 454 is used to increase the
sensor analog signal value. The compensation value increases over
time as the sensor resistance Rs increases. The correction
algorithm 454 includes at least one value that varies with changes
in sensor resistance Rs. In particular embodiments, a low pass
filter is applied to the sensor resistance Rs measurement to
decrease high frequency noise before evaluating how much the sensor
resistance Rs has changed since the last calibration. [0265] In
alternative embodiments, the sensor resistance Rs may be calculated
using different equations. For instance, a sensor resistance
Rs.sub.2 may be calculated as:
[0265] Rs.sub.2=(V.sub.0-Vcnt)/Isig
[0266] In particular embodiments, V.sub.0 is the same voltage as
Vset. An advantage of this approach is that it accounts for the
voltage level Vset, which can vary from sensor to sensor and/or
monitor to monitor, and/or as the analog sensor signal changes.
This removes the noise and/or offset associated with variations in
Vset, and can provide a more accurate indication of sensor
resistance. In other particular embodiments, V.sub.0 is set at
0.535 volts, which is a commonly used voltage for Vset. In further
embodiments, V.sub.0 is calculated from paired measurements of Vcnt
and Isig. Using least squares or another curve fitting method, a
mathematical equation representing the curve (typically a straight
line equation) is derived from the relationship between Vcnt and
Isig. Then, V.sub.0 is obtained by extrapolating the curve to find
the value for Vent when Isig is zero. FIGS. 38(a-h) show a
comparison between calculating the sensor resistance with V.sub.0
and without V.sub.0. The plot of the derivative of Rs.sub.2 shown
in FIG. 38(g) is cleaner and indicates the sensor failure more
clearly than the plot of the derivative of Rs shown in FIG. 38(f).
Hence sensor resistance Rs.sub.2 may be used instead of, or in
conjunction with, sensor resistance Rs described above. [0267] In
preferred embodiments, the sensor is recalibrated or replaced when
the change in the sensor resistance Rs since the last calibration
exceeds a threshold, or the rate of change of the sensor resistance
dRs/dt exceeds another threshold. In particular embodiments, the
rate of change of the sensor resistance dRs/dt may be compared to
two thresholds as shown in FIG. 32. If dRs/dt exceeds a
`replacement` threshold then a warning is provided to the user to
replace the sensor. If dRs/dt exceeds a `recalibrate` threshold
then a warning is provided to the user to recalibrate the sensor.
[0268] In an example shown in FIGS. 33(a-c), the analog sensor
signal Isig decreases dramatically at approximately 0.3 days, as
seen in FIG. 33(a). Given only the analog sensor signal Isig, the
user would believe that the decrease in the analog sensor signal
Isig is due to a decrease in blood glucose. But in reality the drop
in the analog sensor signal Isig is due to a sudden change in
sensor sensitivity. The sensor resistance Rs, shown in FIG. 33(b)
increases as the analog sensor signal Isig drops at about 0.3 days.
The derivative of the sensor resistance dRs/dt, shown in FIG.
33(c), clearly shows a spike 522 at about 0.3 days when the analog
sensor signal Isig dropped. The spike 522 in the change in sensor
resistance dRs/dt indicates a sensor anomaly rather than a
realistic drop in blood glucose. If a threshold were placed at +/-4
on the dRs/dt, the user would have received a warning to replace
the sensor at about 0.3 days. As seen in FIG. 33(a), the sensor was
not replaced until about 1.4 days. The analog sensor signal Isig
was under estimating the true glucose level from about 0.3 days
until the sensor was replaced at about 1.4 days. [0269] In
particular embodiments, the amount of time dt over which the
derivative of the sensor resistance Rs is taken is the entire time
since the last calibration. In other embodiments, the amount of
time dt over which the derivative is taken is fixed, for example
over the last hour, 90 minutes, 2 hours, or the like. [0270] In
alternative embodiments, the sensor is recalibrated or replaced
when the integral of the sensor resistance Rs over a predetermined
time window (.intg. Rs d/dt) exceeds a predetermined resistance
integral threshold. An advantage to this approach is that it tends
to filter out potential noise that could be encountered from a
signal that includes occasional spikes, sudden variations in
voltage levels, or the like. Preferably, the integral of the sensor
resistance Rs is calculated over a time window (such as 15 minutes,
or the like) based on Rs measurements obtained at set rates (such
as 1 minute, 5 minutes, or the like) during the time window. In
alternative embodiments, the time windows may be longer or shorter
and different sampling rates may be used, with the selection being
dependent on noise, response of the system, sampling rate used in
the controller, or the like. In further embodiments, the time
windows and sampling rates may change over time, such as when
approaching the end of the expected sensor life, or as the
equations indicate that the sensor is degrading, or the like.
