Method and device for analyzing a periodic or semi-periodic signal

• US 20030208129A1
• Filed: 06/25/2002
• Published: 11/06/2003
• Est. Priority Date: 12/29/1999
• Status: Active Grant

• Current Assignee: Bsp Biological Signal Processing Ltd.
• Original Assignee: Bsp Biological Signal Processing Ltd.
• Inventors: Beker, Amir, Ben David, Tamir, Hasson, Assaf
• Granted Patent: US 7,151,957 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening

Abstract

A device for reducing noise in signals having successive substantially repetitive portions, comprising: an iterative averager operative to superimpose and average said substantially repetitive portions to produce a running average thereof, and an iteration ender comprising a noise analyzer for determining a noise level in said running average and ending operation of said iterative averager when said noise level reaches a predetermined level. Also, a method of obtaining an indication of ischemia in a patient using an ECG signal therefrom, the method comprising: extracting an ECG signal over a duration, extracting from said ECG signal a series of QRS complexes over said duration, extracting high frequency components of said QRS complexes, analyzing said high frequency components over said duration for at least one of a predetermined quality, and inferring from said predetermined quality an indication of ischemia.

Claims

1. A device for reducing noise in signals having successive substantially repetitive portions, comprising:

an iterative averager operative to superimpose and average said substantially repetitive portions to produce a running average thereof,

and an iteration ender comprising a noise analyzer for determining a noise level in said running average and ending operation of said iterative averager when said noise level reaches a predetermined level.

2. A device for reducing noise in signals according to claim 1, wherein said iterative averager is operative to take said successive portions in successive iterative steps.

3. A device for reducing noise in signals according to claim 1, further comprising an aligner for aligning at least some of said substantially repetitive portions one with another, wherein said signal comprises first frequency and second frequency components and said aligner comprises a first frequency correlated band pass filter and a second frequency correlated band pass filter to extract respective first and second frequency components, thereby to use said first frequency components to locate an alignment point in successive portions and to use said alignment point to align said second frequency components.

4. A device for reducing noise in signals according to claim 1, wherein said iteration ender is further operative to end said operation of said iterative averager when said repetitive portions are exhausted.

5. A device for reducing noise in signals according to claim 1, wherein said iteration ender is further operative to end said operation of said iterative averager when said running average reaches a preset maximum of included repetitive portions.

6. A device for reducing noise in signals according to claim 1, further comprising a repetitive portion selector for selecting repetitive portions for passing to said iterative averager, the repetitive portion selector comprising

a reference portion store for storing a reference portion,

a cross correlator for computing a cross correlation between a current repetitive portion and said reference portion, and

a comparator for comparing a result of said cross-correlation with a predetermined threshold to produce a comparison output,

and wherein said selector is operable to pass said current repetitive portion to said iterative averager in accordance with said comparison output.

7. A device for reducing noise in signals according to claim 6, further comprising a reference portion determination unit associated with said repetitive portion selector, operable to determine as a reference portion any one of a group comprising a first repetitive portion of a current length of said signal, a final result of a running average of a previous set of iterations and a prior determined typical wave.

8. A device for reducing noise in signals according to claim 7, wherein said reference portion determination unit is operable to dynamically change between members of said group over the course of a set of iterations.

9. A device for reducing noise in signals according to claim 7, wherein said reference portion determination unit further comprises a reference portion updater for dynamically updating said reference portion during the course of a set of iterations.

10. A device for reducing noise in signals according to claim 6, comprising a reference portion determiner, said reference portion determiner comprising,

a first store for storing a first set of repetitive portions from said signal,

a second store for storing a second set of repetitive portions from said signal,

a cross correlator for cross-correlating repetitive portions from said second set in turn with repetitive portions from said first set to produce a plurality of cross-correlation results for respective repetitive portions in said second set,

and a reference selector for selecting one of said repetitive portions in said second set as a reference portion in accordance with its respective cross-correlation results.

11. A device for noise reduction in a signal according to claim 10, wherein said reference selector comprises a threshold level comparator for comparing each cross-correlation result with a threshold and which is operable to select as said reference portion a repetitive portion having a highest number of respective cross-correlation results exceeding said threshold.

