COMPUTER-BASED DIABETES MANAGEMENT

• US 20140128705A1
• Filed: 01/10/2013
• Published: 05/08/2014
• Est. Priority Date: 11/07/2012
• Status: Active Grant

• Current Assignee: Bigfoot Biomedical, Inc.
• Original Assignee: Smartloop, LLC
• Inventors: Mazlish, Bryan
• Granted Patent: US 9,833,191 B2
• Time in Patent Office: Days
• US Class Current: 600/365
• 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 computer-based method comprising:

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,

wherein 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.

2. The computer-based method of claim 1, wherein generating the plurality of estimated trajectories of the user'"'"'s blood glucose level comprises:

generating a nominal trajectory of the user'"'"'s blood glucose level using mid-point values in a range of values associated with each of a plurality of parameters; and

generating one or more other trajectories of the user'"'"'s blood glucose level, at least one of which represents a better fit than the nominal trajectory to the set of data that represents the actual blood glucose measurements.

3. The computer-based method of claim 2, wherein identifying which of the estimated trajectories represents the best fit to the set of data that represents the actual blood glucose measurements for the user, comprises:

identifying which of the nominal trajectory or one or more other trajectories represents the best fit to the actual blood glucose measurements for the user.

4. The computer-based method of claim 3, wherein identifying which of the nominal trajectory or other trajectories represents the best fit to the set of data that represents the actual blood glucose measurements for the user comprises:

calculating, with the computer-based processor, an absolute difference between a value at a point in time as represented by each of the nominal trajectory and other trajectories and a corresponding value at the point in time as represented by the actual blood glucose measurements; and

considering the calculated differences in identifying the best fit.

5. The computer-based method of claim 4, wherein identifying which of the nominal trajectory or other trajectories represents the best fit to the set of data that represents the actual blood glucose measurements for the user comprises:

calculating, with the computer-based processor, a first derivative and/or a second derivative associated with each of the nominal trajectory and other trajectories; and

considering the calculated first derivatives and/or second derivatives in identifying the best fit.

6. The computer-based method of claim 1, wherein the set of data that represents the actual blood glucose measurements for the user is obtained using a continuous glucose monitor or a blood glucose meter.

7. The computer-based method of claim 1, wherein the user-specified information about the one or more events influential on the user'"'"'s blood glucose describes:

the user'"'"'s consumption of carbohydrates,

a discrete dose of insulin received by the user, or

a quantity of exercise completed by the user.

8. The computer-based method of claim 7, wherein a change in insulin basal rate for the user is represented by a sequence of discrete doses of insulin, wherein the sequence of discrete doses can be positive or negative depending on whether the change in insulin basal rate is an increase or decrease, respectively.

9. The computer-based method of claim 7, wherein, for each event, the user-specified information comprises:

a start time associated with the event, and

a quantity associated with the event, wherein the quantity associated with the event represents a quantity of the carbohydrates consumed, a quantity of insulin in the discrete dose received, or an amount of exercise that the user completed.

10. The computer-based method of claim 9, further comprising, for each event:

assigning, with the computer-based processor, a duration associated with the event, wherein the duration associated with the event represents an estimate of;

how long it will take for the carbohydrates that were consumed to be fully absorbed by the user,

how long it will take for the dose of insulin that was received to be fully absorbed by the user, or

how long it will take for the quantity of exercise completed by the user to fully affect the user'"'"'s blood glucose level.

11. The computer-based method of claim 1, wherein generating the plurality of estimated trajectories of the user'"'"'s blood glucose level over time comprises, for each event:

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

how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time,

how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or

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; and

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

applying an optimization search to create one or more other trajectories, wherein the optimization search iterates until it converges on a solution that is deemed optimal.

12. The computer-based method of claim 11, wherein each event candidate curve is based on a different set of the parameters relative to the other event candidate curves,

wherein a set of the parameters associated with each event candidate curve includes a start time, a duration, and a quantity.