[0271] Like above, multiple thresholds may be used. For instance,
if .intg. Rs d/dt exceeds a `replacement` threshold then a warning
is provided to the user to replace the sensor. And if .intg. Rs
d/dt exceeds a `recalibrate` threshold then a warning is provided
to the user to recalibrate the sensor. In further alternative
embodiments, the counter electrode voltage Vcnt is used to evaluate
other characteristics such as, sensor accuracy, sensor bio-fouling,
sensor function, sensor voltage operating range, sensor attachment,
or the like.
[0272] pH Controller Input [0273] In alternative embodiments, the
controller uses measurements of both the interstitial fluid (ISF)
glucose level and a local pH in the ISF surrounding the sensor to
generate commands for the infusion device. In particular
alternative embodiments, a single multi-sensor 508 located in the
subcutaneous tissue is used to measure both the glucose level and
the pH. The tip of the multi-sensor 508 that is placed into the
subcutaneous tissue with three electrodes is shown in FIG. 30. The
working electrode 502 is plated with platinum black and coated with
glucose oxidase (GOX). The reference electrode 506 is coated with
silver-silver chloride. And the counter electrode 504 is coated
with iridium oxide (Ir Ox). The analog sensor signal Isig is
generated at the working electrode 502 due to the reaction between
glucose oxidase GOX and the ISF glucose as described with the
preferred sensor embodiment. In this alternative embodiment
however, as glucose in the ISF reacts with the glucose oxidase GOX
on the working electrode and gluconic acid is generated, the local
pH in the ISF surrounding the sensor decreases, which changes the
potential of the iridium oxide on the counter electrode 504, with
respect to the reference electrode REF. So, as the pH decreases,
the voltage at the counter electrode 504 increases. Therefore, as
the glucose concentration increases, the local pH decreases, which
causes the counter electrode voltage to increase. So, the glucose
concentration may be estimated based on the counter electrode
voltage. The counter electrode voltage estimate of glucose
concentration can be compared to the estimate of glucose level from
the analog sensor signal Isig. The two estimates of the glucose
level may be combined by a weighted average or one estimate may
simply be used as a check to verify that the other sensing method
is functioning properly. For example, if the difference between the
two estimates is 10% for a period of time and then suddenly the
difference increased to 50%, a warning would be issued indicating
to the user that the sensor may need to be replaced or
recalibrated. [0274] In additional alternative embodiments, the pH
level near the sensor may be used to detect infection. By tracking
trends in the pH over time, a dramatic change in pH may be used to
identify that an infection has developed in proximity to the
sensor. A warning is used to notify the user to replace the sensor.
[0275] The pH sensor may be used in other embodiments. When insulin
is not available to assist the body to use glucose, the body shifts
to consuming fat for energy. As the body shifts from using glucose
to using almost exclusively fat for energy, concentrations of keto
acids (acetoacetic acid and .beta.-hydroxybutyric acid) increase
from about 1 mEq/liter to as high as 10 mEq/liter. In particular
alternative embodiments, the pH level is measured to detect
increases in keto acids in the body. In embodiments of the present
invention, a warning is provided to the user when the ISF pH level
is too low. [0276] A side effect of the increased of keto acid
concentrations is that sodium is drawn from the body's extra
cellular fluid to combine with the acids so that the body can
excrete the acids. This leads to increased quantities of hydrogen
ions, which greatly increases the acidosis. Severe cases lead to
rapid deep breathing, acidotic coma and even death. In other
alternative embodiments, an ion-selective electrode (ISE) is used
to detect changes in sodium concentration. A special membrane is
used to coat the ISE so that it only senses changes in sodium
concentration. In particular alternative embodiments, the ISE is a
fourth electrode added to the glucose sensor. In another
alternative embodiment, a three-electrode system is used with a
silver-silver chloride reference electrode REF, an Ir Ox counter
electrode CNT, and a sodium ion-selective (Na ISE) working
electrode WRK.
