METHODS, SYSTEM AND APPARATUS FOR THE DETECTION, DIAGNOSIS AND TREATMENT OF BIOLOGICAL RHYTHM DISORDERS

• US 20110251505A1
• Filed: 04/06/2011
• Published: 10/13/2011
• Est. Priority Date: 04/08/2010
• Status: Active Grant

• Current Assignee: Topera, Inc (Abbott Laboratories Incorporated), United States Department of Veterans Affairs Office of General Counsel, Regents of the University of California (University of California)
• Original Assignee: Topera Medical, Inc., Regents of the University of California (University of California)
• Inventors: Sehra, Ruchir, Narayan, Sanjiv M.
• Granted Patent: US 8,700,140 B2
• Time in Patent Office: Days
• US Class Current: 600/515
• CPC Class Codes: A61B 5/0255 Recording instruments specially adapted therefor
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/333 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/339 Displays specially adapted therefor
• CPC Class Codes: A61B 5/341 Vectorcardiography [VCG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/4857 Indicating the phase of biorhythm clocks or watches with indicators for biological cycles G04B19/264
• CPC Class Codes: A61B 5/6852 Catheters
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

Abstract

System, assembly and method are provided to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the heart rhythm disorder. The complex rhythm disorder can be treated by application of energy to modify the source of the rhythm disorder.

Claims

1. A system to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder, the system comprising:

at least one computing device configured to;

receive cardiac information signals from the patient'"'"'s heart during the complex rhythm disorder,

classify the cardiac information signals into high and low confidence signals, wherein the high and low confidence signals are separated by a confidence threshold,

determine activation onsets associated with the low confidence signals within an acceptance window;

order the activation onsets associated with the low confidence signals and activation onsets associated with the high confidence signals; and

output the activation onsets associated with the high and low confidence signals to indicate a source of the complex cardiac rhythm disorder.

2. The system according to claim 1, wherein the at least one computing device determines activation onsets associated with the low confidence signals using a wave path vector connecting at least two discernable activation onsets.

3. The system according to claim 1, wherein the complex rhythm disorder comprises no discernable period during which the cardiac information signals are quiescent.

4. The system according to claim 1, wherein the complex rhythm disorder comprises no discernable earliest activation onset associated with the cardiac information signals.

5. The system according to claim 1, wherein the at least one computing device classifies the cardiac information signals into high and low confidence signals using at least one of activation onset, cycle length (CL), action potential duration (APD), and amplitude, wherein the activation onset is determined by using at least one of maximum dV/dt, template matching, frequency and amplitude.

6. The system according to claim 1, wherein the at least one computing device determines the acceptance window using at least one of APD, conduction velocity (CV), fiber angle, wave path vector connecting at least two discernable activation onsets, and anatomic factors.

7. The system according to claim 1, wherein the at least one computing device removes baseline wander and noise from the cardiac information signals, the computing device filtering the cardiac information signals.

8. The system according to claim 1, wherein the at least one computing device disregards at least one of the cardiac information signals using at least one of signal-to-noise ratio (SNR), template matching, frequency and amplitude.

9. The system according to claim 5, wherein the at least one computing device performs template matching by identifying high-confidence level beats associated with the cardiac information signals as templates.

10. The system according to claim 5, further comprising an expert system, the expert system performing template matching.

11. The system according to claim 1, wherein the at least one computing device classifies beats associated with the cardiac information signals based on a shape associated with the beats to be classified.

12. The system according to claim 1, wherein the at least one computing device classifies beats associated with the cardiac information signals as high confidence beats in response to CL associated with the beat to be classified being greater than or equal to a minimum APD and less than or equal to a maximum CL.

13. The system according to claim 1, wherein the at least one computing device classifies beats associated with the cardiac information signals as low confidence beats in response to CL associated with the beat to be classified being less than a minimum APD or greater than a maximum CL.

14. The system according to claim 2, wherein the at least one computing device modifies the wave path vector using at least one of beat shape, beat polarity, and surrounding rotating/radial emanation.

15. The system according to claim 1, further comprising an expert system, the expert system determining the acceptance window using at least one of APD, CV, wave path vector connecting at least two discernable activation onsets, frequency and fiber angle.

16. The system according to claim 1, further comprising an expert system, the expert system determining activation onsets using wave shapes.