13. The computer-based method of claim 11, wherein the set of parameters associated with each respective one of the events comprises:

a start time associated with that event,

a quantity associated with that event, wherein the quantity represents an amount of carbohydrates consumed, an amount of insulin by the user in a discrete dose, or an amount of exercise accomplished by the user, and

a duration associated with that event, wherein the duration represents a total absorption time for the carbohydrates ingested, a total absorption time for the dose of insulin received, or a total amount of time that the exercise accomplished will affect the user'"'"'s blood glucose level.

14. The computer-based method of claim 11, wherein values for the parameters of each event candidate curve for the event are selected from specified ranges of values around values received with the user-specified information about the event.

15. The computer-based method of claim 11, wherein each of the event candidate curves represents an example of:

how the quantity of carbohydrates consumed might be absorbed by the user over time,

how the quantity of the insulin dose received might be absorbed by the user over time, or

how the exercise completed by the user might affect the user'"'"'s blood glucose level over time.

16. The computer-based method of claim 11, wherein generating the plurality of estimated trajectories of the user'"'"'s blood glucose level as influenced by the one or more events comprises:

combining effects of the event candidate curves associated with more than one of the events to produce each of the plurality of estimated trajectories.

17. The computer-based method of claim 1, further comprising:

displaying, at a computer-based visual display, a visual representation of the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

18. The computer-based method of claim 17, wherein the visual representation is a curve that represents estimated future blood glucose levels for the user.

19. The computer-based method of claim 17, further comprising:

displaying, at the computer-based visual display, a visual representation of upper and lower boundaries of the estimated future blood glucose levels for the user,

wherein the visual representation of the upper and lower boundaries are superimposed over the visual representation of the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

20. The computer-based method of claim 19, wherein the upper and lower boundaries are determined by perturbing the estimated trajectory that represents the best fit with upper and lower values in corresponding ranges associated with parameters for the one or more events.

21. The computer-based method of claim 1, wherein each of the estimated trajectories has:

a first portion that overlaps in time at least some of the set of data that represents the actual blood glucose measurements for the user; and

a second portion that extends in time beyond the set of data that represents the actual blood glucose measurements for the user.

22. The computer-based method of claim 21, wherein identifying which of the estimated trajectories represents the best fit to the actual blood glucose measurements for the user comprises:

considering which of the estimated trajectories has a first portion that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

23. The computer-based method of claim 1, further comprising:

receiving, via the computer-based user interface, information related to user-specific, diabetes-related therapy characteristics,

wherein the user-specific, diabetes-related therapy parameters include one or more of the following;

a range of insulin-to-carbohydrate ratios, a range of insulin sensitivity factors, a range representing a duration of insulin action, a range representing a duration for carbohydrate absorption, a range representing a duration of effect associated with exercise done by the user, and a range of exercise per hour to carbohydrate ratios representing how many carbohydrates are needed to offset the blood glucose lowering effect of one hour of exercise for the user.

24. The computer-based method of claim 1, wherein the user-specified information about each of the one or more events comprises a start time and a quantity,

wherein the start time and the quantity have specified ranges that depend on a type of event associated with the start time and the quantity.

25. The computer-based method of claim 24, wherein one or more of the range of insulin-to-carbohydrate ratios, the range of insulin sensitivity factors, the range representing a duration of insulin action specific to the user, the range representing a time for carbohydrate absorption, the range representing the duration of effect associated with exercise done by the user, and the range representing the exercise per hour to carbohydrate ratios, has values that differ depending on a time of day.

26. The computer-based method of claim 1, wherein the computer-based processor is configured to identify a therapeutic recommendation for the user based on the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

27. The computer-based method of claim 1, wherein the computer-based user interface is integrated into a computer-based visual display.

28. The computer-based method of claim 1, further comprising:

identifying, with the computer-based processor, an amount of insulin that the user has received that is yet to be absorbed by the user and an amount of carbohydrates that the user has received that is yet to be absorbed by the user.

29. The computer-based method of claim 1, further comprising:

calculating, with the computer-based processor, a recommended dose of insulin or a recommended quantity of carbohydrates to consume based, at least in part, on an amount of carbohydrates that the user has received that is yet to be absorbed by the user.