[0277] While pH measurements, end-of-life measurements, hormone
measurements, or the like, add inputs to the controller that can
significantly affect the accuracy of insulin delivery, the basic
input to the controller is generally a glucose measurement. The
glucose measurement is provided by the sensor system. And once the
controller uses the glucose measurement to generate commands, the
delivery system executes the commands. The following is a detailed
description of several apparatus embodiments for the sensor system
and the delivery system.
Sensor System
[0278] The sensor system provides the glucose measurements used by
the controller. The sensor system includes a sensor, a sensor set
to hold the sensor if needed, a telemetered characteristic monitor
transmitter, and a cable if needed to carry power and/or the sensor
signal between the sensor and the telemetered characteristic
monitor transmitter.
[0279] Sensor and Sensor Set [0280] In preferred embodiments, the
glucose sensor system 10 includes a thin film electrochemical
sensor such as the type disclosed in U.S. Pat. No. 5,391,250,
entitled "METHOD OF FABRICATING THIN FILM SENSORS"; U.S. patent
application Ser. No. 09/502,204, filed on Feb. 10, 2000, entitled
"IMPROVED ANALYTE SENSOR AND METHOD OF MAKING THE SAME"; or other
typical thin film sensors such as described in commonly assigned
U.S. Pat. Nos. 5,390,671; 5,482,473; and 5,586,553 which are
incorporated by reference herein. See also U.S. Pat. No. 5,299,571.
[0281] The glucose sensor system 10 also includes a sensor set 28
to support the sensor 26 such as described in U.S. Pat. No.
5,586,553, entitled "TRANSCUTANEOUS SENSOR INSERTION SET"
(published as PCT Application WO 96/25088); and U.S. Pat. No.
5,954,643, entitled "INSERTION SET FOR A TRANSCUTANEOUS SENSOR"
(published as PCT Application WO 98/56293); and U.S. Pat. No.
5,951,521, entitled "A SUBCUTANEOUS IMPLANTABLE SENSOR SET HAVING
THE CAPABILITY TO REMOVE OR DELIVER FLUIDS TO AN INSERTION SITE",
which are incorporated by reference herein. [0282] In preferred
embodiments, the sensor 26 is inserted through the user's skin 46
using an insertion needle 58, which is removed and disposed of once
the sensor is positioned in the subcutaneous tissue 44. The
insertion needle 58 has a sharpened tip 59 and an open slot 60 to
hold the sensor during insertion into the skin 46, as shown in
FIGS. 3(c) and (d) and FIG. 4. Further description of the needle 58
and the sensor set 28 are found in U.S. Pat. No. 5,586,553,
entitled "TRANSCUTANEOUS SENSOR INSERTION SET" (published as PCT
Application WO 96/25088); and U.S. Pat. No. 5,954,643, entitled
"INSERTION SET FOR A TRANSCUTANEOUS SENSOR" (published as PCT
Application WO 98/5629), which are incorporated by reference
herein. [0283] In preferred embodiments, the sensor 26 has three
electrodes 42 that are exposed to the interstitial fluid (ISF) in
the subcutaneous tissue 44 as shown in FIGS. 3 (d) and 4. A working
electrode WRK, a reference electrode REF and a counter electrode
CNT are used to form a circuit, as shown in FIG. 7. When an
appropriate voltage is supplied across the working electrode WRK
and the reference electrode REF, the ISF provides impedance (R1 and
R2) between the electrodes 42. And an analog current signal Isig
flows from the working electrode WRK through the body (R1 and R2,
which sum to Rs) and to the counter electrode CNT. Preferably, the
working electrode WRK is plated with platinum black and coated with
glucose oxidase (GOX), the reference electrode REF is coated with
silver-silver chloride, and the counter electrode is plated with
platinum black. The voltage at the working electrode WRK is
generally held to ground, and the voltage at the reference
electrode REF is substantially held at a set voltage Vset. Vset is
between 300 and 700 mV, and preferably to about 535 mV. [0284] The
most prominent reaction stimulated by the voltage difference
between the electrodes is the reduction of glucose as it first
reacts with GOX to generate gluconic acid and hydrogen peroxide
(H.sub.2O.sub.2). Then the H.sub.2O.sub.2 is reduced to water
(H.sub.2O) and (O') at the surface of the working electrode WRK.
