System and Method Considering the Effect of Physical Activity on the Glucoregulatory System

• US 20130130215A1
• Filed: 01/09/2013
• Published: 05/23/2013
• Est. Priority Date: 07/23/2010
• Status: Active Grant

• Current Assignee: Roche Diagnostics Operations Incorporated (Roche Holding AG)
• Original Assignee: Roche Diagnostics Operations Incorporated (Roche Holding AG)
• Inventors: Duke, David L., Soni, Abhishek S., Bock, Alain
• Granted Patent: US 11,004,555 B2
• Time in Patent Office: Days
• US Class Current: 434/247
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 23/28 for medicine
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A system and method for considering the effects of aerobic exercise on blood glucose levels for individuals is described. In at least one embodiment of the system of the present disclosure, the system comprises a computing device for generating a prediction of future blood glucose levels for the individual at least partly based on an exercise model, wherein the exercise model is based on parameters that are independent of intensity of the aerobic exercise, and a means for taking an action at least based on the prediction from the exercise model.

Claims

1. A system for considering the effect of aerobic exercise on blood glucose levels for an individual, comprising:

a computing device for generating a prediction of future blood glucose levels for the individual at least partly based on an exercise model, wherein the exercise model is based on parameters that are independent of intensity of the aerobic exercise; and

means for taking an action at least based on the prediction from the exercise model.

2. The system according to claim 1, wherein the means for taking the action includes an automated pancreas.

3. The system according to claim 1, further comprising an exercise monitoring device in communication with the computing device., wherein the exercise monitoring device is capable of detecting the occurrence of an exercise and sending an input signal to the computing device for whether the aerobic exercise is being or will be performed by the individual or not

4. The system according to claim 1, further comprising an interface device in communication with the computing device, wherein the interface device is operable to alert the individual of a dangerous blood glucose level condition via the interface device.

5. A method of considering the effect of aerobic exercise on blood glucose levels for an individual, comprising:

generating with a computing device a prediction of future blood glucose levels for the individual at least partly based on an exercise model, wherein the exercise model is based on parameters that are independent of intensity of the aerobic exercise; and

taking an action with the computing device at least based on the prediction from the exercise model.

6. The method according to claim 5, wherein the parameters include a non-constant and measured parameter, the non-constant and measured parameter is an Exercise Input indicating whether an exercise is performed or not.

7. The method according claim 5, wherein the exercise model incorporates an exercise sensitivity value that represents change in the blood glucose level over time during exercise without considering intensity of the exercise.

8. The method according to claim 5, wherein the exercise model accounts for a change in the blood glucose level based on an amplitude of the change in the blood glucose level during exercise for the individual and how quickly the exercise effect appears and disappears in the individual along with an exercise input that considers whether or not an exercise is being performed without considering the intensity of the exercise.

9. The method according to claim 5, wherein the exercise model is based on the following equation:

10. The method according to claim 5, wherein the exercise model is based on the following equation:

where;

11. The method according to 5, further comprising:

to receiving an exercise input with the computing device that the aerobic exercise is being performed by the individual.

12. The method according to claim 11, wherein the exercise input is a binary type input that signifies whether or not the aerobic exercise is occurring.

13. The method according to claim 11, wherein said receiving the exercise input includes receiving a manual input from the individual.

14. The method according to claim 11, wherein said receiving the exercise input includes receiving an automatic input from an exercise monitoring device.

15. The method according to claim 5, wherein said taking the action with the computing device includes alerting the individual of a dangerous blood glucose level condition.

16. The method according to claim 5, wherein said taking the action with the computing device includes providing an output that educates the individual about the effect of aerobic exercise on blood glucose levels for the individual.

17. The method according to claim 5, wherein said taking the action with the computing device includes changing an insulin injection profile for an automated pancreas.

18. The method according to claim 5, wherein said taking the action with the computing device includes performing a bolus calculation.

19. The method according to claims 5, wherein the aerobic exercise occurs in a range from 65% to 75% of a maximum heart rate for the individual.

20. The method according to claim 5, further comprising:

conducting an exercise study to determine the parameters for the exercise model.

21. The method according to claim 20, wherein only blood glucose concentrations during the exercise study are used to determine the parameters for the exercise model.

22. The method according to claim 5, wherein the exercise has a duration of no more than 90 minutes.

23. The method according to claims 5, wherein the exercise has a duration of no more than 45 minutes.

24. The method according to claim 5, wherein the exercise has a duration of no more than 30 minutes,

25. The method according to claim 5, wherein the computing device includes a glucose meter.