30. The computer-based method of claim 29, wherein calculating the recommended dose of insulin or the recommended quantity of carbohydrates to consume is further based on one or more of:

the user'"'"'s current blood glucose value;

information about a planned consumption of carbohydrates by the user,

the amount of insulin that the user has received that is yet to be absorbed by the user,

an amount of insulin that the user plans to receive,

an amount of exercise the user has accomplished that is yet to take full effect on the user,

an amount of exercise that the user plans to accomplish, and

the user'"'"'s target blood glucose level or range.

31. The computer-based method of claim 1, further comprising:

generating, with the computer-based processor, a plurality of second estimated trajectories of the user'"'"'s blood glucose level as influenced by the one or more events, but excluding any insulin deliveries that the user has indicated he or she received;

identifying, with the computer-based processor, which of the second estimated trajectories represents a best fit to the set of data that represents the actual blood glucose measurements for the user;

comparing the best fit of the second estimated trajectories to the first estimated trajectory to determine a likelihood that insulin was not actually delivered; and

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

32. A computer system comprising:

a computer-based user interface; and

a computer-based processor coupled to the computer-based interface,

wherein the computer-based processor is configured to;

receive, from the computer-based user interface, user-specified information about one or more events influential on the user'"'"'s blood glucose level;

generate a plurality of estimated trajectories of the user'"'"'s blood glucose level as influenced by the one or more events;

receive a set of data that represents actual blood glucose measurements for the user; and

identify which of the estimated trajectories represents a best fit to the set of data that represents the actual blood glucose measurements for the user,

wherein at least some of the actual blood glucose measurements occurred later in time than the one or more events influential on the user'"'"'s blood glucose level.

33. The computer system of claim 32, further comprising:

a continuous glucose monitor or a blood glucose meter,

wherein the set of data that represents the actual blood glucose measurements for the user is obtained using the continuous glucose monitor or the blood glucose meter.

34. The computer system of claim 32, wherein the user-specified information about the one or more events influential on the user'"'"'s blood glucose describes:

the user'"'"'s consumption of carbohydrates,

a discrete dose of insulin received by the user, or

a quantity of exercise completed by the user.

35. The computer system of claim 34, wherein a change in insulin basal rate for the user is represented by a sequence of discrete doses of insulin, wherein the sequence of discrete doses can be positive or negative depending on whether the change in insulin basal rate is an increase or decrease, respectively.

36. The computer system of claim 32, wherein, for each event, the user-specified information comprises:

a start time associated with the event, and

a quantity associated with the event, wherein the quantity associated with the event represents a quantity of the carbohydrates consumed, a quantity of insulin in the discrete dose received, or an amount of exercise that the user completed.

37. The computer system of claim 36, wherein the computer-based processor is further configured to:

assign, for each event, a duration associated with the event, wherein the duration associated with the event represents;

how long it will take for the carbohydrates that were consumed to be fully absorbed by the user,

how long it will take for the dose of insulin that was received to be fully absorbed by the user, or

how long it will take for the quantity of exercise completed by the user to fully affect the user'"'"'s blood glucose level.

38. The computer system of claim 32, further comprising:

a computer-based memory coupled to the computer-based processor,

wherein generating the plurality of estimated trajectories of the user'"'"'s blood glucose level over time comprises, for each event;

accessing, from the computer-based memory, a normalized curve having a shape that represents generically;

how a dimensionless unit of carbohydrates consumed is fractionally absorbed by a generic user as a function of percent of total carbohydrate absorption time,

how a dimensionless unit of insulin is fractionally absorbed by the generic user as a function of percent of total insulin absorption time, or

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; and

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

applying an optimization search to create one or more other trajectories, wherein the optimization search iterates until it converges on a solution that is deemed optimal.

39. The computer system claim 38, wherein each of the event candidate curves is based on a different set of the parameters relative to other event candidate curves, wherein the parameters associated with each event candidate curve include a start time, a duration, and a quantity.