17. The system according to claim 1, wherein the at least one computing device determines activation onsets associated with the low confidence signals using at least one of rolling average and phase lock.

18. The system according to claim 1, wherein the at least one computing device determines activation onsets associated with the low confidence signals by reconciling activation onsets determined by using at least two of the wave path vector, acceptance window, rolling average, and phase lock.

19. The system according to claim 1, wherein the system further comprises:

at least one storage device configured to store the cardiac information signals received from the patient'"'"'s heart, the at least one storage device operatively couplable to the at least one computing device to provide the signals to the at least one computing device.

20. The system according to claim 1, wherein the system further comprises:

a catheter comprising a plurality of sensors to receive the cardiac information signals from the patient'"'"'s heart and operatively couplable to the at least one computing device provide the cardiac information signals to the at least one computing device.

21. The system according to claim 1, wherein the at least one computing device comprises a computer-readable medium storing instructions, which when executed by the at least one processing device, cause the at least one processing device to perform operations of the at least one computing device.

22. An assembly to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder, the assembly comprising:

a catheter comprising a plurality of sensors configured to provide cardiac information signals; and

a computer-readable medium operatively couplable to the sensors, the computer-readable medium comprising instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by;

receiving cardiac information signals from a plurality of sensors during the complex rhythm disorder;

classifying the cardiac information signals into high and low confidence signals, wherein the high and low confidence signals are separated by a confidence threshold;

determining activation onsets associated with the low confidence signals within an acceptance window;

ordering the activation onsets associated with the low confidence signals and activation onsets associated with the high confidence signals; and

outputting the activation onsets associated with the high and low confidence signals to indicate a source of the complex cardiac rhythm disorder.

23. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining activation onsets associated with the low confidence signals using a wave path vector connecting at least two discernable activation onsets.

24. The assembly according to claim 22, wherein the complex rhythm disorder comprises no discernable period during which the cardiac information signals are quiescent.

25. The assembly according to claim 22, wherein the complex rhythm disorder comprises no discernable earliest activation onset associated with the cardiac information signals.

26. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by classifying the cardiac information signals into high and low confidence signals using at least one of activation onset, cycle length (CL), action potential duration (APD), and amplitude, wherein the activation onset is determined by using at least one of maximum dV/dt, template matching, frequency and amplitude.

27. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining the acceptance window using at least one of APD, conduction velocity (CV), fiber angle, wave path vector connecting at least two discernable activation onsets, and anatomic factors.

28. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by:

removing baseline wander and noise from the cardiac information signals; and

filtering the cardiac information signals.

29. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by disregarding at least one of the cardiac information signals using at least one of signal-to-noise ratio (SNR), template matching, frequency and amplitude.

30. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by template matching by identifying high-confidence level beats associated with the cardiac information signals as templates.

31. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by template matching using an expert system, the expert system using beat types to perform template matching.

32. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by classifying beats associated with the cardiac information signals based on a shape associated with the beats to be classified.

33. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by classifying beats associated with the cardiac information signals as high confidence beats in response to CL associated with the beat to be classified being greater than a minimum APD and less than a maximum CL.

34. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by classifying beats associated with the cardiac information signals as low confidence beats in response to CL associated with the beat to be classified being less than a minimum APD or greater than a maximum CL.

35. The assembly according to claim 23, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by modifying the wave path vector using at least one of beat shape, beat polarity, and surrounding rotating/radial emanation.

36. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining the acceptance window using an expert system, the expert system using at least one of APD, CV, wave path vector connecting at least two discernable activation onsets, frequency and fiber angle to determine the acceptance window.

37. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining activation onsets using an expert system, the expert system comprising wave shapes.

38. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining activation onsets associated with the low confidence signals using at least one of rolling average and phase lock.

39. The assembly according to claim 22, wherein the computer-readable medium comprises instructions, which when executed by a computing device, cause the computing device to reconstruct cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder by determining activation onsets associated with the low confidence signals using at least two of the wave path vector, acceptance window, rolling average, and phase lock.

40. The assembly according to claim 22, wherein the assembly further comprises:

at least one storage device configured to store the cardiac information signals from the catheter, the at least one storage device accessible to the computer-readable medium to provide the cardiac information signals to the computing device.

