Methods and systems for analysis of physiological signals

• US 20040249299A1
• Filed: 06/06/2003
• Published: 12/09/2004
• Est. Priority Date: 06/06/2003
• Status: Abandoned Application

• Current Assignee: VivoMetrics, Inc.
• Original Assignee: VivoMetrics, Inc.
• Inventors: Cobb, Jeffrey Lane
• Application Number:
  US10/457,097
• Publication Number:
  US 20040249299A1
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/353 Detecting P-waves
• CPC Class Codes: A61B 5/355 Detecting T-waves
• CPC Class Codes: A61B 5/4818 Sleep apnoea

Abstract

Systems and methods are provided for processing and analyzing signals reflecting, physiologic processes and events in a monitored subject, especially cardio-pulmonary signals. The input signals are analyzed by in a physiological domain by creating structured data representing the physiological events reflected in the signals. Preferably, first, primitive event objects are created representing physiologically-significant portions of these input signals; second, the primitive event objects are grouped into primary event objects representing actual physiologic processes and events. Next, all objects are stored in databases, and organized in containers for efficient searching. Information may be retrieved by creating view objects which associate physiologic event objects having selected properties specified directly in physiological terms. This invention includes methods for performing the above analysis, systems and program products for carrying out these methods, and databases configured with the stored objects and views.

Claims

1. A computer-readable memory including structured data representing physiological events reflected in input signals from a monitored subject, wherein the structured data comprises:

at least one instance of a data-structure representing characteristics of an elementary-type physiological event, wherein an elementary-type physiological event is defined in dependence on a portion of the input signal, and

at least one instance of a data-structure representing characteristics of a primary-type physiological event, wherein the primary-type event is defined in dependence on one or more elementary-type events.

2. The memory of claim 1 wherein primary-type events are defined in dependence on one or more temporally-contiguous elementary-type events.

3. The memory of claim 1 wherein an elementary-type data-structure instance representing an elementary-type physiological event comprises identification of the portion of the input-signal defining the represented elementary-type event.

4. The memory of claim 1 wherein a primary-type data-structure representing a primary-type physiological event comprises identification of the elementary-type data-structures instances representing the defining elementary-type events.

5. The memory of claim 1 further comprising an instance of a software object that comprises an elementary-type or a primary-type data-structure instance.

6. The memory of claim 1 wherein a primary-type data-structure instance comprises an elementary-type data-structure instance.

7. The memory of claim 1 further comprising at least one instance of a view-type data-structure representing at least one elementary-type or primary-type data-structure instance, the view-type data-structure instance representing one or more physiological events that satisfy a pre-determined physiological criterion.

8. The memory of claim 7 further comprising an instance of a software object that comprises a view-type data-structure instance, the software object being an instance of an object class also comprising a method for accessing the elementary-type or primary-type data-structure instances represented by the view-type data-structure instance.

9. The memory of claim 7 wherein a view-type data-structure represents at least one instance of an event-group data-structure, the event-group data-structure representing one or more temporally contiguous primary-type data-structure instances satisfying the pre-determined physiological criterion.

10. The memory of claim 7 wherein the input signal reflects pulmonary events, and wherein the pre-determined physiological criterion define one or more of a period of apnea, a period of hypopnea, a cough, or a period of Cheyne-Stokes respiration.

11. The memory of claim 1 wherein the input signal reflects pulmonary events, wherein the elementary-type physiological events are breath phases, and wherein the primary-type physiological event are breaths defined by a sequence of breath phases.

12. The memory of claim 11 the breath phases comprise one or more of a begin inspiration phase, or a begin inspiratory flow phase, or a peak inspiratory flow phase, or a peak phase, or a begin expiratory flow phase, or a peak expiratory flow phase, or an end expiration phase.

13. The memory of claim 1 wherein the input signal reflects pulse-oximeter measurement events, and wherein the primary-type physiological events are pulses.

14. The memory of claim 1 wherein the input signal reflects cardiac events, and wherein the elementary-type physiological events are cardiac phases, and wherein the primary-type physiological event are heartbeats defined by a sequence of cardiac phases.

15. The memory of claim 14 wherein the cardiac phases comprise depolarization phases, or repolarization phases, or ECG P-wave phases, or ECG QRS-complex phases, or ECG T-wave phases, or diastole phases, or systole phases.

16. The memory of claim 14 wherein the primary-type data-structures comprise indicia of ventricular volume.

17. The memory of claim 1 part of all of which is included in a RAM storage medium of a computer system or a permanent storage medium of a computer system.