12. A device for noise reduction according to claim 10, wherein said reference selector comprises a summation unit for summing cross-correlation results of respective repetitive portions and which reference selector is operable to select as a reference portion a repetitive portion having the highest sum of respective cross-correlation results.

13. A device for noise reduction according to claim 10, wherein said reference selector comprises:

a threshold level comparator for comparing each cross-correlation result with a threshold, and

a summation unit for summing cross-correlation results of respective repetitive portions exceeding said threshold,

and which reference selector is operable to select as a reference portion a repetitive portion having a highest sum of respective cross-correlation results.

14. A device for noise reduction in a signal according to claim 1, further comprising a signal extractor for extracting said repetitive portion.

15. A device for noise reduction in a signal according to claim 14 comprising an RMS computation unit for calculation of the energy level of segments of wave obtained by averaging a series of said repetitive portions.

16. A device for noise reduction in a signal according to claim 15, further comprising an RMS value analysis unit for detecting a falloff in said RMS energy value over succeeding averages.

17. A device for noise reduction in a signal according to claim 14, comprising a cross-correlation unit for computing the cross correlation coefficient of an average of a series of said repetitive portions and a reference wave.

18. A device for noise reduction in a signal according to claim 17, further comprising a cross-correlation value analysis unit for detecting a falloff in said cross-correlation value over succeeding averages.

19. A device for noise reduction in a signal according to claim 3, wherein said aligner further comprises a cross-correlator for cross-correlating a current input with said ruing average at a plurality of successive alignments and for aligning said signal on the basis of an alignment giving a maximum cross-correlation.

20. A device for noise reduction in a signal according to claim 19 wherein said aligner further comprises:

an interpolator for interpolating between said cross-correlations at said successive alignments to determine a higher accuracy sub-sample alignment, and a wave shifter for shifting said current input in accordance with said determined sub-sample alignment.

21. A device for reducing noise in signals having successive substantially repetitive portions, comprising:

an aligner for aligning at least some of said substantially repetitive portions one with another,

a repetitive portion selector for selecting repetitive portions for passing to said iterative averager on the basis of a comparison with a reference portion, and

an iterative averager operative to superimpose and average said aligned, selected portions to produce a running average thereof.

22. A device for reducing noise in signals according to claim 21, further comprising a repetitive portion selector for selecting repetitive portions for passing to said iterative averager, the repetitive portion selector comprising

a reference portion store for storing a reference portion,

a cross correlator for computing the cross correlation between a current repetitive portion and said reference portion, and

a comparator for comparing a result of said cross-correlation with a predetermined threshold to produce a comparison output,

and wherein said selector is operable to pass said current repetitive portion to said iterative averager in accordance with said comparison output.

23. A device for reducing noise in signals according to claim 21, further comprising a reference portion determination unit associated with said repetitive portion selector, operable to determine as a reference portion any one of a group comprising a first repetitive portion of a current length of said signal, a final result of a running average of a previous set of iterations and a prior determined typical wave.

24. A device for reducing noise in signals according to claim 22, wherein said reference portion determination unit is operable to dynamically change between members of said group over a course of a set of iterations.

25. A device for reducing noise in signals according to claim 22, wherein said reference portion determination unit further comprises a reference portion updater for dynamically updating said reference portion during a course of a set of iterations.

26. A device for reducing noise in signals according to claim 21, comprising a reference portion determiner, said reference portion determiner comprising,

a first store for storing a first set of repetitive portions from said signal,

a second store for storing a second set of repetitive portions from said signal,

a cross-correlator for cross-correlating repetitive portions from said second set in turn with repetitive portions from said first set to produce a plurality of cross-correlation results for respective repetitive portions in said second set,

and a reference selector for selecting one of said repetitive portions in said second set as a reference portion in accordance with its respective cross-correlation results.

27. A device for noise reduction in a signal according to claim 25, wherein said reference selector comprises a threshold level comparator for comparing each cross-correlation result with a threshold and which is operable to select as said reference portion a repetitive portion having a highest number of respective cross-correlation results exceeding said threshold.

28. A device for noise reduction according to claim 25, wherein said reference selector comprises a summation unit for summing cross-correlation results of respective repetitive portions and which reference selector is operable to select as a reference portion a repetitive portion having a highest sum of respective cross-correlation results.