The O' draws a positive charge from the sensor electrical
components, thus repelling an electron and causing an electrical
current flow. This results in the analog current signal Isig being
proportional to the concentration of glucose in the ISF that is in
contact with the sensor electrodes 42. The analog current signal
Isig flows from the working electrode WRK, to the counter electrode
CNT, typically through a filter and back to the low rail of an
op-amp 66. An input to the op-amp 66 is the set voltage Vset. The
output of the op-amp 66 adjusts the counter voltage Vcnt at the
counter electrode CNT as Isig changes with glucose concentration.
The voltage at the working electrode WRK is generally held to
ground, the voltage at the reference electrode REF is generally
equal to Vset, and the voltage Vcnt at the counter electrode CNT
varies as needed. [0285] In alternative embodiments, more than one
sensor is used to measure blood glucose. In particular embodiments,
redundant sensors are used. The user is notified when a sensor
fails by the telemetered characteristic monitor transmitter
electronics. An indicator may also inform the user of which sensors
are still functioning and/or the number of sensors still
functioning. In other particular embodiments, sensor signals are
combined through averaging or other means. If the difference
between the sensor signals exceeds a threshold then the user is
warned to recalibrate or replace at least one sensor. In other
alternative embodiments, more than one glucose sensor is used, and
the glucose sensors are not of the same design. For example, an
internal glucose sensor and an external glucose sensor may be used
to measure blood glucose at the same time. [0286] In alternative
embodiments, other continuous blood glucose sensors and sensor sets
may be used. In particular alternative embodiments, the sensor
system is a micro needle analyte sampling device such as described
in U.S. patent application Ser. No. 09/460,121, filed on Dec. 13,
1999, entitled "INSERTION SET WITH MICROPIERCING MEMBERS AND
METHODS OF USING THE SAME", incorporated by reference herein, or an
internal glucose sensor as described in U.S. Pat. Nos. 5,497,772;
5,660,163; 5,791,344; and 5,569,186, and/or a glucose sensor that
uses florescence such as described in U.S. Pat. No. 6,011,984 all
of which are incorporated by reference herein. In other alternative
embodiments, the sensor system uses other sensing technologies such
as described in Patent Cooperation Treaty publication No. WO
99/29230, light beams, conductivity, jet sampling, micro dialysis,
micro-poration, ultra sonic sampling, reverse iontophoresis, or the
like. In still other alternative embodiments, only the working
electrode WRK is located in the subcutaneous tissue and in contact
with the ISF, and the counter CNT and reference REF electrodes are
located external to the body and in contact with the skin. In
particular embodiments, the counter electrode CNT and the reference
electrode REF are located on the surface of a monitor housing 518
and are held to the skin as part of the telemetered characteristic
monitor, as shown in FIG. 34 (a). In other particular embodiments,
the counter electrode CNT and the reference electrode REF are held
to the skin using other devices such as running a wire to the
electrodes and taping the electrodes to the skin, incorporating the
electrodes on the underside of a watch touching the skin, or the
like. In more alternative embodiments, more than one working
electrode WRK is placed into the subcutaneous tissue for
redundancy. In additional alternative embodiments, a counter
electrode is not used, a reference electrode REF is located outside
of the body in contact with the skin, and one or more working
electrodes WRK are located in the ISF. An example of this
embodiment implemented by locating the reference electrode REF on a
monitor housing 520 is shown in FIG. 34 (b). In other embodiments,
ISF is harvested from the body of an individual and flowed over an
external sensor that is not implanted in the body.
[0287] Sensor Cable [0288] In preferred embodiments, the sensor
cable 32 is of the type described in U.S. Patent Application Ser.
No. 60/121,656, filed on Feb. 25, 1999, entitled "TEST PLUG AND
CABLE FOR A GLUCOSE MONITOR", which is incorporated by reference
herein. In other embodiments, other cables may be used such as
shielded, low noise cables for carrying nA currents, fiber optic
cables, or the like. In alternative embodiments, a short cable may
be used or the sensor may be directly connected to a device without
the need of a cable.