18. The memory of claim 1 part or all of which is included in a removable storage medium that can be transported between computer systems.

19. The memory of claim 1 further comprising data representing the input signals.

20. The memory of claim 1 wherein the physiological events are generated by a respiratory process, or a cardiac process, or a pulse oximetry process, or a capnometery process, or an electroencephalographic process, or an electrooculographic process, or a electromyographic process, or a sound microphone signal process, or a body temperature signal process, or an accelerometer signal process, or a blood glucose concentration signal process.

70. A computer-implemented method for creating view-type data structures comprising:

in a computer-readable memory structured according to claim 1, searching part or all of the data-structure instances for data-structure instances that satisfy a pre-determined physiological criterion, and

creating at least one instance of a view-type data-structure representing at least one data-structure instance found in search.

71. The computer-implemented method of claim 70 further comprising accessing the data-structure instances represented by at least one created view-type data-structure instance.

72. The computer-implemented method of claim 70 wherein the physiological criterion specifies characteristics of individual data-structure instances.

73. The computer-implemented method of claim 70 wherein the physiological criterion specifies a pattern comprising a plurality of data-structure instances with pre-determined characteristics and relative order.

21. A computer-readable memory including structured data representing physiological events generated by at least a first and a second physiological process, the physiological events being reflected in input signals from a monitored subject, wherein the structured data comprises:

at least one instance of a data-structure representing characteristics of a primary-type physiological event generated by the first process that is defined in dependence on one or more corresponding elementary-type physiological events, wherein the elementary-type events are defined in dependence on portions of the input signal,

at least one instance of a data-structure representing characteristics of a primary-type physiological event generated by the second process that is defined in dependence on one or more elementary-type physiological events, wherein the elementary-type events are defined in dependence on portions of the input signal,

wherein at least one primary-type data-structure instance comprises data identifying at least one other primary-type data-structure instance, the primary-type data-structure instances representing primary-type events of the first and second processes that are physiologically associated.

22. The memory of claim 21 wherein the first and second physiological processes are a respiratory process, or a cardiac process, or a pulse oximetry process, or a capnometery process, or an electroencephalographic process, or an electrooculographic process, or a electromyographic process, or a sound microphone signal process, or a body temperature signal process, or an accelerometer signal process, or a blood glucose concentration signal process, or a blood pressure process, or a blood flow process.

23. The memory of claim 21 further comprising at least one instance of a view-type data-structure representing

(i) one or more primary-type data-structure instances representing events generated by one of the physiological processes that satisfy a pre-determined physiological criterion, and

(ii) one or more primary-type data-structure instances representing events generated by the other of the physiological processes that are physiologically associated with the represented primary-type data-structures.

24. The memory of claim 21 further comprising at least one instance of a first-process primary-type data-structure that comprises identification of at least one further data-structure instance representing characteristics of a first-process elementary-type physiological event.

25. The memory of claim 24 further comprising at least one instance of a second-process primary-type data-structure that comprises identification of at least one further data-structure instance representing characteristics of a second-process elementary-type physiological event.

26. The memory of claim 21 wherein the data-structure instances of the first and second physiological processes are physiologically associated if the represented events have overlapping occurrence times.

27. The memory of claim 26 wherein the primary-type data-structures represent heartbeats and breaths.

28. The memory of claim 26 wherein the primary-type data-structures represent respiratory events, or cardiac events, or arterial pulse events, or capnometery process events, or electroencephalographic process events, or electrooculographic process events, or electromyographic process events, or sound microphone signal process events, or body temperature events, or accelerometer signal events, or blood glucose concentration events, or blood pressure events, or blood flow events.

29. The memory of claim 21 wherein the data-structure instances of the first and second physiological processes are associated if the represented events have occurrence times displaced by a determined amount.

30. The memory of claim 29 wherein the primary-type data-structures represent heartbeats and arterial pulses, and wherein the determined time displacement is a transit time of blood from the heart to the measured artery.

31. The memory of claim 29 wherein the primary-type data-structures represent breaths and arterial pulses, and wherein the determined time displacement is a transit time of blood from the lungs to the measured artery.

32. The memory of claim 29 wherein the primary-type data-structures represent heartbeats and breaths, and wherein the determined time displacement is an anxiety reaction time.

33. The memory of claim 21 wherein the data-structure instances of the first and second physiological processes are physiologically associated if the represented events have a cause-and-effect relationship.

34. The memory of claim 21 wherein the data-structure instances of the first and second physiological processes are manually associated by a user.