29. A device for noise reduction according to claim 25, wherein said reference selector comprises:

a threshold level comparator for comparing each cross-correlation result with a threshold, and

a summation unit for summing cross-correlation results of respective repetitive portions exceeding said threshold,

and which reference selector is operable to select as a reference portion a repetitive portion having a highest sum of respective cross-correlation results.

30. A waveform frequency component alignment device for aligning first frequency components of waveforms having first frequency and second frequency components, the device comprising:

Band pass filters for extracting respective first and second frequency components of said waveform,

a first frequency component aligner for determining a first frequency alignment point of a current waveform with another waveform based on respective first frequency components,

and a second frequency aligner for aligning said second frequency components of said respective waveforms based on said first frequency alignment point.

31. A waveform frequency component alignment device according to claim 30, wherein said other waveform is a running average of preceding waveforms.

32. A waveform frequency component alignment device according to claim 30, wherein said first frequency component aligner further comprises a cross-correlator for cross-correlating a current waveform with said other waveform at a plurality of successive alignments and for determining said first frequency alignment point on the basis of a one of said successive alignments giving a maximum cross-correlation.

33. A waveform high frequency component alignment device according to claim 32, wherein said first frequency component aligner further comprises an interpolator for interpolating between said cross-correlations at said successive alignments to determine a sub-sample accuracy alignment point between said successive alignments.

34. A device for analyzing high frequency components of ECG signals, comprising

a data extractor for extracting said high frequency components and

a data analyzer for determining, from a change over time in at least a part of said high frequency component, whether said ECG signal contains an indication of the presence of ischemia.

35. A device for analyzing high frequency components of ECG signals according to claim 34, wherein said at least a part of said ECG signal is a QRS complex.

36. A device according to claim 35, wherein said change over time is a fall in the energy level of succeeding QRS complexes.

37. A device according to claim 35, wherein said change over time is a fall in a cross-correlation value of succeeding QRS complexes.

38. A device according to claim 34, wherein said data extractor comprises a waveform averager for performing iterative averaging over successive ones of said high frequency components to obtain a reduced noise version of said components.

39. A device according to claim 38, further comprising a selector for passing to said waveform averager only those ones of said successive components which exceed a threshold cross-correlation with a reference component.

40. A method for reducing noise in signals having successive substantially repetitive portions, comprising:

superimposing one by one weightwise in iterative steps weighted instances of at least some of said successive substantially repetitive portions,

forming a running average of said portions,

determining a noise level in said running average, and

ending said iterative steps when said noise level reaches a predetermined level, thereby to produce an average of said substantially repetitive portions having reduced noise.

41. A method for reducing noise in signals according to claim 40, further comprising a step of aligning at least some of said substantially repetitive portions one with another,

42. A method for reducing noise in signals according to claim 41, wherein said signal comprises first frequency and second frequency components and said step of aligning comprises substeps of

extracting said respective first and second frequency components,

using said first frequency components to locate an alignment point in each of successive portions, and

using said alignment point to align said second frequency components of each of said successive portions.

43. A method for reducing noise in signals according to claim 40, wherein said step of ending said iterative steps further comprises ending when said repetitive portions are exhausted.

44. A method for reducing noise in signals according to claim 40, wherein said step of ending said iterative steps further comprises ending when said running average reaches a preset maximum of included repetitive portions.

45. A method for reducing noise in signals according to claim 40, further comprising the step of selecting repetitive portions for passing to said iterative averager, the step of repetitive portion selecting comprising substeps of:

storing a reference portion,

Computing the cross correlation between a current repetitive portion and said reference portion,

comparing a result of said cross-correlation with a predetermined threshold to produce a comparison output, and

passing said current repetitive portion for iterative averaging in accordance with said comparison output.

46. A method for reducing noise in signals according to claim 45, further comprising the step of determining as a reference portion any one of a group comprising a first repetitive portion of a current length of said signal, a final result of a running average of a previous set of iterations and a prior determined typical wave.

47. A method for reducing noise in signals according to claim 46, wherein said step of selecting comprises the further substep of dynamically changing between members of said group over the course of a set of iterations.

