System and method for monitoring and controlling the glycemic state of a patient

• US 6,572,542 B1
• Filed: 03/03/2000
• Issued: 06/03/2003
• Est. Priority Date: 03/03/2000
• Status: Expired due to Term

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Houben, Richard, Larik, Vincent
• Primary Examiner(s): Hindenburg, Max F.
• Assistant Examiner(s): ASTORINO, MICHAEL C
• Application Number:
  US09/518,796
• Time in Patent Office: 1,187 Days
• Field of Search: 706/924, 705/2-3, 600/300, 600/301, 600/345-365, 600/544-545, 604/66, 128/920-925
• US Class Current: 600/300
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61M 2230/04 Heartbeat characteristics, e.g. ECG, blood pressure modulation
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/14244 adapted to be carried by the patient, e.g. portable on the body
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

Information derived from ECG signals and EEG signals may be employed in combination to reliably predict the onset, or to indicate the presence of, hypoglycemia in a human patient. In one embodiment, ECG and EEG signals are processed and the information derived from them is combined to determine whether a patient suffering from diabetes is undergoing a hypoglycemic event, or whether such an event is imminent. Input data from the patient or a health care provider may also be used to increase the accuracy and reliability of the system. Detection of a hypoglycemic event by the system can result in the output of an alarm signal and/or the delivery or administration of a beneficial agent such as insulin, glucagon or diazoxide to the patient. The system may be implantable, external, or a combination of external and implantable components. The control strategy of the present system is preferably microprocessor based and/or implemented using dedicated electronics. In another embodiment, the glycemic state of the patient is continuously or relatively continuously monitored and controlled by the system. The system may contain any of a number of different types of feedback control systems for monitoring the glycemic state of a patient and controlling same, such as fuzzy logic systems, adaptive systems, reinforcement learning systems, and the like.

Claims

1. A system for at least one of predicting the onset of, and determining the presence of, hypoglycemia in a patient, comprising:

an ECG sensor for obtaining signals representative of the patient'"'"'s ECG;

an EEG sensor for obtaining signals representative of the patient'"'"'s EEG;

first signal processing means for processing said ECG signals to provide first parameter data indicative of the patient'"'"'s current blood insulin level;

second signal processing means for processing said EEG signals to provide second parameter data indicative of the patient'"'"'s future glucose level;

means for providing a response to modify the patient'"'"'s blood insulin level as a function of said first parameter data indicative of the patient'"'"'s current blood insulin level and said second parameter data indicative of the patient'"'"'s future glucose level.

2. The system of claim 1, wherein said response means comprises means for outputting an indication of the patient'"'"'s blood insulin level.

3. The system of claim 1, wherein said response means comprises means for outputting an indication of the patient'"'"'s glucose level.

4. The system of claim 1, wherein said response means comprises means for providing an alarm to at least one of the patient and a health care provider.

5. The system of claim 1, wherein said response means comprises means for delivering a beneficial agent to the patient.

6. The system of claim 1, wherein the means for response is a beneficial agent selected from the group consisting of glucagon, diazoxide, glucose, insulin, and a sulfonylurea-based drug.

7. The system of claim 1, wherein at least portions of the system are implantable.

8. The system of claim 1, wherein at least portions of said system are implantable in said patient and said response means comprises means for injecting a beneficial agent into said patient as a function of at least one of said first parameter data and said second parameter.

9. The system of claim 8, wherein said means for injecting a beneficial agent comprises a pump.

10. The system of claim 1, further comprising a wearable housing for housing at least portions of said system and adapted to be worn by a patient.

11. The system of claim 1, wherein said response means comprises output means for providing an output signal representative of the patient'"'"'s insulin level.

12. The system of claim 1, wherein said response providing means further comprises means for analyzing said first and second parameter data.

13. The system of claim 12, wherein said response providing means further comprises additional response means for providing an additional response as a function of said analyzed first and second parameter data.

14. The system of claim 1, further comprising input means for inputting additional data.

15. The system of claim 14, wherein the input means is external.

16. The system of claim 14, wherein the additional data are representative of data selected from the group consisting of glucose intake data, insulin data, sleep episode data, hypoglycemic sensation data, post-prandial event data, and error data.

17. The system of claim 1, wherein the first signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

18. The system of claim 1, wherein the second signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

19. The system of claim 1, wherein the response providing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

20. The system of claim 1, wherein the response providing means comprises a device selected from the group consisting of a reinforcement learning processor, a neural network processor, an adaptive fuzzy logic processor, an adaptive processor, and an adaptive fuzzy inferencing processor.

21. The system of claim 1, further comprising storage means for storing patient blood insulin levels.

22. The system of claim 1, further comprising storage means for storing patient glucose levels.

23. The system of claim 1, wherein said response providing means further comprises extrapolation means for extrapolating anticipated time of insulin need as a function of said stored patient blood insulin levels.

24. The system of claim 1, further comprising means for processing said ECG signals and obtaining therefrom an indication of patient blood glucose.

