Method and system for processing data from ambulatory physiological monitoring

• US 20050240087A1
• Filed: 11/18/2004
• Published: 10/27/2005
• Est. Priority Date: 11/18/2003
• Status: Active Grant

• Current Assignee: Adidas AG
• Original Assignee: VivoMetrics, Inc.
• Inventors: Coyle, Michael, Keenan, Desmond B.
• Granted Patent: US 8,137,270 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• 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 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence
• CPC Class Codes: A61B 5/0806 by whole-body plethysmography measuring blood flow using plethysmography A61B5/0295; impedance plethysmography A61B5/053; measuring volume of the body or parts thereof A61B5/1073
• CPC Class Codes: A61B 5/085 Measuring impedance of respiratory organs or lung elasticity
• CPC Class Codes: A61B 5/1073 Measuring volume, e.g. of limbs
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4803 Speech analysis specially adapted for diagnostic purposes
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence

Abstract

This invention provides methods and systems for the analysis of data returned from monitoring multiple physiological parameters of a subject, especially from ambulatory multiple parameter monitoring. The methods and systems remove motion artifacts from signals and separate multiple components of single signals due to two or more physiological systems or processes. Each output signal is are preferably free from motion artifacts and reflects primarily functioning of only a single physiological system or process.

Claims

1. A method for processing sensor signals arising from a plurality of sensors sensitive to a plurality of pbysiological systems or processes of a monitored subject, said method comprising:

adaptively enhancing desired physiological components relative to undesired artifact components in one or more sensor signals monitored from said subject during periods comprising unconstrained activity; and

adaptively enhancing components sensitive to desired physiological systems or processes relative to components sensitive to other undesired physiological systems or processes in one or more of the sensor signals that have adaptively enhanced physiological components.

2. The method of claim 1 wherein said monitoring further comprises retrieving one or more sensor signals from a wearable construction comprising one or more sensors.

3. The method of claim 2 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

4. The method of claim 2 wherein said wearable construction further comprises one or more inductive plethysmographic sensors.

5. The method of claim 1 wherein said activities comprise one or more of standing, or walking, or running, or climbing, or sitting, or lying, or sleeping.

6. The method of claim 1 wherein said activities comprise normal daily activities of said subject.

7. The method of claim 1 wherein said activities are unconstrained by said monitoring.

8. The method of claim 1 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

9. The method of claim 1 wherein said physiological systems or processes comprise one or more of respiratory activity, or cardiac mechanical activity, or cardiac electrical activity, or electroencephalographic activity, or motion activity.

10. The method of claim 1 wherein said physiological systems or processes comprise one or more of temperature activity, or blood saturation activity, or vocal activity, or electro-oculogram activity, or electro-myogram activity.

11. The method of claim 1 wherein said sensor signals comprise size sensor signals sensitive to a rib cage size, or to a mid-thorax size, or to an abdominal size, or to an extremity size.

12. The method of claim 1 wherein said artifact components comprise motion artifacts arising from subject activity.

13. The method of claim 1 wherein said artifact components comprise electromagnetic interference artifacts.

14. The method of claim 1 wherein said desired physiological systems or processes comprise cardiac pulsation activity and said undesired physiological systems or processes comprise respiratory activity.

15. The method of claim 1 wherein said desired physiological systems or processes comprise electroencephalographic activity and said undesired physiological systems or processes comprise respiratory activity.

16. The method of claim 1 wherein said steps of adaptively enhancing further comprise joint processing of two or more sensor signals sampled and/or re-sampled at a single common sampling rate.

17. The method of claim 1 wherein said steps of adaptively enhancing further comprise re-sampling one or more sensor signals to a common sampling rate.

18. The method of claim 1 wherein said adaptively enhancing components in sensor signals further comprises processing said sensor signals jointly with one or more reference sensor signals, wherein said sensor signals and said reference sensor signals are sampled and/or re-sampled at a single common sampling rate.

19. The method of claim 18 wherein said one or more reference signals comprise signals sensitive to subject motion activity.

20. The method of claim 18 wherein said one or more reference signals sensitive to said undesired physiological systems or processes.

21. The method of claim 1 wherein said reference sensor signals comprise components correlating with said undesired components in said sensor signals, and said sensor signals and said reference signals being sampled and/or re-sampled at a single common sampling rate.

22. The method of claim 21 further comprising re-sampling one or more sensor signals at a single common sampling rate.

23. The method of claim 21 wherein said adaptively enhancing further comprises reducing an error signal, said error signal being a difference between said processed sensor signals and said processed reference sensor signals.