48. A method for reducing noise in signals according to claim 46, wherein said step of selecting further comprises dynamically updating said reference portion during the course of a set of iterations.

49. A method for reducing noise in signals according to claim 45, comprising a step of determining a reference portion by:

storing a first set of repetitive portions from said signal,

storing a second set of repetitive portions from said signal,

cross-correlating repetitive portions from said second set in turn with repetitive portions from said first set to produce a plurality of cross-correlation results for respective repetitive portions in said second set, and

selecting one of said repetitive portions in said second set as a reference portion in accordance with its respective cross-correlation results.

50. A method for noise reduction in a signal according to claim 49, further comprising:

comparing each cross-correlation result with a threshold, and

selecting as said reference portion a repetitive portion having a highest number of respective cross-correlation results exceeding said threshold.

51. A method for noise reduction according to claim 49, wherein said step of determining a reference further comprises:

summing cross-correlation results of respective repetitive portions and

selecting as a reference portion a repetitive portion having the highest sum of respective cross-correlation results.

52. A method for noise reduction according to claim 49, wherein said step of determining a reference portion further comprises:

comparing each cross-correlation result with a threshold,

summing cross-correlation results of respective repetitive portions exceeding said threshold, and

selecting as a reference portion a repetitive portion having a highest sum of respective cross-correlation results.

53. A method for noise reduction in a signal according to claim 40, further comprising the step of extracting QRS complexes from an ECG signal to provide said repetitive portion.

54. A method for noise reduction in a signal according to claim 40 comprising extracting an RMS energy value from an average of a series of said repetitive portions.

55. A method for noise reduction in a signal according to claim 54, further comprising a step of analyzing said RMS energy to detect for the presence of a falloff in said RMS energy value over succeeding averages.

56. A method for noise reduction in a signal according to claim 40, comprising extracting a cross-correlation value from an average of a series of said repetitive portions.

57. A method for noise reduction in a signal according to claim 56, further comprising the step of analyzing succeeding ones of said cross correlation value to detect the presence of a falloff in said cross-correlation value over succeeding averages.

58. A method for noise reduction in a signal according to claim 42, wherein said alignment step further comprises cross-correlating a current input with said running average at a plurality of successive alignments, and

aligning said signal on the basis of an alignment giving a maximum cross-correlation.

59. A method for noise reduction in a signal according to claim 58, said step of alignment further comprising interpolating between said cross-correlations at successive alignments to determine a high accuracy alignment between said successive alignments.

60. A method for reducing noise in signals having successive substantially repetitive portions, comprising:

aligning at least some of said substantially repetitive portions one with another,

selecting repetitive portions for passing to said iterative averager on the basis of a comparison with a reference portion, and

superimposing and averaging said aligned, selected portions to produce a running average thereof.

61. A method for reducing noise in signals according to claim 60, further comprising a step of selecting from said repetitive portions for passing to said iterative averager, the step of selecting comprising substeps of:

storing a reference portion,

carrying out a cross correlation between a current repetitive portion and said reference portion,

comparing a result of said cross-correlation with a predetermined threshold to produce a comparison output, and

passing said current repetitive portion to said iterative averager in accordance with said comparison output.

62. A method for reducing noise in signals according to claim 60, comprising the further step of selecting as a reference portion any one of a group comprising a first repetitive portion of a current length of said signal, a final result of a running average of a previous set of iterations and a prior determined typical wave.

63. A method for reducing noise in signals according to claim 62, wherein said step of selecting a reference portion includes a substep of dynamically change between members of said group over the course of a set of iterations.

64. A device for reducing noise in signals according to claim 62, wherein said step of selecting a reference portion includes dynamically updating said reference portion during the course of a set of iterations.

65. A method for reducing noise in signals according to claim 61, comprising a step of determining a reference point, said step comprising,

storing a first set of repetitive portions from said signal,

storing a second set of repetitive portions from said signal,

cross-correlating repetitive portions from said second set in turn with repetitive portions from said first set to produce a plurality of cross-correlation results for respective repetitive portions in said second set, and

selecting one of said repetitive portions in said second set as a reference portion in accordance with its respective cross-correlation results.

