Computer-based diabetes management

• US 9,833,191 B2
• Filed: 01/10/2013
• Issued: 12/05/2017
• Est. Priority Date: 11/07/2012
• Status: Active Grant

• Current Assignee: Bigfoot Biomedical, Inc.
• Original Assignee: Bigfoot Biomedical, Inc.
• Inventors: Mazlish, Bryan
• Primary Examiner(s): Cheng, Jacqueline
• Assistant Examiner(s): PORTILLO, JAIRO H
• Application Number:
  US13/738,466
• Publication Number:
  US 20140128705A1
• Time in Patent Office: 1,790 Days
• Field of Search: None
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/4848 Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A computer-based method includes receiving, from a computer-based user interface, user-specified information about one or more events influential on the user'"'"'s blood glucose level, generating, with a computer-based processor, a plurality of estimated trajectories of the user'"'"'s blood glucose level as influenced by the one or more events, receiving a set of data that represents actual blood glucose measurements for the user, and identifying, with the computer-based processor, which of the estimated trajectories represents a best fit to the set of data that represents the actual blood glucose measurements for the user. At least some of the actual blood glucose measurements occurred later in time than a start time of the one or more events influential on the user'"'"'s blood glucose level. A computer-based system is provided for implementing the method.

Claims

1. A method for managing diabetes, the method comprising:

receiving, from a computer-based user interface, user-specified information about one or more events influential on a blood glucose level of a user, the user-specified information about the one or more events influential on the blood glucose level of the user describing;

(a) consumption of carbohydrates by the user, (b) a discrete dose of insulin received by the user, or (c) a quantity of exercise completed by the user;

receiving, from a continuous glucose monitor, a plurality of blood glucose levels for the user after receiving the user-specified information;

accessing, in a computer-based memory, one or more normalized curves, each having a shape that represents generically any of;

(i) how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time, (ii) how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or (iii) how a dimensionless quantity of exercise fractionally takes effect on the generic user as a function of percent of total time for the exercise to take full effect on the user;

generating a nominal trajectory of the blood glucose level of the user by parameterizing one or more of the generic, normalized curves with the user-specified information about the one or more events influential on the blood glucose level of the user;

applying an iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting different types of the user-specified information at different rates based on an expected accuracy of the user-specified information until the iterative search converges on one or more of;

an amount of, time of, and absorption time of one or more of the following;

(a) carbohydrates actually consumed by the user,

(b) a discrete dosage of insulin actually received by the user, and

(c) a quantity of exercise actually completed by the user,

that produces a trajectory that matches the plurality of blood glucose levels received after the time of the one or more events more closely than the nominal trajectory; and

delivering insulin to the user based on the trajectory generated by the iterative search.

2. The method of claim 1, wherein delivering insulin to the user comprises determining an insulin on board for the user based on the trajectory generated by the iterative search.

3. The method of claim 1, further comprising triggering an alarm when the trajectory generated by the iterative search indicates that insulin was not actually delivered.

4. The method of claim 1, wherein the user-specified information about the one or more events influential on the blood glucose level of the user includes at least two of:

(a) a consumption of carbohydrates by the user, (b) a discrete dose of insulin received by the user, and (c) a quantity of exercise completed by the user.

5. The method of claim 1, further comprising displaying the trajectory generated by the iterative search, the trajectory including future projected blood glucose levels of the user.

6. The method of claim 5, further comprising displaying an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search, the upper projection and the lower projection indicative of a confidence band reflecting a degree of confidence in the future projected blood glucose levels.

7. The method of claim 6, wherein displaying an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search further comprises super-imposing the upper projection and the lower projection over the trajectory generated by the iterative search.

8. The method of claim 1, wherein the iterative search includes a gradient descent algorithm seeded with a midpoint of a constrained range for one or more parameters used to generate the nominal trajectory, the one or more parameters including the user-specified information.

9. The method of claim 1, wherein applying an iterative search to generate one or more other trajectories is continued until stopping conditions are met.

10. The method of claim 1, wherein the user-specified information includes a start time of a given event and a quantity associated with the given event.

11. The method of claim 10, further comprising determining a duration for the given event based on the start time and the quantity associated with the given event, wherein the nominal trajectory is based on the duration for the given event.

12. The method of claim 1, wherein the trajectory generated by the iterative search includes a first portion that overlaps in time with at least one of the plurality of blood glucose levels received from the continuous glucose monitor, and a second portion that extends as future projected blood glucose levels.

13. The method of claim 1, wherein the nominal trajectory is further based on one or more additional factors including:

an insulin-to-carbohydrate ratio, an insulin sensitivity factor, and a time of carbohydrate absorption.

14. The method of claim 13, wherein at least one of the one or more additional factors has a value that depends on a time of day.