41. A method of reconstructing cardiac information representing a complex rhythm disorder associated with a patient'"'"'s heart to indicate a source of the complex rhythm disorder, the method comprising:

receiving cardiac information signals from a plurality of sensors during the complex rhythm disorder;

classifying, by a computing device, the cardiac information signals into high and low confidence signals, wherein the high and low confidence signals are separated by a confidence threshold;

determining, by the computing device, activation onsets associated with the low confidence signals within an acceptance window;

ordering, by the computing device, the activation onsets associated with the low confidence signals and activation onsets associated with the high confidence signals; and

outputting, by the computing device, the activation onsets associated with the high and low confidence signals to indicate a source of the complex cardiac rhythm disorder.

42. The method according to claim 41, wherein determining further comprises determining activation onsets associated with the low confidence signals using a wave path vector connecting at least two discernable activation onsets.

43. The method according to claim 41, wherein the complex rhythm disorder comprises no discernable period during which the cardiac information signals are quiescent.

44. The method according to claim 41, wherein the complex rhythm disorder comprises no discernable earliest activation onset associated with the cardiac information signals.

45. The method according to claim 41, wherein classifying further comprises using at least one of activation onset, cycle length (CL), action potential duration (APD), and amplitude to classify the cardiac information signals into high and low confidence signals, wherein the activation onset is determined by using at least one of maximum dV/dt, template matching, frequency and amplitude.

46. The method according to claim 41, wherein the acceptance window is determined using at least one of APD, conduction velocity (CV), fiber angle, wave path vector connecting at least two discernable activation onsets, and anatomic factors.

47. The method according to claim 41, further comprising:

removing baseline wander and noise from the cardiac information signals; and

filtering the cardiac information signals.

48. The method according to claim 41, further comprising disregarding at least one of the cardiac information signals using at least one of signal-to-noise ratio (SNR), template matching, frequency and amplitude.

49. The method according to claim 45, wherein template matching further comprises identifying high-confidence level beats associated with the cardiac information signals as templates.

50. The method according to claim 45, wherein template matching is performed using an expert system, the expert system using beat types to perform template matching.

51. The method according to claim 41, further comprising classifying beats associated with the cardiac information signals based on a shape associated with the beats to be classified.

52. The method according to claim 41, wherein classifying the cardiac information signals further comprises classifying beats associated with the cardiac information signals as high confidence beats in response to CL associated with the beat to be classified being greater than a minimum APD and less than a maximum CL.

53. The method according to claim 42, further comprising modifying the wave path vector using at least one of beat shape, beat polarity, and surrounding rotating/radial emanation.

54. The method according to claim 41, wherein classifying the cardiac information signals further comprises classifying beats associated with the cardiac information signals as low confidence beats in response to CL associated with the beat to be classified being less than a minimum APD or greater than a maximum CL.

55. The method according to claim 41, wherein determining the acceptance window further comprises using an expert system, the expert system using at least one of APD, CV, wave path vector connecting at least two discernable activation onsets, frequency and fiber angle to determine the acceptance window.

56. The method according to claim 41, wherein determining activation onsets further comprises using an expert system, the expert system comprising wave shapes.

57. The method according to claim 41, wherein determining activation onsets associated with the low confidence signals further comprises determining activation onsets using at least one of rolling average and phase lock.

58. The method according to claim 41, wherein determining activation onsets associated with the low confidence signals further comprises reconciling activation onsets determined by using at least two of the wave path vector, acceptance window, rolling average, and phase lock.

59. A system to reconstruct cardiac signals associated with a complex rhythm disorder received over a plurality of channels from a patient'"'"'s heart, the system comprising:

at least one computing device configured to;

identify a plurality of discernable beats on high-confidence channels that are adjacent to a low-confidence channel, the discernable beats on the high-confidence channels corresponding to a non-discernable beat on the low-confidence channel;

compute a vector between at least two activation onsets of the identified discernable beats on the adjacent channels through the non-discernable beat on the low-confidence channel;

define a time interval associated with the non-discernable beat about a region where the wave path crosses the non-discernable beat, the time interval indicating how early the non-discernable beat can activate based on a previous beat on the low-confidence channel that has a selected or determined activation onset and how late the non-discernable beat can terminate based on at least one predetermined property; and

select a possible activation onset during the defined time interval that is closest to the computed wave path for the non-discernable beat.