25. The system of claim 1, wherein said response providing means further comprises delivery means for delivering insulin to the patient and control means for controlling said delivery means to provide indicated insulin in response to indicated patient insulin and glucose levels.

26. The system of claim 1 wherein the patient'"'"'s future blood insulin level is estimated by analyzing the patient'"'"'s ECG time rate of change.

27. The system of claim 26 wherein the patient'"'"'s future blood insulin level improves accuracy in predicting the onset or presence of a hypoglycemic state.

28. A system for monitoring a glycemic state of a patient and controlling the glycemic state of the patient, comprising:

an ECG sensor for obtaining signals representative of the patient'"'"'s ECG;

an EEG sensor for obtaining signals representative of the patient'"'"'s EEG;

first signal processing means for processing said ECG signals to provide first parameter data indicative of the patient'"'"'s current blood insulin level;

second signal processing means for processing said EEG signals to provide second parameter data indicative of the patient'"'"'s future glucose level;

means for providing a response to modify the patient'"'"'s blood insulin level as a function of said first parameter data indicative of the patient'"'"'s current blood insulin level and said second parameter data indicative of the patent'"'"'s future glucose level.

29. The system of claim 28, wherein said response means comprises means for outputting an indication of the patient'"'"'s blood insulin level.

30. The system of claim 28, wherein said response means comprises means for outputting an indication of the patient'"'"'s glucose level.

31. The system of claim 28, wherein said response means comprises means for providing an alarm to at least one of the patient and a health care provider.

32. The system of claim 28, wherein said response means comprises means for delivering a beneficial agent to the patient.

33. The system of claim 28, wherein the means for response is a beneficial agent selected from the group consisting of glucagon, diazoxide, glucose, insulin, and a sulfonylurea-based drug.

34. The system of claim 28, wherein at least portions of the system are implantable.

35. The system of claim 28, wherein at least portions of said system are implantable in said patient and said response means comprises means for injecting a beneficial agent into said patient as a function of at least one of said first parameter data and said second parameter.

36. The system of claim 35, wherein said means for injecting a beneficial agent comprises a pump.

37. The system of claim 28, further comprising a wearable housing for housing at least portions of said system and adapted to be worn by a patient.

38. The system of claim 28, wherein said response means comprises output means for providing an output signal representative of the patient'"'"'s insulin level.

39. The system of claim 28, wherein said response providing means further comprises means for analyzing said first and second parameter data.

40. The system of claim 39, wherein said response providing means further comprises additional response means for providing an additional response as a function of said analyzed first and second parameter data.

41. The system of claim 28, further comprising input means for inputting additional data.

42. The system of claim 41, wherein the input means is external.

43. The system of claim 41, wherein the additional data are representative of data selected from the group consisting of glucose intake data, insulin data, sleep episode data, hypoglycemic sensation data, post-prandial event data, and error data.

44. The system of claim 28, wherein the first signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

45. The system of claim 28, wherein the second signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

46. The system of claim 28, wherein the response providing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

47. The system of claim 28, wherein the response providing means comprises a device selected from the group consisting of a reinforcement learning processor, a neural network processor, an adaptive fuzzy logic processor, an adaptive processor, and an adaptive fuzzy inferencing processor.

48. The system of claim 28, further comprising storage means for storing patient blood insulin levels.

49. The system of claim 28, further comprising storage means for storing patient glucose levels.

50. The system of claim 28, wherein said response providing means further comprises extrapolation means for extrapolating anticipated time of insulin need as a function of said stored patient blood insulin levels.

51. The system of claim 28, further comprising means for processing said ECG signals and obtaining therefrom an indication of patient blood glucose.

52. The system of claim 28, wherein said response providing means further comprises delivery means for delivering insulin to the patient and control means for controlling said delivery means to provide indicated insulin in response to indicated patient insulin and glucose levels.

53. The system of claim 28 wherein the patient'"'"'s future blood insulin level is estimated by analyzing the patient'"'"'s ECG time rate of change.

54. The system of claim 53 wherein the patient'"'"'s future blood insulin level improves accuracy in predicting the onset or presence of a hypoglycemic state.

55. A system for at least one of predicting the onset of, and determining the presence of, hypoglycemia in a patient, comprising:

an ECG sensor for obtaining signals representative of the patient'"'"'s ECG;

an EEG sensor for obtaining signals representative of the patient'"'"'s EEG;

signal processing means for processing said ECG signals to provide first parameter data indicative of the patient'"'"'s current blood insulin level and for processing said EEG signals to provide second parameter data indicative of the patient'"'"'s future glucose level;

means for providing a response to modify the patient'"'"'s blood insulin level as a function of said first parameter data indicative of the patient'"'"'s current blood insulin level and said second parameter data indicative of the patient'"'"'s future glucose level.

56. The system of claim 55, wherein said response means comprises means for outputting an indication of the patient'"'"'s blood insulin level.

57. The system of claim 55, wherein said response means comprises means for outputting an indication of the patient'"'"'s glucose level.

58. The system of claim 55, wherein said response means comprises means for providing an alarm to at least one of the patient and a health care provider.