24. The method of claim 21 wherein said adaptively enhancing comprises adjusting weights of a finite impulse response filter by a least means squares technique.

25. The method of claim 21 wherein said adaptively enhancing desired physiological components comprises joint processing with one or more reference signals sensitive to subject motion activity.

26. The method of claim 21 wherein said adaptively enhancing components sensitive to said desired physiological systems or processes comprises joint processing with one or more reference signals sensitive to said undesired other physiological systems or processes.

27. The method of claim 1 wherein said adaptively enhancing components sensitive to desired physiological components or processes in one or more sensor signals further comprises generating additional signals in which are enhanced components sensitive to said other undesired physiological systems or processes, whereby said desired and said undesired physiological components are enhanced in separate output signals.

28. The method of claim 1

wherein said sensor signals comprise electrocardiograph (ECG) signals and said reference signals comprise respiratory signals,

wherein said adaptively enhancing enhances respiratory components in a heart rate (HR) signal derived from said ECG signal, said enhanced signal comprising a high frequency heart rate variability (HF HRV) signal, and

further comprising generating a low frequency heart rate variability (LF HRV) signal comprising components in said HR signal other than said enhanced respiratory components.

29. The method of claim 28 further comprising estimating one or more corrected QT intervals independence on QT intervals measured in said ECG signal and on said LF HRV signal.

30. A system for processing physiological sensor signal data comprising:

a wearable construction comprising one or more sensors sensitive to one or more physiological systems or processes including motion activity; and

computer memory comprising computer instructions to

retrieve a plurality of physiological sensor signals from said wearable construction when worn by a monitored subject during periods comprising unconstrained activities, said retrieved sensor signals comprising reference signals sensitive to subject motion activity; and

enhance desired physiological components relative to undesired motion artifact components in one or more retrieved sensor signals, said enhancing comprising adaptively processing said sensor signals jointly with one or more of said reference signals in order to reduce an error signal.

31. The system of claim 30 wherein said activities comprise normal daily activities of said subject.

32. The system of claim 30 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

33. The system of claim 30 where said reference sensors comprise one or more accelerometers.

34. The system of claim 30 wherein said sensor signals and said reference signals are sampled and/or re-sampled at a single common sampling rate.

35. The system of claim 30 further comprising re-sampling one or more sensor signals at a single common sampling rate.

36. The system of claim 30 further comprising de-trending one or more of said sensor signals and/or said reference signals.

37. The system of claim 30 wherein said desired physiological systems of processes comprise respiratory activity, or cardiac activity, or electroencephalographic activity.

38. The system of claim 30 wherein said error signal is a difference between processed retrieved sensor signals and processed reference sensor signals.

39. The system of claim 30 wherein said reducing said error signal further comprises adjusting weights of a finite impulse response filter by a least means squares technique.

40. The system of claim 30 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

41. The system of claim 30 wherein said retrieved sensor signals are adaptively processed to enhance desired components relative to artifact components.

42. A system for processing physiological sensor signal data comprising:

a wearable construction comprising one or more sensors sensitive to physiological systems or processes comprising cardiac pulsation activity and respiratory activity; and

computer memory comprising computer instructions to

retrieve sensor signals from said wearable construction when worn by a monitored subject during periods comprising unconstrained activities, said retrieved sensor signals comprising cardiac signals with cardiac pulsation components and respiratory signals with respiratory activity components; and

enhance desired cardiac components relative to undesired respiratory components in said cardiac signals, said enhancing comprising adaptively processing said cardiac signals jointly with said respiratory signals in order to reduce an error signal.

43. The system of claim 42 wherein said activities comprise normal daily activities of said subject.

44. The system of claim 42 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

45. The system of claim 42 wherein said cardiac signals comprise cardiac pulsation components and respiratory activity components with relative amplitudes larger than relative amplitudes of cardiac pulsation components and respiratory activity components in said respiratory signals.

46. The system of claim 42 wherein said sensor signals are sampled and/or re-sampled at a single common sampling rate.

47. The system of claim 42 further comprising re-sampling one or more sensor signals at a single common sampling rate.

48. The system of claim 42 wherein said error signal is a difference between processed cardiac signals and processed respiratory signals.

49. The system of claim 42 wherein said reducing said error signal further comprises adjusting weights of a finite impulse response filter by a least means squares technique.

50. The system of claim 42 wherein said processors further time domain filter said enhanced cardiac signals.

51. The system of claim 50 wherein said time domain filtering comprises ensemble averaging timed by electrocardiographic R waves.