15. A method for determining when to trigger an occlusion alarm when managing diabetes, the method comprising:

receiving insulin delivery data from an insulin pump, wherein the insulin delivery data relates to one or more doses of insulin believed to have been received by a user;

receiving, from a continuous glucose monitor, a plurality of blood glucose levels for the user after receiving the insulin delivery data;

receiving user-specified information;

accessing, in a computer-based memory, one or more normalized curves, each having a shape that represents generically any of;

(i) how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time, (ii) how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or (iii) how a dimensionless quantity of exercise fractionally takes effect on the generic user as a function of percent of total time for the exercise to take full effect on the user;

generating a nominal trajectory of the blood glucose levels of the user by parameterizing one or more of the generic, normalized curves with the insulin delivery data and parameterization of the user-specified information;

applying an iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting different types of the user-specified information at different rates based on an expected accuracy of the user-specified information until the iterative search converges on one or more of;

an amount of, time of, and absorption time of one or more of the following;

(a) carbohydrates actually consumed by the user,

(b) a discrete dosage of insulin actually received by the user, and

(c) a quantity of exercise actually completed by the user,

that produces a trajectory that matches the plurality of blood glucose levels received after receiving the insulin delivery data more closely than the nominal trajectory;

generating one or more second estimated trajectories using normalized curves that exclude any insulin deliveries;

comparing a fit of the one or more second estimated trajectories to the trajectory generated by the iterative search using insulin delivery data to determine a likelihood that insulin was not actually delivered; and

triggering a sensory alarm if the likelihood is above a certain threshold.

16. The method of claim 15, wherein generating one or more second estimated trajectories comprises applying the iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting one or more parameterizations of the generic, normalized curves until the iterative search converges on one or more of:

an amount of, time of, or absorption time of one or more of the following;

(a) carbohydrates actually consumed by the user,

(b) a discrete dosage of insulin actually received by the user, or

(c) a quantity of exercise actually completed by the user,

that produces a trajectory that matches the plurality of blood glucose levels received after receiving the insulin delivery data more closely than the nominal trajectory.

17. The method of claim 15, wherein the user-specified information includes a start time of a given event and a quantity associated with the given event.

18. The method of claim 17, further comprising determining a duration for the given event based on the start time and the quantity associated with the given event, wherein the nominal trajectory is based on the duration for the given event.

19. The method of claim 15, wherein the user-specified information includes at least one of:

(a) a consumption of carbohydrates by the user, (b) a discrete dose of insulin received by the user, and (c) a quantity of exercise completed by the user.

20. The method of claim 15, further comprising displaying the trajectory generated by the iterative search.

21. The method of claim 20, further comprising displaying an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search, the upper projection and the lower projection indicative of a confidence band reflecting a degree of confidence in future projected blood glucose levels.

22. The method of claim 21, wherein displaying an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search further comprises super-imposing the upper projection and the lower projection over the trajectory generated by the iterative search.

23. The method of claim 15, wherein the trajectory generated by the iterative search includes a first portion that overlaps in time with at least one of the plurality of blood glucose levels received from the continuous glucose monitor, and a second portion that extends as future projected blood glucose levels.

24. The methods of claim 15, wherein the nominal trajectory is further based on one or more additional factors including:

an insulin-to-carbohydrate ratio, an insulin sensitivity factor, and a time of carbohydrate absorption.

25. The methods of claim 24, wherein at least one of the one or more additional factors has a value that depends on a time of day.

26. The method of claim 15, wherein the sensory alarm includes an audible alarm or a tactile alarm.

27. The method of claim 15, wherein the iterative search includes a gradient descent algorithm seeded with a midpoint of a constrained range for one or more parameters used to generate the nominal trajectory, wherein the generic, normalized curves are based on the one or more parameters.

28. The method of claim 15, wherein applying an iterative search to generate one or more other trajectories is continued until stopping conditions are met.

29. A system for managing diabetes, the system comprising:

a control device comprising;

a user interface configured to obtain user-specified information about one or more events influential on a blood glucose level of a user;

one or more processors; and

one or more non-transitory storage media storing instructions that, when executed by the one or more processors, are configured to cause the control device to perform operations, the operations comprising;

receiving the user-specified information about the one or more events influential on a blood glucose level of the user describing one or more of;

(a) a consumption of carbohydrates by the user, (b) a discrete dose of insulin received by the user, and (c) a quantity of exercise completed by the user

receiving a plurality of blood glucose levels for the user after receiving the user-specified information;

accessing one or more normalized curves, each having a shape that represents generically any of;

(i) how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time, (ii) how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or (iii) how a dimensionless quantity of exercise fractionally takes effect on the generic user as a function of percent of total time for the exercise to take full effect on the user;

generating a nominal trajectory of the blood glucose levels of the user by parameterizing one or more of the generic, normalized curves with the user-specified information about the one or more events influential on the blood glucose level of the user;

applying an iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting different types of the user-specified information at different rates based on an expected accuracy of the user-specified information until the iterative search converges on one or more of;

an amount of, time of, or absorption time of one or more of the following;

 

(a) carbohydrates actually consumed by the user,

 

(b) a discrete dosage of insulin actually received by the user, and

 

(c) a quantity of exercise actually completed by the user,

that produces a trajectory that matches the plurality of blood glucose levels received after the time of the one or more events more closely than the nominal trajectory; and

generating a command to deliver insulin to the user based on the trajectory generated by the iterative search; and

an insulin pump configured to deliver insulin to the user based on the command to deliver insulin.

