AUTOMATIC INSULIN PUMPS USING RECURSIVE MULTIVARIABLE MODELS AND ADAPTIVE CONTROL ALGORITHMS

• US 20110106011A1
• Filed: 10/05/2010
• Published: 05/05/2011
• Est. Priority Date: 10/06/2009
• Status: Active Grant

• Current Assignee: Illinois Institute of Technology
• Original Assignee: Illinois Institute of Technology
• Inventors: Oruklu, Meriyan, Cinar, Ali
• Granted Patent: US 8,690,820 B2
• Time in Patent Office: Days
• US Class Current: 604/151
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A method and device for monitoring or treating patient glucose levels. The device includes a glucose sensor for measuring a glucose level of a patient, a physiological status monitoring system for measuring at least one physical or metabolic variable of the patient, and an automatic controller in communication with the glucose sensor and the physiological status monitoring system. The controller includes a prediction module for automatically predicting a future glucose level using data measured by the glucose sensor and the physiological sensor.

Claims

1. A device for monitoring or treating patient glucose levels, the device comprising:

a glucose sensor for measuring a glucose level of a patient;

a physiological status monitoring system for measuring at least one physical or metabolic variable of the patient;

an automatic controller in communication with the glucose sensor and the physiological status monitoring system, the controller including a prediction module for automatically predicting a future glucose level using data measured by the glucose sensor and the physiological sensor.

2. The device according to claim 1, wherein the glucose sensor comprises a continuous glucose monitor and the prediction module comprises an algorithm for predicting future glucose concentration values at or between 5 to 30 minutes into the future.

3. The device according to claim 1, wherein the physiological status monitoring system comprises an armband monitoring system worn by the patient.

4. The device according to claim 1, wherein the physiological status monitoring system comprises at least one sensor that measures movement, skin temperature, dissipated heat from the body, galvanic skin response, or combinations thereof, and derives at least one variable selected from sleep, total energy expenditure, stress, physical activity, or combinations thereof.

5. The device according to claim 1, further comprising a recordable medium for storing the data measured by the glucose sensor and the physiological sensor, wherein the prediction module predicts the future blood glucose level using at least a portion of the stored measured information by the glucose sensor and the physiological sensor

6. The device according to claim 1, wherein the controller comprises a closed-loop system.

7. The device according to claim 1, further comprising an alarm mechanism for alerting the patient of an unsafe current or future glucose level.

8. The device according to claim 1, further comprising an insulin pump in combination with the controller, wherein the controller controls an insulin infusion as a function of the predicted future glucose level.

9. The device according to claim 1, wherein the prediction module comprises a recursive model for predicting the future glucose level using data measured by the glucose sensor and the physiological sensor.

10. A method of predicting glucose levels in a patient, the method comprising:

periodically measuring a glucose level in the patient to obtain actual glucose measurements;

monitoring for physiological signals of the patient to obtain measured physiological signals or derived physiological variables;

modeling a glucose concentration of the patient as a function of the actual glucose measurements and the physiological signals; and

estimating future glucose levels for the patient from the model of the glucose concentration of the patient.

11. The method according to claim 10, further comprising periodically measuring a glucose level in the patient with a continuous glucose monitor.

12. The method according to claim 10, further comprising monitoring for physiological signals of the patient using at least one sensor that measures movement, skin temperature, dissipated heat from the body, galvanic skin response, or combinations thereof, and further comprising deriving at least one variable selected from sleep, total energy expenditure, stress, physical activity, or combinations thereof.

13. The method according to claim 10, further comprising activating an alarm when an estimated future glucose level is below a predetermined glucose level.

14. The method according to claim 10, further comprising:

determining changes in glucose concentration model parameters; and

modifying the glucose concentration model in view of the new parameters.

15. The method according to claim 10, wherein the method is a closed-loop insulin therapy.

16. The method according to claim 10, further comprising automatically recursively updating the model of the glucose concentration with each of the actual glucose measurements.

17. The method according to claim 10, wherein the modeling comprises multivariate recursive time series modeling.

18. The method according to claim 10, further comprising determining a difference between an estimated future glucose level for a timeframe and an actual glucose measurement for the timeframe, and modifying the model of the glucose concentration as a function of the difference.

19. The method according to claim 10, further comprising compensating for time delays between blood glucose levels and subcutaneous glucose levels.

20. The method according to claim 10, further comprising storing the actual glucose measurements and corresponding physiological data on a recordable medium in combination with a data processor, and automatically modeling the glucose concentration of the patient with the data processor as a function of a plurality of the stored actual glucose measurements and the corresponding physiological data sampled during a predetermined timeframe prior to the modeling or estimating.

21. The method according to claim 10, further comprising automatically infusing insulin into the patient by modifying an insulin flow rate by an insulin pump.

22. The method according to claim 21, further comprising compensating for time delays between subcutaneous insulin injection and insulin levels in blood.