[0289] Telemetered Characteristic Monitor Transmitter [0290] In
preferred embodiments, the telemetered characteristic monitor
transmitter 30 is of the type described in U.S. patent application
Ser. No. 09/465,715, filed on Dec. 17, 1999, entitled "TELEMETERED
CHARACTERISTIC MONITOR SYSTEM AND METHOD OF USING THE SAME"
(published as PCT Application WO 00/19887 and entitled.
"TELEMETERED CHARACTERISTIC MONITOR SYSTEM"), which is incorporated
by reference herein, and is connected to the sensor set 28 as shown
in FIGS. 3 (a) and (b). [0291] In alternative embodiments, the
sensor cable 32 is connected directly to the infusion device
housing, as shown in FIG. 8 (a), which eliminates the need for a
telemetered characteristic monitor transmitter 30. The infusion
device contains a power supply and electrical components to operate
the sensor 26 and store sensor signal values. [0292] In other
alternative embodiments, the telemetered characteristic monitor
transmitter includes a receiver to receive updates or requests for
additional sensor data or to receive a confirmation (a hand-shake
signal) indicating that information has been received correctly.
Specifically, if the telemetered characteristic monitor transmitter
does not receive a confirmation signal from the infusion device,
then it re-sends the information. In particular alternative
embodiments, the infusion device anticipates receiving blood
glucose values or other information on a periodic basis. If the
expected information is not supplied when required, the infusion
device sends a `wake-up` signal to the telemetered characteristic
monitor transmitter to cause it to re-send the information.
Insulin Delivery System
[0293] Infusion device [0294] Once a sensor signal 16 is received
and processed through the controller 12, commands 22 are generated
to operate the infusion device 34. In preferred embodiments,
semi-automated medication infusion devices of the external type are
used, as generally described in U.S. Pat. Nos. 4,562,751;
4,678,408; 4,685,903; and U.S. patent application Ser. No.
09/334,858, filed on Jun. 17, 1999, entitled "EXTERNAL INFUSION
DEVICE WITH REMOTE PROGRAMMING, BOLUS ESTIMATOR AND/OR VIBRATION
CAPABILITIES" (published as PCT application WO 00/10628), which are
herein incorporated by reference. In alternative embodiments,
automated implantable medication infusion devices, as generally
described in U.S. Pat. Nos. 4,373,527 and 4,573,994, are used,
which are incorporated by reference herein.
[0295] Insulin [0296] In preferred embodiments, the infusion device
reservoir 50 contains Humalog.RTM. lispro insulin to be infused
into the body 20. Alternatively, other forms of insulin may be used
such as Humalin.RTM., human insulin, bovine insulin, porcine
insulin, analogs, or other insulins such as insulin types described
in U.S. Pat. No. 5,807,315, entitled "METHOD AND COMPOSITIONS FOR
THE DELIVERY OF MONOMERIC PROTEINS", and U.S. Patent Application
Ser. No. 60/177,897, filed on Jan. 24, 2000, entitled "MIXED BUFFER
SYSTEM FOR STABILIZING POLYPEPTIDE FORUMLATIONS", which are
incorporated by reference herein, or the like. In further
alternative embodiments, other components are added to the insulin
such as polypeptides described in U.S. patent application Ser. No.
09/334,676, filed on Jun. 25, 1999, entitled "MULTIPLE AGENT
DIABETES THERAPY", small molecule insulin mimetic materials such as
described in U.S. patent application Ser. No. 09/566,877, filed on
May 8, 2000, entitled "DEVICE AND METHOD FOR INFUSION OF SMALL
MOLECULE INSULIN MIMETIC MATERIALS", both of which are incorporated
by reference herein, or the like.
[0297] Infusion Tube [0298] In preferred embodiments, an infusion
tube 36 is used to carry the insulin 24 from the infusion device 34
to the infusion set 38. In alternative embodiments, the infusion
tube carries the insulin 24 from infusion device 34 directly into
the body 20. In further alternative embodiments, no infusion tube
is needed, for example if the infusion device is attached directly
to the skin and the insulin 24 flows from the infusion device,
through a cannula or needle directly into the body. In other
alternative embodiments, the infusion device is internal to the
body and an infusion tube may or may not be used to carry insulin
away from the infusion device location.