35. A computer-implemented method for analyzing input signals from a monitored subject, the input signals reflecting physiological events in the subject, the method comprising:

recognizing at least one elementary-type physiological event in dependence on a portion of the input signal,

creating at least one instance of an elementary-type data-structure representing characteristics of the elementary-type event,

recognizing at least one primary-type of physiological event from one or more contiguous elementary-type events, and

creating at least one instance of a primary-type data-structure representing characteristics of a primary-type event.

36. The computer-implemented method of claim 35 wherein the physiological process is a respiratory process, or a cardiac process, or a pulse oximetry process, or a capnometery process, or an electroencephalographic process, or an electrooculographic process, or a electromyographic process, or a sound microphone signal process, or a body temperature signal process, or an accelerometer signal process, or a blood glucose concentration signal process or a blood pressure process, or a blood flow process.

37. The computer-implemented method of claim 35 wherein the input-signal characteristics comprise a maximum value of a portion of the signal, or a minimum value of a portion of the signal, or a maximum value of the time derivative of a portion of the signal, or a minimum value of the time derivative of a portion of the signal.

38. The computer-implemented method of claim 35 wherein an elementary-type physiological event is recognized as a sequence of input-signal characteristics.

39. The computer-implemented method of claim 35 wherein the recognition of elementary-type and primary-type events proceeds concurrently, and wherein the recognition of a next elementary-type event further proceeds in dependence on a partially-completed recognition of a current primary-type event.

40. The computer-implemented method of claim 35 wherein the recognition of a primary-type event proceeds in dependence on a pattern of elementary-type events, the pattern comprising specification of elementary-type events with pre-determined characteristics and order.

41. The computer-implemented method of claim 40 wherein the recognition of elementary-type and primary-type events proceeds concurrently, and wherein the recognition of a next elementary-type event further proceeds in dependence on at least one expected next elementary-type event that is determined by the pattern for the partially-recognized current primary-type event.

42. The computer-implemented method of claim 40 wherein the pattern of elementary-type events is specified by a regular expression.

43. The computer-implemented method of claim 40 wherein the pattern of elementary-type events is recognized by a finite state machine.

44. The computer-implemented method of claim 35 wherein creation of an elementary-type data-structure comprises providing identification of the portion of the input-signal defining the represented elementary-type event.

45. The computer-implemented method of claim 35 wherein creation of a primary-type data-structure comprises providing identification of the elementary-type data-structure instances representing the defining elementary-type events.

46. The computer-implemented method of claim 35 further comprising:

searching part or all of the created data-structure instances for one or more data-structure instances that satisfy a pre-determined physiological criterion, and

creating at least one instance of a view-type data-structure representing at least one data-structure instance found in search.

47. The computer-implemented method of claim 46 wherein the pre-determined physiological criterion comprises a pattern specifying data-structure instances with pre-determined characteristics and order.

48. The computer-implemented method of claim 47 wherein the pattern is recognized by a finite state machine.

49. The computer-implemented method of claim 46 wherein the pre-determined physiological criterion defines one or more of a period of apnea, a period of hypopnea, a cough, or a period of Cheyne-Stokes respiration.

74. A computer system comprising:

a processor, and

a memory operatively coupled to the processor, wherein the memory comprises executable instructions for causing the processor to perform the method of claim 35 for analyzing input signals from a monitored subject.

75. The computer system of claim 74 further comprising user interface equipment.

76. The computer system of claim 74 further comprising communication equipment for the receiving input signals.

77. The computer system of claim 76 wherein the communication equipment comprises Internet access devices.

78. The computer system of claim 74 further comprising equipment for reading the input signals from a removable computer-readable media.

79. The computer system of claim 78 wherein the removable computer-readable media include memory cards.

80. The computer system of claim 74 wherein the memory further comprises executable instruction for causing the computer to perform the method of claim 46 for creating view-type data structures.

82. A program product comprising a computer readable medium having instructions for causing a computer to execute the method of claim 35 for analyzing input signals from a monitored subject.

50. A computer-implemented method for analyzing input signals from a monitored subject, the input signals reflecting physiological events in the subject generated by at least a first and a second physiological process, the method comprising:

recognizing at least one primary-type physiological event of the first process defined in dependence on one or more corresponding elementary-type physiological events, wherein the elementary-type events are defined in dependence on portions of the input signal,

creating at least one instance of a first-process data-structure representing characteristics of the recognized primary-type event

recognizing at least one primary-type physiological event of the second process defined in dependence on one or more corresponding elementary-type physiological events, wherein the elementary-type events are defined in dependence on portions of the input signal,

creating at least one instance of a second-process data-structure representing characteristics of the recognized primary-type event

wherein at least one primary-type data-structure instance comprises data identifying at least one other primary-type data-structure instance, the primary-type data-structure instances representing primary-type events of the first and second processes that are physiologically associated.