40. The computer system of claim 39, wherein the parameters associated with each of the events comprise:

a start time associated with that event,

a quantity associated with that event, wherein the quantity represents an amount of carbohydrates consumed, an amount of insulin by the user in a discrete dose, or an amount of exercise accomplished by the user, and

a duration associated with that event, wherein the duration represents a total absorption time for the carbohydrates ingested, a total absorption time for the dose of insulin received, or a total amount of time that the exercise accomplished will affect the user'"'"'s blood glucose level.

41. The computer system of claim 38, wherein values for the parameters of each event candidate curve for the event are selected from specified ranges of values around values received with the user-specified information about the event.

42. The computer system of claim 37, wherein each event candidate curves represents an example of:

how the quantity of carbohydrates consumed might be absorbed by the user over time,

how the quantity of the insulin dose received might be absorbed by the user over time, or

how the exercise completed by the user might affect the user'"'"'s blood glucose level over time.

43. The computer system of claim 32, wherein generating the plurality of estimated trajectories of the user'"'"'s blood glucose level over time as influenced by the one or more events comprises:

combining effects of the event candidate curves associated with more than one of the events to produce each of the plurality of estimated trajectories.

44. The computer system of claim 32, further comprising:

a computer-based visual display,

wherein the computer-based visual display is configured to display a visual representation of the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

45. The computer system of claim 44, wherein the visual representation is a curve that includes at least a portion that represents estimated future blood glucose levels for the user.

46. The computer system of claim 44, wherein the computer-based processor is further configured to:

display, at the computer-based visual display, a visual representation of upper and lower boundaries of the estimated future blood glucose levels for the user,

wherein the visual representation of the upper and lower boundaries are superimposed over the visual representation of the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

47. The computer system of claim 46, wherein the upper and lower boundaries are determined by perturbing the estimated trajectory that represents the best fit with upper and lower values in corresponding ranges associated with the one or more events.

48. The computer system of claim 32, wherein each of the estimated trajectories has:

a first portion that overlaps in time at least some of the set of data that represents the actual blood glucose measurements for the user; and

a second portion that extends in time beyond the set of data that represents the actual blood glucose measurements for the user,

wherein identifying which of the estimated trajectories represents the best fit to the set of data that represents the actual blood glucose measurements for the user comprises considering which of the estimated trajectories has a first portion that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

49. The computer system of claim 32, wherein the computer-based user interface is configured to receive information related to user-specific, diabetes-related therapy characteristics,

wherein the user-specific, diabetes-related therapy parameters include some or all of the following:

a range of insulin-to-carbohydrate ratios, a range of insulin sensitivity factors, a range representing a duration of insulin action, a range representing a duration for carbohydrate absorption a range representing a duration of effect associated with exercise done by the user, and a range of exercise per hour to carbohydrate ratios representing how many carbohydrates are needed to offset the blood glucose lowering effect of one hour of exercise for the user.

50. The computer system of claim 32, wherein the user-specified information about each of the one or more events comprises a start time and a quantity,

wherein the start time and the quantity have specified ranges that depend on a type of event associated with the start time and the quantity.

51. The computer system of claim 50, wherein one or more of the range of insulin-to-carbohydrate ratios, the range of insulin sensitivity factors, the range representing a duration of insulin action specific to the user, the range representing a time for carbohydrate absorption, the range representing the duration of effect associated with exercise done by the user, and the range of exercise per hour to carbohydrate ratios representing, has a value that depends on a time of day.

52. The computer system of claim 32, wherein the computer-based processor is further configured to identify a therapeutic recommendation for the user based on the estimated trajectory that represents the best fit to the set of data that represents the actual blood glucose measurements for the user.

53. The computer system of claim 32, wherein the computer-based user interface is integrated into a computer-based visual display.

54. The computer system of claim 32, wherein the computer-based processor is configured to identify an amount of insulin that the user has received that is yet to be absorbed by the user and an amount of carbohydrates that the user has received that is yet to be absorbed by the user.

