# US 11,298,460 B2 · Automated system for controlling the blood glucose level of a patient

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 11,298,460 B2
- Document ID: US11298460B2
- Status: Granted
- Kind: B2
- Application number: 16/334,825
- Filed: 2017-09-19
- Published: 2019-10-03
- Granted: 2022-04-12
- Earliest claimed: 2016-09-21
- Assignees: Commissariat A L'energie Atomique Et Aux Energies Alternatives
- Applicants: Commissariat à l'Énergie Atomique et aux Énergies Alternatives
- Inventors: Pierre Jallon
- Web page: https://patentgrep.com/patent/US11298460B2

## CPC

- A61M 5/1723: {using feedback of body parameters, e.g. blood sugar or pressure}
- A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement}
- A61B 5/1495: Calibrating or testing of in-vivo probes
- A61B 5/4839: {combined with drug delivery}
- A61M 5/142: Pressure infusion, e.g. using pumps
- A61M 5/14276: {specially adapted for implantation}
- G16H 20/17: delivered via infusion or injection
- G16H 40/63: for local operation
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- A61B 5/14503: {invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors (A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence)}
- A61B 2560/0223: of calibration, e.g. protocols for calibrating sensors
- A61M 2005/14208: {with a programmable infusion control system, characterised by the infusion program}
- A61M 2005/1726: {the body parameters being measured at, or proximate to, the infusion site}
- A61M 2205/52: with memories providing a history of measured variating parameters of apparatus or patient
- A61M 2230/005: Parameter used as control input for the apparatus
- A61M 2230/201: Glucose concentration
- A61M: DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY (introducing media into or onto the bodies of animals A61D7/00; means for inserting tampons A61F13/26; devices for administering food or medicines orally A61J; containers for collecting, storing or administering blood or medical fluids A61J1/05); DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY (surgery A61B; chemical aspects of surgical articles A61L); DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR {(Electrotherapy, e.g. producing anaesthesia by the use of alternating or intermittent currents A61N1/36021)}
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

An automated system of regulation of a patient's blood sugar, including: a blood sugar sensor; an insulin injection device; and a processing and control unit capable of predicting the future evolution of the patient's blood sugar from a physiological model and of controlling the insulin injection device by taking the prediction into account, wherein: the physiological model includes a differential equation system describing the time variation of a plurality of state variables; and the processing and control unit is capable of implementing a step of automatic calibration of the physiological model including a step of estimation of initial values of the state variables by minimization of a quantity representative of the error, during a past observation period, between the blood sugar estimated based on the physiological model and the blood sugar measured by the sensor.

## Claims

### Claim 1

An automated system of regulation of a patient's blood sugar, comprising:
a blood sugar sensor;
an insulin injection device; and
a processing and control unit capable of predicting a future evolution of the patient's blood sugar from a physiological model and of controlling the insulin injection device by taking the prediction into account,
wherein:
the physiological model comprises a differential equation system describing a time variation of a plurality of state variables; and
the processing and control unit is capable of implementing a step of automatic calibration of the physiological model comprising:
a) a step of estimation of parameters of the differential equation system by minimization of a quantity representative of an error, during a past observation period, between the patient's blood sugar as estimated based on the physiological model and the patient's blood sugar as measured by the sensor; and
b) a step of estimation of initial values of the state variables by minimization of said quantity representative of an error, during a past observation period, between the patient's blood sugar as estimated based on the physiological model and the patient's blood sugar as measured by the sensor;
wherein said quantity is representative of the area between a first curve ĝ representative of the time variation of the patient's blood sugar as estimated based on the model over the observation period, and a second curve g representative of the time variation of the patient's blood sugar as measured by the sensor over the observation period;
and wherein, at step a), the parameters are determined using an algorithm for solving problems of parameter optimization by minimization of a cost function, and, at step b), the initial values of the state variables are determined using an algorithm for solving problems of parameter optimization by minimization of a cost function.

### Claim 2 (depends on 1)

The system of claim 1, wherein said quantity is defined as follows:
m
=
1
Δ
⁢
T
⁢
∑
t
=
t
0
t
0
+
Δ
⁢
T
⁢

g
⁡
(
t
)
-
g
^
⁡
(
t
)

2
where t is a discretized time variable, t0 is the time of beginning of the observation phase, and t0+ΔT is the end time of the observation phase.

### Claim 3 (depends on 1)

The system of claim 1, wherein steps a) and b) are performed simultaneously in a single search, considering the parameters of the differential equation system and the initial values of the state variables as random variables.

### Claim 4 (depends on 1)

The system of claim 1, wherein the step of automatic calibration comprises a plurality of successive iterations of steps a) and b), and wherein, at each iteration of step a), the initial values of the state variables are initialized to a set of fixed values, and, at each iteration of step b), the initial parameters of the differential equation system are initialized to a set of fixed values.

### Claim 5 (depends on 4)

The system of claim 4, wherein, at the first iteration of step a), the set of fixed values of the initial values of the state variables is determined analytically, considering that all the derivatives of the differential equation system are zero.

### Claim 6 (depends on 1)

The system of claim 1, wherein the processing and control unit is configured for stimulating the evolution of the patient's blood sugar based on the physiological model, and based on a history of insulin injected to the patient by the insulin injection device and on a history of the glucose ingested by the patient.

### Claim 7 (depends on 1)

The system of claim 1, wherein the physiological model is Hovorka's model.

### Claim 8

An automated method of regulating a patient's blood sugar, comprising:
a step of calculating, by means of a processing and control unit, a prediction of future evolution of the patient's blood sugar based on a physiological model comprising a differential equation system describing the time variation of a plurality of state variables;
a step of controlling an insulin injection device taking this prediction into account; and
a step of automatic calibration of the physiological model comprising:
a) a step of estimation of parameters of the differential equation system by minimization of a quantity representative of an error, during a past observation period, between the patient's blood sugar as estimated based on the physiological model and the patient's blood sugar as measured by the sensor; and
b) a step of estimation of initial values of the state variables by minimization of said quantity representative of an error, during a past observation period, between the patient's blood sugar as estimated based on the physiological model and the patient's blood sugar as measured by the sensor;
wherein said quantity is representative of the area between a first curve ĝ representative of the time variation of the patient's blood sugar as estimated based on the model over the observation period, and a second curve g representative of the time variation of the patient's blood sugar as measured by the sensor over the observation period,
and wherein, at step a), the parameters are determined using an algorithm for solving problems of parameter optimization b minimization of a cost function, and, at step b), the initial values of the state variables are determined using an algorithm for solving problems of parameter optimization by minimization of a cost function.

### Claim 9 (depends on 8)

The method of claim 8, wherein steps a) and b) are preformed simultaneously in a single search, considering the parameters of the differential equation system and the initial values of the state variables as random variables.

### Claim 10 (depends on 8)

The method of claim 8, wherein the calibration step comprises a plurality of successive iterations of steps a) and b), and wherein, at each iteration of step a), the initial values of the state variables are initialized to a set of fixed values, and, at each iteration of step b), the initial parameters of the differential equation system are initialized to a set of fixed values.

### Claim 11 (depends on 10)

The method of claim 10, wherein, at the first iteration of steps a), the set of fixed values of the initial values of the state variables is determined analytically, considering that all the derivatives of the differential equation system are zero.