52. The system of claim 51 wherein a value of said ensemble averaged signal at a current time sample comprises an average of a current value of said cardiac signal and of values of said cardiac signal at one or more prior time samples, all averaged samples having the same relative position in the cardiac cycle.

53. The system of claim 52 wherein said relative position in the cardiac cycle is determined from R-R intervals.

54. The system of claim 42 wherein said instructions further determine an R-R interval signal by:

detecting R waves in an electrocardiogram signal sensitive to cardiac electrical activity;

discarding detected R waves that occur in an ectopic temporal location; and

determining said R-R interval signal from said detected and interpolated R waves,

55. The system of claim 42 wherein said sensors comprise at least one size sensor for monitoring respiratory signals and at least one size sensor at a pre-cordial mid-thorax level for monitoring cardiac pulsation signals.

56. The system of claim 55 wherein said size sensors comprise at least one inductive plethysmographic sensor.

57. The system of claim 42 wherein said instructions further extract one or more indicia of cardiac functioning from said enhanced cardiac signal.

58. The system of claim 57 wherein said indicia of cardiac functioning comprise stroke volume, or cardiac output, or pre-ejection period, or peak ejection rate, or time to peak ejection rate.

59. The system of claim 42 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

60. The system of claim 42 wherein said retrieved sensor signals are adaptively processed to enhance desired components relative to artifact components.

61. A system for processing physiological sensor signal data comprising:

a wearable construction comprising one or more sensors sensitive to physiological systems or processes comprising electroencephalographic (EEG) activity and respiratory activity; and

computer memory comprising computer instructions to

retrieve sensor signals from said wearable construction when worn by a monitored subject during periods comprising unconstrained activities, said retrieved sensor signals comprising EEG signals and respiratory signals;

estimate respiratory components in said EEG signal by adaptively processing said EEG signals jointly with said respiratory signals in order to reduce an error signal; and

enhance desired EEG components relative to undesired respiratory components in said EEG signals in dependence on said estimated respiratory components.

62. The system of claim 61 wherein said activities comprise normal daily activities of said subject.

63. The system of claim 61 wherein said joint processing comprises low pass filtering said EEG signals using a low pass filter that passes at least those frequencies in the range of frequencies present in respiratory signals.

64. The system of claim 61 wherein said error signal is a difference between processed EEG signals and processed respiratory signals.

65. The system of claim 61 wherein said reducing said error signal further comprises adjusting weights of a finite impulse response filter by a least means squares technique.

66. The system of claim 61 wherein said enhancing comprises removing said estimated respiratory components from said retrieved and unprocessed EEG signal.

67. The system of claim 66 wherein said removing comprises subtraction.

68. The system of claim 61 wherein said sensor signals are sampled and/or re-sampled at a single common sampling rate.

69. The system of claim 61 further comprising re-sampling one or more sensor signals at a single common sampling rate.

70. The system of claim 61 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

71. The system of claim 61 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

72. The system of claim 61 wherein said retrieved sensor signals are adaptively processed to enhance desired components relative to artifact components.

73. A system for processing physiological sensor signal data comprising:

a wearable construction comprising one or more sensors sensitive to physiological systems or processes comprising electrocardiographic (ECG) activity and respiratory activity; and

computer memory comprising computer instructions to

retrieve sensor signals from said wearable construction when worn by a monitored subject during periods comprising unconstrained activities, said retrieved sensor signals comprising ECG signals and respiratory signals;

generate an RR interval signal from said ECG signal comprising data describing successive intervals between successive R-waves; and

estimate respiratory components in said ECG signal by adaptively processing said ECG signals jointly with said respiratory signals in order to reduce an error signal, wherein a high frequency heart rate variability (HF HRV) signal comprises said estimated respiratory components, a low frequency heart rate variability (LF HRV) signal comprises said error signal.

74. The system of claim 73 wherein said instructions further de-trend said HF HRV signal and de-trend said LF HRV signal.

75. The system of claim 73 wherein said instructions further de-trend said HF HRV and de-trend said RR interval signal prior to said estimating.

76. The system of claim 73 wherein said instructions further spectrally analyze said LF HRV signal.

77. The system of claim 73 wherein said instructions further spectrally analyze said HF HRV signal.

78. The system of claim 73 wherein said respiratory signal comprises a tidal volume (Vt) signal.

79. The system of claim 78 wherein said retrieved respiratory signals comprise at least one signal from a size sensor at a rib cage (RC) level and at least one signal from a size sensor at an abdominal (AB) level, and

wherein said instructions further determine said Vt signal by combining said RC signal and said AB signal.

