Method and system for generating a likelihood of cardiovascular disease, analyzing cardiovascular sound signals remotely from the location of cardiovascular sound signal acquisition, and determining time and phase information from cardiovascular sound signals

• US 20030229289A1
• Filed: 03/18/2003
• Published: 12/11/2003
• Est. Priority Date: 03/18/2002
• Status: Active Grant

• Current Assignee: AusculSciences, Inc.
• Original Assignee: SonoMedica, Inc.
• Inventors: Mohler, Sailor Hampton, Figgatt, Alan, Mulholland, Dan, Holford, Warren
• Granted Patent: US 7,190,994 B2
• Time in Patent Office: Days
• US Class Current: 600/508
• CPC Class Codes: A61B 5/02 Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
• 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 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/322 Physical templates or devices for measuring ECG waveforms, e.g. electrocardiograph rulers or calipers by template matching A61B5/35
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 7/026 comprising more than one sound collector
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A system, method, and computer executable code for generating a likelihood of cardiovascular disease from acquired cardiovascular sound signals is diesclosed, where the generated likelihood of cardiovascular disease is based at least on an overlapping in time of bruit candidates in one heart cycle or in different heart cycles. Also disclosed is a system, method, and computer executable code for collecting, forwarding, and analyzing cardiovascular sound signals, where the collecting and analyzing may occur at locations that are remote from each other. Further disclosed is a system, method, and computer executable code for determining the time and phase information contained in cardiovascular sound signals, for use in analyzing those cardiovascular sound signals.

Claims

1. A method comprising:

determining a first time window within which a first bruit candidate is located;

determining a second time window within which a second bruit candidate is located; and

if the first time window and the second time window overlap in time with respect to a common reference, then emphasizing the overlap of the first time window and the second time window in a generation of a likelihood of cardiovascular disease.

2. The method of claim 1, the first and second time windows each having an accuracy greater than at least half of a duration of either diastole or systole.

3. The method of claim 1, the first bruit candidate and the second bruit candidate each being within one heart cycle.

4. The method of claim 1, the first bruit candidate being within a first heart cycle and the second bruit candidate being within a second heart cycle.

5. The method of claim 4, the first heart cycle being part of a first heart waveform signal corresponding to a first location of a patient where cardiovascular sound signals were acquired, the second heart cycle being part of a second heart waveform signal corresponding to a second location of the patient where cardiovascular sound signals were acquired.

6. The method of claim 4, the first heart cycle and the second heart cycle being part of a single heart waveform signal corresponding to one location of a patient where cardiovascular sound signals were acquired.

7. A method comprising:

determining, to an accuracy greater than at least half of a duration of either diastole or systole, a first time window within which a first bruit candidate is located;

determining, to an accuracy greater than at least half of a duration of either diastole or systole, a second time window within which a second bruit candidate is located; and

generating a likelihood of cardiovascular disease, an overlapping in time of the first time window and the second time window contributing to the generated likelihood.

8. A method for processing acquired cardiovascular sound signals of a patient, the cardiovascular sound signals corresponding to at least a first heart cycle and a second heart cycle of the patient, the method comprising:

defining a plurality of time windows of the acquired cardiovascular sound signals, each of the time windows being a portion of a whole of diastole or systole of the first and second heart cycles of the patient;

determining a location of a first bruit candidate in the first heart cycle based on information collected from the time windows;

determining a location of a second bruit candidate in the second heart cycle based on information collected from the time windows; and

generating a likelihood that the patient has cardiovascular disease, the determined location of the first bruit candidate and the determined location of the second bruit candidate contributing to the generated likelihood.

9. The method of claim 8, the generated likelihood including a numerical indicator.

10. The method of claim 9, the numerical indicator being between 0 and 1 or between 0 and 100%.

11. The method of claim 8, the acquired cardiovascular sound signals including one heart waveform signal corresponding to a location of the patient where the cardiovascular sound signals were acquired, the heart waveform signal including the first and second heart cycles of the patient.

12. The method of claim 8, the acquired cardiovascular sound signals including one heart waveform signal corresponding to a location of the patient where the cardiovascular sound signals were acquired, the heart waveform signal including the first heart cycle of the patient.

13. The method of claim 12, the one heart waveform signal being a first heart waveform signal, the cardiovascular sound signals further including a second heart waveform signal corresponding to second location of the patient where the cardiovascular sound signals were acquired, the second heart waveform signal including the second heart cycle of the patient.

14. The method of claim 8, the determined location of the first bruit candidate and the determined location of the second bruit candidate each being measured relative to a common reference of the first and the second heart cycles.

15. The method of claim 14, the common reference being a common time location in the first and second heart cycles.

16. The method of claim 15, the common time location being the start or end of S1.

17. The method of claim 15, the common time location being the start or end of S2.

18. The method of claim 14, further comprising:

determining the common reference using a signal derived from electrical potential heart signals.