[0299] Infusion Set [0300] In preferred embodiments, the infusion
set 38 is of the type described in U.S. Pat. No. 4,755,173,
entitled "SOFT CANNULA SUBCUTANEOUS INJECTION SET", which is
incorporated by reference herein. In alternative embodiments, other
infusion sets, such as the Rapid set from Desetronic, the
Silhouette from MiniMed, or the like, may be used. In further
alternative embodiments, no infusion set is required, for example
if the infusion device is an internal infusion device or if the
infusion device is attached directly to the skin.
Configurations With Supplemental Devices
[0300] [0301] In further alternative embodiments, the pre-filter,
filters, calibrator and/or controller 12 are located in a
supplemental device that is in communication with both the
telemetered characteristic monitor transmitter 30 and the infusion
device 34. Examples of supplemental devices include, a hand held
personal digital assistant such as described in U.S. patent
application Ser. No. 09/487,423, filed on Jan. 20, 2000, entitled
"HANDHELD PERSONAL DATA ASSISTANT (PDA) WITH A MEDICAL DEVICE AND
METHOD OF USING THE SAME", which is incorporated by reference
herein, a computer, a module that may be attached to the
telemetered characteristic monitor transmitter 30, a module that
may be attached to the infusion device 34, a RF programmer such as
described in U.S. patent application Ser. No. 09/334,858, filed on
Jun. 17, 1999, entitled EXTERNAL INFUSION DEVICE WITH REMOTE
PROGRAMMING, BOLUS ESTIMATOR AND/OR VIBRATION CAPABILITIES
(published as PCT application WO 00/10628), which is incorporated
by reference herein, or the like. In particular embodiments, the
supplemental device includes a post-calibration filter, a display,
a recorder, and/or a blood glucose meter. In further alternative
embodiments, the supplemental device includes a method for a user
to add or modify information to be communicated to the infusion
device 34 and/or the telemetered characteristic monitor transmitter
30 such as buttons, a keyboard, a touch screen, and the like.
[0302] In particular alternative embodiments, the supplemental
device is a computer in combination with an analyte monitor and a
RF programmer. The analyte monitor receives RF signals from the
telemetered characteristic monitor transmitter 30, stores the
signals and down loads them to a computer when needed. The RF
programmer sends control signals to the infusion device 34 to
reprogram the rate of insulin infusion. Both the analyte monitor
and the RF programmer are placed into separate communication
stations. The communication stations include IR transmitters and IR
receivers to communicate with the analyte monitor and the RF
programmer. The sensor signal values are transmitted via the
telemetered characteristic monitor transmitter 30 to the analyte
monitor located in one of the communication stations. Then the
sensor signal values are communicated through the IR receiver in a
first communication station and to the computer. The computer
processes the sensor signal values through one or more filters,
calibrators, and controllers to generate commands 22. The commands
are sent to a second communication station and sent to an RF
programmer by the IR transmitter in the communication station.
Finally the RE programmer transmits the commands 22 to the infusion
device 34. The communication station, analyte monitor and infusion
device 34 may be of the type described in U.S. patent application
Ser. No. 09/409,014, filed on Sep. 29, 1999 entitled COMMUNICATION
STATION FOR INTERFACING WITH AN INFUSION PUMP, ANALYTE MONITOR,
ANALYTE METER OR THE LIKE (published as a PCT application WO
00/18449), which is incorporated by reference herein.
Alternatively, the RF programmer may be omitted and the infusion
device may be placed in a communication station, or the infusion
device may receive the commands without the use of an RF programmer
and/or a communication station.
[0303] While the description above refers to particular embodiments
of the present invention, it will be understood that many
modifications may be made without departing from the spirit
thereof. The accompanying claims are intended to cover such
modifications as would fall within the true scope and spirit of the
present invention.
[0304] The presently disclosed embodiments are therefore to be
considered in all respects as illustrative and not restrictive, the
scope of the invention being indicated by the appended claims,
rather than the foregoing description, and all changes which come
within the meaning and range of equivalency of the claims are
therefore intended to be embraced therein.
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