Automatic orientation determination for ECG measurements using multiple electrodes

• US 20050288600A1
• Filed: 06/24/2004
• Published: 12/29/2005
• Est. Priority Date: 06/24/2004
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: McCabe, Aaron, Sweeney, Robert J., Zhang, Yi, Ricci, Carlos Alberto, Daum, Douglas R., Brockway, Marina, Heil, Ron
• Granted Patent: US 7,706,866 B2
• Time in Patent Office: Days
• US Class Current: 600/510
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/341 Vectorcardiography [VCG]
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7217 of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
• CPC Class Codes: A61N 1/3756 Casings with electrodes thereon, e.g. leadless stimulators
• CPC Class Codes: G06F 18/2134 based on separation criteria, e.g. independent component analysis

Abstract

Cardiac monitoring and/or stimulation methods and systems provide monitoring, defibrillation and/or pacing therapies. A signal processor receives a plurality of composite signals associated with a plurality of sources, separates a signal using a source separation algorithm, and identifies a cardiac signal using a selected vector. The signal processor may iteratively separate signals from the plurality of composite signals until the cardiac signal is identified. The selected vector may be updated if desired or necessary. A method of signal separation involves detecting a plurality of composite signals at a plurality of locations, separating a signal using source separation, and selecting a vector that provides a cardiac signal. The separation may include a principal component analysis and/or an independent component analysis. Vectors may be selected and updated based on changes of position and/or orientation of implanted components and changes in patient parameters such as patient condition, cardiac signal-to-noise ratio, and disease progression.

Claims

1. A signal separation method, comprising:

sensing, at least in part implantably, a plurality of composite signals using a plurality of cardiac electrodes;

performing a source separation using the detected plurality of composite signals, the source separation producing a plurality of vectors;

identifying, for each vector of the plurality of vectors, a signal from the detected plurality of composite signals;

selecting one vector from the plurality of vectors as a selected vector based on a selection criterion; and

using the signal associated with the selected vector.

2. The method of claim 1, wherein the selection criterion comprises detection of a cardiac signal.

3. The method of claim 1, wherein the selection criterion comprises detection of a cardiac signal using a local rate of occurrence of significant points in the identified signals, wherein the local rate of occurrence is within a predetermined range.

4. The method of claim 1, wherein the selection criterion comprises identifying a cardiac signal using a morphology of the identified signals.

5. The method of claim 1, wherein the selection criterion comprises identifying a cardiac signal using a local peak density of the identified signals, wherein the local peak density is within a predetermined range.

6. The method of claim 1, wherein the selection criterion comprises identifying a cardiac signal using a beat detection of the identified signals, wherein a beat rate is within a predetermined range.

7. The method of claim 1, wherein the selection criterion comprises finding a noise signal.

8. The method of claim 1, further comprising band-pass filtering the sensed plurality of composite signals.

9. The method of claim 1, further comprising iteratively separating signals from the detected plurality of composite signals until a cardiac signal is identified.

10. The method of claim 1, wherein the detected plurality of composite signals comprise a cardiac signal and at least one non-cardiac signal.

11. The method of claim 1, wherein performing the source separation comprises performing blind source separation.

12. The method of claim 1, wherein the source separation comprises a principal component analysis.

13. The method of claim 12, wherein the principal component analysis includes a singular value decomposition.

14. The method of claim 1, wherein the source separation comprises an independent component analysis.

15. The method of claim 1, wherein the source separation comprises a principal component analysis and an independent component analysis.

16. The method of claim 1, further comprising forming an estimate of a spatial covariance matrix for a composite signal matrix formed from the detected plurality of composite signals.

17. The method of claim 16, further comprising performing a principal component analysis on the estimate of the spatial covariance matrix to produce a set of singular values and associated singular vectors.

18. The method of claim 17, wherein an eigenvector of the associated eigenvectors that is associated with a largest magnitude singular value of the set of singular values is used to separate a cardiac signal from the detected plurality of composite signals.