66. A method for noise reduction in a signal according to claim 65, comprising the further steps of:

comparing each cross-correlation result with a threshold, and

selecting as said reference portion a repetitive portion having a highest number of respective cross-correlation results exceeding said threshold.

67. A method for noise reduction according to claim 65, comprising the further steps of

summing cross-correlation results of respective repetitive portions, and

selecting as a reference portion a repetitive portion having the highest sum of respective cross-correlation results.

68. A method for noise reduction according to claim 65, comprising the further steps of:

comparing each cross-correlation result with a threshold,

summing cross-correlation results of respective repetitive portions exceeding said threshold, and

selecting as a reference portion a repetitive portion having a highest sum of respective cross-correlation results.

69. A method of aligning waveforms having first and second frequency components, said second frequency components being more subject to noise than said first frequency components, the method comprising:

extracting respective first and second frequency components of said waveform,

determining an alignment point of a current waveform with another waveform based on respective first frequency components, and

aligning said second frequency components of said respective waveforms based on said alignment point.

70. A method of aligning waveforms according to claim 69, wherein said other waveform is a running average of preceding waveforms.

71. A method of aligning waveforms according to claim 69, comprising the further steps of:

cross-correlating a current waveform with said other waveform at a plurality of successive alignments, and

determining said alignment point on the basis of a one of said successive alignments giving a maximum cross-correlation.

72. A method of aligning waveforms according to claim 71, comprising the further step of interpolating between said cross-correlations at said successive alignments to obtain a sub-sample alignment point.

73. A method for analyzing high frequency components of ECG signals, comprising the steps of:

extracting said high frequency components and

determining, from a change over time in at least a part of said high frequency component, whether said ECG signal contains an indication of the presence of ischemia.

74. A method for analyzing high frequency components of ECG signals, according to claim 73, wherein said at least a part of said ECG signal is at least part of a QRS complex.

75. A method for analyzing high frequency components of an ECG signal according to claim 74, wherein said change over time is a fall in an RMS energy level of succeeding QRS complexes.

76. A method for analyzing high frequency components of an ECG signal according to claim 74, wherein said change over time is a fall in a cross-correlation value of succeeding QRS complexes.

77. A method for analyzing high frequency components of an ECG signal according to claim 75, comprising the further step of performing iterative averaging over successive ones of said high frequency components to obtain a reduced noise version of said components.

78. A method for analyzing high frequency components of an ECG signal according to claim 77, further comprising a selection step of comparing successive waveforms with a reference component and selecting only those ones of said successive waveforms which exceed a threshold cross-correlation level with said reference component for said step of iterative averaging.

79. A method of obtaining an indication of ischemia in a patient using an ECG signal therefrom, the method comprising:

extracting an ECG signal over a duration,

extracting from said ECG signal a series of at least partial QRS complexes over said duration,

extracting high frequency components of said QRS complexes,

analyzing said high frequency components over said duration for at least one of a predetermined quality, and

inferring from said predetermined quality an indication of ischemia.

80. A method according to claim 79, wherein said predetermined quality is a falloff in a cross-correlation level with a reference component.

81. A method according to claim 79, wherein said predetermined quality is a falloff in the energy level of said component.

82. A method according to claim 79, wherein said step of extracting said high frequency components comprises carrying out iterative steps of averaging over preselected ones of successive components to reduce noise

83. A method according to claim 79, wherein said step of extracting an ECG signal is carried out over a duration of a stress test comprising placing the patient in at least one of a group of phases comprising rest, stress, and recovery from stress.

84. A method according to claim 79, wherein said step of extracting an ECG signal is carried out over a duration of an event being any one of a group comprising:

acute myocardial ischemia, other forms of heart failure, coronary occlusion, and coronary angioplasty, said duration being any one of a group comprising before, during and after said event.

85. A method according to claim 79, wherein said ECG signal is masked by another ECG signal.

87. A method according to claim 83 comprising the further step of ending said iterative averaging when a signal to noise ratio of a result of said iterative averaging has a level below a predetermined threshold.

86. A method of producing a noise reduced waveform from a series of substantially similar repeated waveforms having superimposed noise, the method comprising:

selecting waveforms having a highest cross-correlation with a preselected reference waveform, and

carrying out iterative averaging steps using said selected waveforms.