30. The system of claim 29, further comprising a continuous glucose monitor configured to communicate the plurality of blood glucose levels of the user to the control device.

31. The system of claim 29, wherein the operations further comprise generating one or more second estimated trajectories that exclude any insulin deliveries by applying the iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting one or more parameterizations of the generic, normalized curves until the iterative search converges on one or more:

an amount of, time of, or absorption time of one or more of the following;

(a) carbohydrates actually consumed by the user,

(b) a discrete dosage of insulin actually received by the user, and

(c) a quantity of exercise actually completed by the user, that produces a trajectory that matches the plurality of blood glucose levels received after the time of the one or more events more closely than the nominal trajectory.

32. The system of claim 31, further comprising an alarm generation device configured to generate an alarm based on an alarm message from the control device, wherein the operations further comprise:

comparing a fit of the one or more second estimated trajectories to the trajectory generated by the iterative search using insulin delivery data to determine a likelihood that insulin was not actually delivered; and

generating the alarm message if the likelihood is above a particular threshold.

33. The system of claim 29, further comprising a display configured to display the trajectory generated by the iterative search, the trajectory including future projected blood glucose levels of the user.

34. The system of claim 33, wherein the display is further configured to display an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search, the upper projection and the lower projection indicative of a confidence band reflecting a degree of confidence in the future projected blood glucose levels.

35. The system of claim 34, wherein the display is further configured to super-impose the upper projection and the lower projection over the trajectory generated by the iterative search.

36. A system comprising:

an insulin pump configured to deliver insulin to a user;

a control device comprising;

one or more processors; and

one or more non-transitory storage media storing instructions that, when executed by the one or more processors, are configured to cause the control device to perform operations, the operations comprising;

receiving insulin delivery data from the insulin pump, wherein the insulin delivery data relates to one or more doses of insulin believed to have been received by the user

receiving a plurality of blood glucose levels for the user after receiving the insulin delivery data;

receiving user-specified information

accessing one or more normalized curves, each having a shape that represents generically any of;

(i) how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time, (ii) how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or (iii) how a dimensionless quantity of exercise fractionally takes effect on the generic user as a function of percent of total time for the exercise to take full effect on the user;

generating a nominal trajectory of the blood glucose level of the user by parameterizing one or more of the generic, normalized curves with the insulin delivery data and parameterization of the user-specified information;

applying an iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting different types of the user-specified information at different rates based on an expected accuracy of the user-specified information until the iterative search converges on one or more of

an amount of, time of, or absorption time of one or more of the following;

 

(a) carbohydrates actually consumed by the user,

 

(b) a discrete dosage of insulin actually received by the user, and

 

(c) a quantity of exercise actually completed by the user, that produces a trajectory that matches the plurality of blood glucose levels received after receiving the insulin delivery data more closely than the nominal trajectory;

generating one or more second estimated trajectories using normalized curves that exclude any insulin deliveries;

comparing a fit of the one or more second estimated trajectories to the trajectory generated by the iterative search using insulin delivery data to determine a likelihood that insulin was not actually delivered; and

generating an alarm command if the likelihood is above a certain threshold; and

an alarm generation device configured to generate a sensory alarm based on the alarm command from the control device.

37. The system of claim 36, wherein generating one or more second estimated trajectories comprises applying the iterative search to generate one or more other trajectories based on the nominal trajectory by adjusting one or more parameterizations of the generic, normalized curves until the iterative search converges on one or more of:

an amount of, time of, or absorption time of one or more of the following;

(a) carbohydrates actually consumed by the user,

(b) a discrete dosage of insulin actually received by the user, and

(c) a quantity of exercise actually completed by the user, that produces a trajectory that matches the plurality of blood glucose levels received after receiving the insulin delivery data more closely than the nominal trajectory.

38. The system of claim 36, wherein the control device further comprises a user interface configured to receive the user-specified information, wherein the nominal trajectory is further generated by parameterization of the user-specified information.

39. The system of claim 36, further comprising a display configured to display the trajectory generated by the iterative search, the trajectory including future projected blood glucose levels of the user.

40. The system of claim 39, wherein the display is further configured to display an upper projection above the trajectory generated by the iterative search and a lower projection below the trajectory generated by the iterative search, the upper projection and the lower projection indicative of a confidence band reflecting a degree of confidence in the future projected blood glucose levels.

41. The system of claim 40, wherein the display is further configured to super-impose the upper projection and the lower projection over the trajectory generated by the iterative search.

42. The system of claim 39, wherein the display is further configured to super-impose the one or more second estimated trajectories over the trajectory generated by the iterative search.

43. The system of claim 36, wherein the alarm generation device includes a speaker, a vibrator, or both.