19. The method of claim 14, further comprising:

determining the common reference without the assistance of a signal derived from electrical potential heart signals.

20. The method of claim 8, the generated likelihood being based on a power of the first bruit candidate and a power of the second bruit candidate.

21. The method of claim 8, the generated likelihood being based on a frequency of the first bruit candidate and a frequency of the second bruit candidate.

22. The method of claim 8, the generated likelihood being based on a duration of the first bruit candidate and a duration of the second bruit candidate.

23. The method of claim 8, the cardiovascular sound signals corresponding to a third heart cycle of the patient, the method further comprising:

determining a location of a third bruit candidate in the third heart cycle based on information collected from the time windows, the determined location of the third bruit candidate contributing to the generated probability indicator.

24. A method comprising:

generating from acquired cardiovascular sound signals a likelihood that a patient has cardiovascular disease based on whether signals indicative of bruit occur within a same time window of at least two different heart cycles of the patient, the same time window being measured relative to a common reference in the two different heart cycles and being a portion of a whole of diastole or systole of each of the at least two different heart cycles.

25. A method for processing cardiovascular sound signals of a patient, the cardiovascular sound signals corresponding to at least two different heart cycles of the patient, each of the different heart cycles having one of a systole or a diastole divided into a plurality of time windows, each of the different heart cycles having a common reference, the method comprising:

generating a likelihood that the patient has cardiovascular disease based on whether bruit candidates occur within at least one same time window of the plurality of time windows of the two different heart cycles of the patient, the same time window being measured relative to the common reference.

26. A method comprising:

identifying a first bruit candidate in a first heart cycle of a patient based on acquired cardiovascular signals of the patient;

identifying a second bruit candidate in a second heart cycle of the patient based on the acquired cardiovascular signals of the patient; and

determining a time location of the identified first bruit candidate and a time location of the second bruit candidate, both relative to a common reference in each of the first and second heart cycles of the patient.

27. A method comprising:

generating a two dimensional distribution matrix of probability indicators for at least two bruit candidates in one heart cycle or in different heart cycles.

28. A method comprising:

generating a two dimensional distribution matrix of probability indicators for each of a plurality of heart waveform signals, each of the heart waveform signals corresponding to a different location where cardiovascular sound signals were acquired.

29. A method comprising:

generating a two dimensional running total bruit matrix for a first heart waveform; and

generating a two dimensional running total bruit matrix for a second heart waveform.

30. The method of claim 29, further comprising:

generating a likelihood of cardiovascular disease from the two dimensional running total bruit matrix for the first heart waveform and the two dimensional running total bruit matrix for the second heart waveform.

31. A system comprising:

means for determining, to an accuracy greater than at least half of a duration of either diastole or systole, a first time window within which a first bruit candidate is located;

means for determining, to an accuracy greater than at least half of a duration of either diastole or systole, a second time window within which a second bruit candidate is located; and

means for generating a likelihood of cardiovascular disease, an overlapping in time of the first time window and the second time window contributing to the generated likelihood.

32. A computer readable medium containing computer program instructions for:

determining, to an accuracy greater than at least half of a duration of either diastole or systole, a first time window within which a first bruit candidate is located;

determining, to an accuracy greater than at least half of a duration of either diastole or systole, a second time window within which a second bruit candidate is located; and

generating a likelihood of cardiovascular disease, an overlapping in time of the first time window and the second time window contributing to the generated likelihood.

33. A computer readable medium containing computer program instructions for:

identifying a first bruit candidate in a first heart cycle of a patient based on acquired cardiovascular sound signals of the patient;

identifying a second bruit candidate in a second heart cycle of the patient based on the acquired cardiovascular sound signals of the patient; and

determining a time location of the first bruit candidate and a time location of the second bruit candidate, both relative to a common reference in each of the first and second heart cycles of the patient.

34. A method comprising:

determining a start point or an end point of at least one of S1, S2, S3, and S4 within each of a plurality of heart cycle signals independently of a signal derived from electrical potential or optical heart signals, each of the plurality of heart cycle signals corresponding to a different heart cycle.

35. The method of claim 34, further comprising:

identifying any possible bruit signals in each heart cycle within a time window located relative to the determined start point or determined end point.

36. The method of claim 35, further comprising:

generating a probability indicator indicative of the likelihood that the patient has cardiovascular disease based on at least some of identified possible bruit signals.

37. The method of claim 34, said determining including determining the end point of S2.

38. The method of claim 37, further comprising:

identifying in each heart cycle within a time window located relative to the end point of S2 any possible bruit signals.

39. The method of claim 34, said determining including determining the end point of S1 .

40. The method of claim 39, further comprising:

identifying in each heart cycle within a time window located relative to the end point of S1 any possible bruit signals.

41. The method of claim 34, said determining the start point of at least one of S1, S2, S3, and S4 within each of the plurality of heart cycle signals comprising:

applying at least one low pass filter to each of said heart cycle signals to obtain a low pass filter set for each heart cycle; and

decimating the low pass filter set to obtain a decimated sample set for each heart cycle.