19. The method of claim 18, wherein signals are iteratively separated from the detected plurality of composite signals using a next-largest magnitude singular value of the set of singular values for each iteration, until a cardiac signal is separated from the detected plurality of composite signals.

20. A signal separation method, comprising:

sensing, at least in part implantably, a plurality of composite signals at a plurality of locations;

performing source separation on the detected plurality of composite signals to produce a set of signal vectors;

selecting, from the set of signal vectors, a target vector associated with a target signal; and

updating selection of the target vector by performing a subsequent source separation on the detected plurality of composite signals.

21. The method of claim 20, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal.

22. The method of claim 20, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal using a local rate of occurrence of significant points in the target signal, wherein the local rate of occurrence is within a predetermined range.

23. The method of claim 20, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal using a morphology of the target signal.

24. The method of claim 20, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal using a local peak density of the target signal, wherein the local peak density is within a predetermined range.

25. The method of claim 20, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal using beat detection on the target signal, wherein a beat rate is within a predetermined range.

26. The method of claim 20, wherein updating the target vector is performed in response to detection of a pathologic change.

27. The method of claim 20, wherein updating the target vector is performed in response to a change in orientation of a patient-internal medical device.

28. The method of claim 20, wherein updating the target vector is performed in response to exceeding an arrhythmia detection rate zone or threshold.

29. The method of claim 20, wherein updating the target vector is performed in response to patient activity level.

30. The method of claim 20, wherein updating the target vector is performed in response to detection of a postural change.

31. The method of claim 20, wherein updating the target vector is performed in response to detection of a therapy change.

32. The method of claim 20, wherein the target vector is updated in response to detection of an activation stimulus.

33. The method of claim 20, wherein the target vector is updated periodically.

34. The method of claim 20, wherein updating the target vector is performed in response to a change of a signal to noise ratio of the target signal.

35. The method of claim 20, further comprising band-pass filtering the detected plurality of composite signals.

36. The method of claim 20, further comprising forming an estimate of a spatial covariance matrix for the detected plurality of composite signals.

37. The method of claim 20, further comprising performing a principal component analysis on the spatial covariance matrix for the detected plurality of composite signals.

38. The method of claim 20, further comprising performing an independent component analysis on the detected plurality of composite signals.

39. The method of claim 20, further comprising performing a principal component analysis and an independent component analysis on the detected plurality of composite signals.

40. A cardiac system, comprising:

a plurality of electrodes, each electrode configured for sensing a composite signal, thereby providing a plurality of composite signals;

a housing configured for implantation in a patient;

a controller provided in the housing;

a memory configured to store a target vector; and

a signal processor configured to receive the plurality of composite signals and perform a source separation algorithm that separates a target signal from the plurality of composite signals using the target vector, wherein the signal processor is further configured to update the target vector stored in the memory by performing a subsequent source separation.

41. The system of claim 40, wherein the signal processor and the memory are provided in the housing.

42. The system of claim 40, wherein the signal processor is provided in a patient-external device or system, the signal processor and the controller coupled to respective communication devices to facilitate wireless communication between the signal processor and controller.

43. The system of claim 40, wherein the signal processor is provided in a network server system, the signal processor and the controller coupled to respective communication devices to facilitate wireless communication between the signal processor and controller.

44. The system of claim 40, wherein the signal processor iteratively separates target signals from the plurality of composite signals using different target vectors, until the target vector that provides a cardiac signal is identified.

45. The system of claim 40, wherein the signal processor comprises a filter configured to filter the plurality of composite signals prior to separating the target signal.

46. The system of claim 40, wherein the signal processor comprises a filter configured to band-pass filter the plurality of composite signals prior to separating the target signal.

47. The system of claim 40, wherein the signal processor forms an estimate of a spatial covariance matrix for the plurality of composite signals.