51. The computer-implemented method of claim 50 wherein the first and second physiological processes comprise a respiratory process, or a cardiac process, or a pulse oximetry process, or a capnometery process, or an electroencephalographic process, or an electrooculographic process, or a electromyographic process, or a sound microphone signal process, or a body temperature signal process, or an accelerometer signal process, or a blood glucose concentration signal process, or a blood pressure process, or a blood flow process.

52. The computer-implemented method of claim 50 wherein the physiological processes comprise a breath process, wherein primary-type physiological event are breaths and the elementary-type physiological events are breath phases.

53. The computer-implemented method of claim 52 wherein the breath phases comprise one or more of a begin inspiration phase, or a begin inspiratory flow phase, or a peak inspiratory flow phase, or a peak phase, or a begin expiratory flow phase, or a peak expiratory flow phase, or an end expiration phase.

54. The computer-implemented method of claim 50 wherein the physiological processes comprise a cardiac process, wherein the primary-type physiological event are heartbeats and the elementary-type physiological events are cardiac phases

55. The memory of claim 54 wherein the cardiac phases comprise a depolarization phase, or a repolarization phase, or an ECG P-wave phase, or an ECG QRS-complex phase, or an ECG T-wave phase, or a diastole phases or a systole phases.

56. The memory of claim 54 wherein the primary-type data-structures comprise indicia of ventricular volume or of ventricular wall motion.

57. The computer-implemented method of claim 50 further comprising:

searching part or all of the created data-structure instances for one or more data-structure instances that satisfy a pre-determined physiological criterion, and

creating at least one instance of a view-type data-structure representing at least one data-structure instance found in search.

58. The computer-implemented method of claim 57 wherein the pre-determined physiological criterion comprises specification of a pattern comprising data-structure instances.

59. The computer-implemented method of claim 50 further comprising:

searching part or all of the created data-structure instances for instances representing events generated by one of the physiological processes that satisfy a pre-determined physiological criterion, and

creating at least one instance of a view-type data-structure representing

(i) at least one data-structure instance found in search, and

(ii) at least one data-structure instance representing an event generated by the other of the physiological processes that is physiologically associated with the instances of (i).

60. The computer-implemented method of claim 59 wherein the data-structure instances of the first and second physiological processes are physiologically associated if the represented events have overlapping occurrence times.

61. The computer-implemented method of claim 60 wherein the primary-type data-structures represent heartbeats and breaths.

62. The computer-implemented method of claim 59 wherein the primary-type data-structures represent respiratory events, or cardiac events, or arterial pulse events, or capnometery process events, or electroencephalographic process events, or electrooculographic process events, or electromyographic process events, or sound microphone signal process events, or body temperature events, or accelerometer signal events, or blood glucose concentration events, or blood pressure events, or blood flow events.

63. The computer-implemented memory of claim 59 wherein the data-structure instances of the first and second physiological processes are associated if the represented events have occurrence times displaced by a determined amount.

64. The computer-implemented memory of claim 59 wherein the data-structure instances of the first and second physiological processes are physiologically associated if the represented events have a cause-and-effect relationship.

65. The computer-implemented method of claim 59 wherein the data-structure instances of the first and second physiological processes are manually associated by a user.

66. The computer-implemented method of claim 59 wherein the primary-type data-structures represent heartbeats and breaths, and wherein heartbeats and breaths are physiologically associated if their occurrence times overlap.

67. The computer-implemented method of claim 59 the primary-type data-structures represent heartbeats and arterial pulses, and wherein arterial pulses and heartbeats are physiologically associated if the arterial pulses result from the heartbeats.

68. The computer-implemented method of claim 59 wherein the primary-type data-structures represent breaths and arterial pulses, and wherein breaths and arterial pulses are physiologically associated if the oxygen saturation of the arterial pulses results from the breaths.

69. The computer-implemented method of claim 59 wherein the primary-type data-structures represent heartbeats and breaths, and wherein heartbeats and breaths are physiologically associated if the heartbeats are temporally displaced from the breaths by a displacement interval characteristic of an anxiety reaction.

81. A computer system comprising:

a processor, and

a memory operatively coupled to the processor, wherein the memory comprises executable instructions for causing the processor to perform the method of claim 50 for analyzing input signals from a monitored subject.

83. A program product comprising a computer readable medium having instructions for causing a computer to execute the method of claim 50 for analyzing input signals from a monitored subject.