42. The method of claim 41, said determining the start point of at least one of S1, S2, S3, and S4 within each of the plurality of heart cycle signals comprising:

convolving the decimated sample set with itself to produce an auto correlation.

43. The method of claim 42, said determining the start point of at least one of S1, S2, S3, and S4 within each of the plurality of heart cycle signals comprising:

determining a start point of each of the heart cycle signals.

44. The method of claim 41, the low pass filter having cutoff frequency between 3000-6000 Hz.

45. The method of claim 44, the cutoff being approximately 4410 Hz.

46. The method of claim 41, the low pass filter having cutoff frequency between 300-600 Hz.

47. The method of claim 46, the cutoff being approximately 441 Hz.

48. A method comprising:

receiving cardiovascular sound signals of a patient that were previously captured at a point of care of the patient;

processing at a location remote from the point of care the received cardiovascular sound signals to generate a probability indicator indicative of the likelihood that the patient has cardiovascular disease; and

forwarding the probability indicator to at least one of the point of care and another location.

49. The method of claim 48, the received cardiovascular sound signals further comprising digital signals that were previously converted from analog signals.

50. The method of claim 48, the received cardiovascular sound signals further comprising a plurality of heart waveform signals each corresponding to a different location where the patient'"'"'s heart sounds were sensed.

51. The method of claim 50, each heart waveform signal further comprising a plurality of heart cycle signals.

52. The method of claim 51, each heart cycle signal corresponding to a heart cycle of the patient.

53. The method of claim 48, said receiving further comprising receiving a plurality of data files, each data file containing at least one heart waveform signal of a patient.

54. The method of claim 53, each of said data files also including background noise signals.

56. The method of claim 48, said forwarding further comprising forwarding the generated probability to a location remote from a location where the probability indicator was generated.

57. The method of claim 56, further comprising forwarding the probability indicator to the point of care over a data communications network

58. The method of claim 57, wherein said data communications network further comprises the internet.

59. The method of claim 48, said receiving further comprising receiving the cardiovascular sound signals in an encrypted format.

55. The method of claim 55, each of said data files also including an ECG signal.

60. A system comprising:

means for receiving cardiovascular sound signals of a patient that were previously captured at a point of care of the patient;

means for processing at a location remote from the point of care the received cardiovascular sound signals to generate a probability indicator indicative of the likelihood that the patient has cardiovascular disease; and

means for forwarding the probability indicator to at least one of the point of care and another location.

61. A computer readable medium containing computer program instructions for:

receiving cardiovascular sound signals of a patient that were previously captured at a point of care of the patient;

processing at a location remote from the point of care the received cardiovascular sound signals to generate a probability indicator indicative of the likelihood that the patient has cardiovascular disease; and

forwarding the probability indicator to at least one of the point of care and another location.

62. A method comprising:

capturing cardiovascular sound signals of a patient at a point of care of the patient;

forwarding to a location remote from the point of care the captured cardiovascular sound signals; and

receiving from the location remote from the point of care a probability indicator indicative of the likelihood that the patient has cardiovascular disease, the probability indicator being generated based on the cardiovascular sound signals that were forwarded to the location remote from the point of care.

63. The method of claim 62, the captured cardiovascular sound signals further comprising a plurality of heart waveform signals each corresponding to a different location where the patient'"'"'s heart sounds were sensed.

64. The method of claim 63, each heart waveform signal further comprising heart cycles signals each corresponding to a heart cycle.

65. The method of claim 62, further comprising capturing background noise signals and forwarding said background noise signals to the location remote from the point of care.

66. The method of claim 62, further comprising capturing an ECG signal and forwarding said ECG signal to the location remote from the point of care.

67. The method of claim 62, further comprising encrypting the cardiovascular sound signals prior to said forwarding to the location remote from the point of care.

68. A system comprising:

means for capturing cardiovascular sound signals of a patient at a point of care of the patient;

means for forwarding to a location remote from the point of care the captured cardiovascular sound signals; and

means for receiving from the location remote from the point of care a probability indicator indicative of the likelihood that the patient has cardiovascular disease, the probability indicator being generated based on the cardiovascular sound signals that were forwarded to the location remote from the point of care.

69. A computer readable medium containing computer program instructions for:

capturing cardiovascular sound signals of a patient at a point of care of the patient;

forwarding to a location remote from the point of care the captured cardiovascular sound signals; and

receiving from the location remote from the point of care a probability indicator indicative of the likelihood that the patient has cardiovascular disease, the probability indicator being generated based on the cardiovascular sound signals that were forwarded to the location remote from the point of care.

70. A computer readable medium containing computer program instructions for:

determining a start point or an end point of at least one of S1, S2, S3, and S4 within each of a plurality of heart cycle signals independently of a signal derived from electrical potential or optical heart signals, each of the plurality of heart cycle signals corresponding to a different heart cycle.