48. The system of claim 40, wherein the signal processor performs a principal component analysis on the spatial covariance matrix for the plurality of composite signals used to separate the target signal from the plurality of composite signals.

49. The system of claim 40, wherein the signal processor detects a cardiac condition using the separated target signal.

50. The system of claim 40, further comprising a lead configured for subcutaneous non-intrathoracic placement in a patient and coupled to the signal processor, wherein at least some of the plurality of electrodes are supported by the lead.

51. The system of claim 40, wherein the housing comprises a header configured for coupling a lead to the housing, and at least one of the plurality of electrodes is provided on the header.

52. The system of claim 40, further comprising a lead coupled to the signal processor, wherein at least some of the plurality of electrodes are supported by the lead.

53. The system of claim 40, further comprising an antenna coupled to the controller, the antenna configured to receive a patient-externally generated signal.

54. The system of claim 53, wherein the antenna is further configured as one or more of the plurality of electrodes.

55. The system of claim 40, wherein at least one of the plurality of electrodes is disposed in or on the housing and configured as a can electrode.

56. The system of claim 55, wherein the can electrode is configured to extend between at least a portion of a front surface of the housing and at least a portion of a rear surface of the housing.

57. The system of claim 40, wherein at least two of the plurality of electrodes are disposed in or on the housing and configured as can electrodes.

58. The system of claim 40, wherein the plurality of electrodes comprises at least four electrodes, wherein one of the at least four electrodes does not lie in the same plane as the other of the at least four electrodes.

59. The system of claim 40, wherein the signal processor is configured to perform a blind source separation algorithm.

60. The system of claim 40, wherein the memory is configured to store ECG signals.

61. An implantable cardiac device, comprising:

means for subcutaneously detecting a plurality of composite signals produced by a plurality of sources;

means for performing source separation using the detected plurality of composite signals;

means for separating a target signal from the detected plurality of composite signals using a target vector determined from the source separation; and

means for updating the target vector.

62. The device of claim 61, wherein the separating means performs a principal component analysis on the detected plurality of composite signals.

63. The device of claim 61, wherein the separating means produces a set of eigenvalues and associated eigenvectors, and an eigenvector with a largest magnitude eigenvalue is used for separating the target signal from the detected plurality of composite signals.

64. The device of claim 61, wherein the separating means iteratively separates the target signal from the detected plurality of composite signals using a next-largest magnitude eigenvalue for each iteration, until a cardiac signal is separated from the detected plurality of composite signals.

65. The device of claim 61, further comprising means for identifying the separated target signal as a cardiac signal.

66. The device of claim 65, further comprising means for detecting a cardiac condition using the cardiac signal.

67. The device of claim 66, further comprising means for treating the cardiac condition.

68. A method, comprising:

receiving a plurality of signals from a plurality of electrodes configured to detect cardiac activity; and

mathematically reconstructing an electrocardiogram vector corresponding to a signal having a largest cardiac signal-to-noise ratio using a linear combination of the plurality of signals.

69. The method of claim 68, further comprising band-pass filtering the received plurality of signals.

70. The method of claim 68, wherein mathematically reconstructing the electrocardiogram vector comprises performing blind source separation.

71. The method of claim 68, wherein mathematically reconstructing the electrocardiogram vector comprises a principal component analysis.

72. The method of claim 68, wherein the principal component analysis includes a singular value decomposition.

73. The method of claim 68, wherein mathematically reconstructing the electrocardiogram vector comprises an independent component analysis.

74. The method of claim 68, wherein mathematically reconstructing the electrocardiogram vector comprises a principal component analysis and an independent component analysis.

75. The method of claim 68, further comprising forming an estimate of a spatial covariance matrix for a signal matrix formed from the detected plurality of signals.

76. The method of claim 75, further comprising performing a principal component analysis on the estimate of the spatial covariance matrix to produce a set of singular values and associated singular vectors.