59. The system of claim 55, wherein said response means comprises means for delivering a beneficial agent to the patient.

60. The system of claim 55, wherein the means for response is a beneficial agent selected from the group consisting of glucagon, diazoxide, glucose, insulin, and a sulfonylurea-based drug.

61. The system of claim 55, wherein at least portions of the system are implantable.

62. The system of claim 55, wherein at least portions of said system are implantable in said patient and said response means comprises means for injecting a beneficial agent into said patient as a function of at least one of said first parameter data and said second parameter.

63. The system of claim 62, wherein said means for injecting a beneficial agent comprises a pump.

64. The system of claim 55, further comprising a wearable housing for housing at least portions of said system and adapted to be worn by a patient.

65. The system of claim 55, wherein said response means comprises output means for providing an output signal representative of the patient'"'"'s insulin level.

66. The system of claim 55, wherein said response providing means further comprises means for analyzing said first and second parameter data.

67. The system of claim 66, wherein said response providing means further comprises additional response means for providing an additional response as a function of said analyzed first and second parameter data.

68. The system of claim 55, further comprising input means for inputting additional data.

69. The system of claim 68, wherein the input means is external.

70. The system of claim 68, wherein the additional data are representative of data selected from the group consisting of glucose intake data, insulin data, sleep episode data, hypoglycemic sensation data, post-prandial event data, and error data.

71. The system of claim 55, wherein the first signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

72. The system of claim 55, wherein the signal processing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

73. The system of claim 55, wherein the response providing means is incorporated into a device selected from the group consisting of a CPU, a processor, a microprocessor, a controller, a micro-controller, an ASIC, a DSP, a signal conditioning amplifier, pre-amplifier or filter, a micro-computer, and a computer.

74. The system of claim 55, wherein the response providing means comprises a device selected from the group consisting of a reinforcement learning processor, a neural network processor, an adaptive fuzzy logic processor, an adaptive processor, and an adaptive fuzzy inferencing processor.

75. The system of claim 55, further comprising storage means for storing patient blood insulin levels.

76. The system of claim 55, further comprising storage means for storing patient glucose levels.

77. The system of claim 55, wherein said response providing means further comprises extrapolation means for extrapolating anticipated time of insulin need as a function of said stored patient blood insulin levels.

78. The system of claim 55, further comprising means for processing said ECG signals and obtaining therefrom an indication of patient blood glucose.

79. The system of claim 55, wherein said response providing means further comprises delivery means for delivering insulin to the patient and control means for controlling said delivery means to provide indicated insulin in response to indicated patient insulin and glucose levels.

80. The system of claim 55 wherein the patient'"'"'s future blood insulin level is estimated by analyzing the patient'"'"'s ECG time rate of change.

81. The system of claim 80 wherein the patient'"'"'s future blood insulin level improves accuracy in predicting the onset or presence of a hypoglycemic state.

82. A system for determining insulin need of a diabetic patient, comprising

ECG sensing means for sensing the patient'"'"'s ECG and deriving therefrom an indication of patient current blood insulin level,

EEG sensing means for sensing the patient'"'"'s EEG and deriving therefrom an indication of patient future blood glucose level;

processing means for determining at least one of patient insulin need and patient glucose need as a function of said indication of patient current blood insulin level and said indication of patient future blood glucose level, and

response means for outputting an indication of at least one of said determined patient insulin need and said determined blood glucose need that includes both patent current need and patient future need.

83. The system of claim 82, wherein said ECG sensing means comprises first processing means for processing ECG signals and deriving therefrom selected parameter data.

84. The system of claim 83, wherein said ECG sensing means comprises second processing means for determining time variations of selected ECG parameters and for calculating anticipated insulin need as a function of said variations.

85. The system of claim 82, wherein said EEG sensing means comprises first processing means for processing EEG signals and deriving therefrom selected parameter data.

86. The system of claim 85, wherein said EEG sensing means comprises second processing means for determining time variations of selected EEG parameters and for calculating said anticipated insulin need as a function of said variations.

87. The system of claim 82, further comprising external data input means.

88. The system of claim 87, wherein said external data input means comprises time means for storing data representative of the time of patient glucose intake.

89. The system of claim 82, wherein said processing means comprises glucose variation means for calculating anticipated glucose variation as a function of said glucose blood levels, and wherein said response means comprises comparing means for comparing anticipated glucose variation with measured patient insulin level.

90. The system of claim 82, further comprising storage means for storing patient blood insulin levels.

91. The system of claim 82, wherein said processing means further comprises extrapolation means for extrapolating anticipated time of insulin need as a function of said stored patient blood insulin levels.

92. The system of claim 82, further comprising delivery means for delivering a insulin to the patient, and control means for controlling said delivery means to provide indicated insulin in response to indicated patient insulin and glucose.

93. The system of claim 82 wherein the patient'"'"'s future blood insulin level is estimated by analyzing the patient'"'"'s ECG time rate of change.

94. The system of claim 93 wherein the patient'"'"'s future blood insulin level improves accuracy in predicting the onset or presence of a hypoglycemic state.