55. The computer system of claim 32, wherein the computer-based processor is further configured to:

calculate a recommended dose of insulin or a recommended quantity of carbohydrates to consume based, at least in part, on an amount of carbohydrates that the user has received that is yet to be absorbed by the user.

56. The computer system of claim 55, wherein the recommended dose of insulin or recommended quantity of carbohydrates to consume is further based on one or more of:

the user'"'"'s current blood glucose value;

information about a planned consumption of carbohydrates by the user,

the amount of insulin that the user has received that is yet to be absorbed by the user,

an amount of insulin that the user plans to receive,

an amount of exercise the user has accomplished that is yet to take full effect on the user,

an amount of exercise that the user plans to accomplish, and

the user'"'"'s target blood glucose level or range.

57. The computer system of claim 32, further comprising:

an occlusion alarm coupled to the computer-based processor,

wherein the computer-based processor is further configured to

generate a plurality of second estimated trajectories of the user'"'"'s blood glucose level as influenced by the one or more events, but excluding any insulin deliveries that the user has indicated he or she received;

identify which of the second estimated trajectories represents a best fit to the set of data that represents the actual blood glucose measurements for the user;

comparing the best fit of the second estimated trajectories to the first estimated trajectory to determine a likelihood that insulin was not actually delivered; and

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

58. A non-transitory, computer-readable medium that stores instructions executable by a computer-based processor to perform the steps comprising:

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

generating 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 which of the estimated trajectories represents a best fit to the set of data that represents the actual blood glucose measurements for the user,

wherein at least some of the actual blood glucose measurements occurred later in time than the one or more events influential on the user'"'"'s blood glucose level.

59. A computer-based method comprising:

calculating, with a computer-based processor, a recommended dose of insulin or a recommended quantity of carbohydrates to consume based, at least in part, on the amount of carbohydrates that a user has received that is yet to be absorbed by the user.

60. The computer-based method of claim 59, wherein the recommended dose of insulin or the recommended quantity of carbohydrates to consume is further based on one or more of:

the user'"'"'s current blood glucose value;

information about a planned consumption of carbohydrates by the user,

the amount of insulin that the user has received that is yet to be absorbed by the user,

an amount of insulin that the user plans to receive,

an amount of exercise the user has accomplished that is yet to take full effect on the user,

an amount of exercise that the user plans to accomplish, and

the user'"'"'s target blood glucose level or range.

61. A computer system comprising:

a computer-based user interface; and

a computer-based processor coupled to the computer-based interface, wherein the computer-based processor is configured to calculate a recommended dose of insulin or a recommended quantity of carbohydrates to consume based, at least in part, on an amount of carbohydrates that a user has received that is yet to be absorbed by the user.

62. The computer system of claim 61, wherein the recommended dose of insulin or the recommended quantity of carbohydrates to consume is further based on one or more of:

the user'"'"'s current blood glucose value;

information about a planned consumption of carbohydrates by the user,

the amount of insulin that the user has received that is yet to be absorbed by the user,

an amount of insulin that the user plans to receive,

an amount of exercise the user has accomplished that is yet to take full effect on the user,

an amount of exercise that the user plans to accomplish, and

the user'"'"'s target blood glucose level or range.

63. A non-transitory, computer-readable medium that stores instructions executable by a computer-based processor to perform the steps comprising:

calculating a recommended dose of insulin or a recommended quantity of carbohydrates to consume based, at least in part, on the amount of carbohydrates that a user has received that is yet to be absorbed by the user.

64. The non-transitory, computer-readable medium of claim 63, wherein the recommended dose of insulin or the recommended quantity of carbohydrates to consume is further based on one or more of:

the user'"'"'s current blood glucose value;

information about a planned consumption of carbohydrates by the user,

the amount of insulin that the user has received that is yet to be absorbed by the user,

an amount of insulin that the user plans to receive,

an amount of exercise the user has accomplished that is yet to take full effect on the user,

an amount of exercise that the user plans to accomplish, and

the user'"'"'s target blood glucose level or range.