80. The system of claim 73 wherein the instructions further low pass filter said respiratory signal using a low pass filter that passes at least those frequencies in the range of frequencies normally present in respiratory signals.

81. The system of claim 80 where said low pass filter passes signals less than approximately 1.5 Hz.

82. The system of claim 73 wherein said EEG signals and said respiratory signals are sampled and/or re-sampled at a single common sampling rate.

83. The system of claim 73 further comprising re-sampling one or more of said EEG signals and said respiratory signals at a single common sampling rate.

84. The system of claim 73 wherein said error signal is a difference between said processed ECG signals and said processed respiratory signals.

85. The system of claim 73 wherein said reducing said error signal further comprises adjusting weights of a finite impulse response filter by a least means squares technique.

86. The system of claim 73 wherein said activities comprise normal daily activities of said subject.

87. The system of claim 73 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

88. The system of claim 73 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

89. The system of claim 73 wherein said instructions further determine an R-R interval signal by:

detecting R waves in an electrocardiogram signal sensitive to cardiac electrical activity;

discarding detected R waves that occur in an ectopic temporal location;

determining said R-R interval signal.

90. The method claim 89 wherein said discarding further comprises interpolating a constructed R wave at the expected temporal position of a discarded ectopic R wave.

91. The system of claim 73 wherein said retrieved sensor signals are adaptively processed to enhance desired components relative to artifact components.

92. A system for processing physiological sensor signal data comprising:

a wearable construction comprising one or more sensors sensitive to physiological systems or processes comprising electrocardiographic (ECG) activity and respiratory activity; and

computer memory comprising computer instructions to

retrieve sensor signals from said wearable construction when worn by a monitored subject during periods comprising unconstrained activities, said retrieved sensor signals comprising ECG signals and respiratory signals;

generate an RR interval signal from said ECG signal comprising data describing intervals between successive R-waves;

estimate respiratory components in said ECG signal by adaptively processing said ECG signals jointly with said respiratory signals in order to reduce an error signal, wherein a low frequency heart rate variability (LF HRV) signal comprises said error signal; and

estimate one or more corrected QT intervals independence on QT intervals measured in said ECG signal and on said LF HRV signal.

93. The system of claim 92 wherein said respiratory signal comprises a tidal volume (Vt) signal.

94. The system of claim 92 wherein said EEG signals and said respiratory signals are sampled and/or re-sampled at a single common sampling rate.

95. The system of claim 92 further comprising re-sampling one or more of said EEG signals and said respiratory signals at a single common sampling rate.

96. The system of claim 92 wherein said error signal is a difference between said processed ECG signals and said processed respiratory signals.

97. The system of claim 92 wherein said reducing said error signal further comprises adjusting weights of a finite impulse response filter by a least means squares technique.

98. The system of claim 92 wherein said activities comprise normal daily activities of said subject.

99. The system of claim 92 wherein said wearable construction comprises a band for encircling a body part, or a garment for all or part of the trunk, or a garment for all or part of the trunk and all or part of one or more extremities, or two or more of said bands or said garments.

100. The system of claim 92 wherein the functioning of one or more physiological systems or processes varies during subject activity, and wherein sensor signals sensitive to said varying physiological systems or processes have varying signal characteristics.

101. The system of claim 92 wherein said instructions further determine an R-R interval signal by:

detecting R waves in an electrocardiogram signal sensitive to cardiac electrical activity;

discarding detected R waves that occur in an ectopic temporal location; and

determining said R-R interval signal from said detected and interpolated R waves.

103. The system of claim 92 wherein said corrected QT intervals are estimated using a formula substantially similar to:

104. The system of claim 92 wherein said corrected QT intervals are estimated using a formula substantially similar to:

QT_LC=Qt+0.154 (1−

RR)

105. The system of claim 92 wherein said retrieved sensor signals are adaptively processed to enhance desired components relative to artifact components.

102. The method claim 102 wherein said discarding further comprises interpolating a constructed R wave at the expected temporal position of a discarded ectopic R wave.

106. A computer memory comprising computer instructions for processing sensor signals arising from a plurality of sensors sensitive to a plurality of physiological systems or processes of a monitored subject, by performing:

adaptively enhancing desired physiological components relative to undesired artifact components in one or more sensor signals monitored from said subject during periods comprising unconstrained activity; and

adaptively enhancing components sensitive to desired physiological systems or processes relative to components sensitive to other undesired physiological systems or processes in one or more of the sensor signals that have adaptively enhanced physiological components.

107. The computer memory of claim 107 further comprising one or more CD-ROMS.

108. The computer memory of claim 107 further one or more memories accessible to one or more processors.