Automatic insulin pumps using recursive multivariable models and adaptive control algorithms

• US 8,690,820 B2
• Filed: 10/05/2010
• Issued: 04/08/2014
• Est. Priority Date: 10/06/2009
• Status: Active Grant

• Current Assignee: Illinois Institute of Technology
• Original Assignee: Illinois Institute of Technology
• Inventors: Cinar, Ali, Oruklu, Meriyan
• Primary Examiner(s): VU, QUYNH-NHU HOANG
• Application Number:
  US12/898,347
• Publication Number:
  US 20110106011A1
• Time in Patent Office: 1,281 Days
• Field of Search: 604 65- 66, 604/67, 600315-316, 600319-320, 600346-347, 600/350, 600/365, 702/19
• US Class Current: 604/66
• 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 method of predicting glucose levels in a patient, the method comprising:

automatically measuring a glucose level in the patient to obtain an actual glucose measurement;

automatically monitoring a physiological variable of the patient to obtain a measured physiological variable;

automatically modeling a glucose concentration of the patient as a function of the actual glucose measurement and the measured physiological variable;

automatically estimating a future glucose level for the patient from the model of the glucose concentration of the patient; and

automatically updating the model of the glucose concentration as a function of further glucose measurements and further physiological variables.

2. The method according to claim 1, further comprising automatically recursively updating the model of the glucose concentration with each of the further glucose measurements.

3. The method of claim 1, wherein the updating occurs upon determining a difference between the estimated future glucose level for a timeframe and a further actual glucose level at the timeframe.

4. The method of claim 1, wherein the updating of the model comprises modifying model parameters upon comparing the estimated future glucose for a timeframe to the further physiological variables measured during the timeframe.

5. The method according to claim 1, further comprising periodically measuring a glucose level in the patient with a continuous glucose monitor worn by the patient.

6. The method according to claim 1, further comprising monitoring for physiological variables of the patient using at least one sensor worn by the patient that measures movement, skin temperature, dissipated heat from the body, galvanic skin response, or combinations thereof, and further comprising deriving at least one physiological variable selected from sleep, total energy expenditure, stress, physical activity, or combinations thereof.

7. The method according to claim 1, further comprising activating an alarm when an estimated future glucose level is below a predetermined glucose level.

8. The method according to claim 1, further comprising:

determining changes in glucose concentration model parameters; and

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

9. The method according to claim 1, wherein the method is a closed-loop insulin therapy without manual inputs by the patient.

10. The method according to claim 1, 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.

11. The method according to claim 1, further comprising measuring the glucose level with a subcutaneous continuous glucose monitor and compensating for time delays between blood glucose levels and subcutaneous glucose levels.

12. The method according to claim 1, further comprising storing the actual glucose measurements and corresponding physiological data on a recordable medium in combination with a data processor, each worn by the patient, 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.

13. The method according to claim 1, further comprising automatically infusing insulin into the patient by modifying an insulin flow rate by an insulin pump.

14. The method according to claim 13, further comprising compensating for time delays between subcutaneous insulin injection and insulin levels in blood.

15. The method according to claim 1, further comprising:

providing a device including an automatic controller in wired or wireless communication with each of a glucose sensor, a physiological sensor, and an insulin pump, each worn by the patient;

the automatic controller automatically collecting information from the glucose sensor to obtain actual glucose measurements;

the automatic controller automatically collecting information from the physiological sensor to obtain measured physiological variables;

the automatic controller automatically recursively modeling the glucose concentration of the patient as a function of the actual glucose measurements and the measured physiological variables;

the automatic controller estimating future glucose levels for the patient from the recursive model of the glucose concentration of the patient;

the automatic controller automatically activating the insulin pump to inject an amount of insulin determined in response to the estimated future glucose level;

obtaining new sensor measurements after injecting the amount of insulin; and

the automatic controller updating the recursive model of the glucose concentration as a function of new sensor measurements and the amount of insulin.

16. The method according to claim 15, 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.

17. The method according to claim 15, wherein the physiological sensor comprises an armband monitoring system worn by the patient.

18. The method according to claim 15, wherein the physiological sensor measures at least one of 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.

19. The method according to claim 15, the device further comprising a recordable medium for storing data measured by the glucose sensor and the physiological sensor, and a prediction module that predicts the future blood glucose level using at least a portion of the stored measured information by the glucose sensor and the physiological sensor.

20. The method according to claim 15, wherein the controller comprises a closed-loop system without manual inputs by the patient.

21. The method according to claim 15, the device further comprising an alarm mechanism for alerting the patient of an unsafe current or future glucose level.