60. The system according to claim 59, wherein the possible activation onset is selected in association with a deflection or a quiescent period during the defined time interval.

61. The system according to claim 59, wherein the at least one computing device is further configured to:

determine a second time interval between discernable beats on the low-confidence channel occurring before the non-discernable beat, the interval extending from a first activation onset to a second activation onset of the respective discernable beats on the low-confidence channel;

advance the determined second time interval such that the first activation onset approximates the activation onset of a beat previous to the non-discernable beat;

reconcile the selected activation onset with the second activation onset to a reconciled activation onset; and

update the selected activation onset with the reconciled activation onset for the non-discernable beat.

62. The system according to claim 59, wherein the at least one computing device is further configured to:

classify high-confidence channels that include at least a predetermined percentage of discernable beats out of total beats, each discernable beat having an identifiable activation onset, and low-confidence channels that include a first number of discernable beats and a second number of non-discernable beats, each non-discernable beat having a plurality of deflections and quiescent periods associated with a possible activation onset, the first number of discernable beats being below the predetermined percentage.

63. The system according to claim 59, wherein the complex rhythm disorder comprises no discernable period during which the cardiac signals are quiescent.

64. The system according to claim 59, wherein the system further comprises:

at least one storage device configured to store the cardiac signals received from the patient'"'"'s heart, the at least one storage device operatively couplable to the at least one computing device to provide the cardiac signals to the at least one computing device.

65. The system according to claim 59, wherein the system further comprises:

a catheter comprising a plurality of sensors to receive the cardiac signals from the patient'"'"'s heart and operatively couplable to the at least one computing device provide the cardiac signals to the at least one computing device.

66. The system according to claim 59, wherein the at least one computing device comprises a computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform operations of the at least one computing device.

67. An assembly to reconstruct cardiac signals associated with a complex rhythm disorder received over a plurality of channels from a patient'"'"'s heart, the assembly comprising:

a catheter comprising a plurality of sensors to receive the cardiac signals; and

a computer-readable medium operatively couplable to the sensors, the computer-readable medium comprising instructions, which when executed by a computing device, cause the computing device to;

identify a plurality of discernable beats on high-confidence channels that are adjacent to a low-confidence channel, the discernable beats on the high-confidence channels corresponding to a non-discernable beat on the low-confidence channel;

compute a vector between at least two activation onsets of the identified discernable beats on the adjacent channels through the non-discernable beat on the low-confidence channel;

define a time interval associated with the non-discernable beat about a region where the defined vector crosses the non-discernable beat, the defined time interval indicating how early the non-discernable beat can activate based on a previous beat on the low-confidence channel that has a selected or determined activation onset and how late the non-discernable beat can terminate based on at least one predetermined property; and

select a possible activation onset during the defined time interval that is closest to the computed vector for the non-discernable beat.

68. The assembly according to claim 67, wherein the possible activation onset is selected in association with a deflection or a quiescent period during the defined time interval.

69. The assembly according to claim 67, wherein the computer-readable medium further comprises instructions, which when executed by the computing device, cause the computing device to:

determine a second time interval between discernable beats on the low-confidence channel occurring before the non-discernable beat, the interval extending from a first activation onset to a second activation onset of the respective discernable beats on the low-confidence channel;

advance the second time interval such that the first activation onset approximates the activation onset of a beat previous to the non-discernable beat;

reconcile the selected activation onset with the second activation onset to a reconciled activation onset; and

update the selected activation onset with the reconciled activation onset for the non-discernable beat.

70. The assembly according to claim 67, wherein the computer-readable medium further comprises instructions, which when executed by a computing device, cause the computing device to:

classify high-confidence channels that include at least a predetermined percentage of discernable beats out of total beats, each discernable beat having an identifiable activation onset, and low-confidence channels that include a first number of discernable beats and a second number of non-discernable beats, each non-discernable beat having a plurality of deflections and quiescent periods associated with a possible activation onset, the first number of discernable beats being below the predetermined percentage.

71. The assembly according to claim 67, wherein the complex rhythm disorder comprises no discernable period during which the cardiac signals are quiescent.

72. The assembly according to claim 67, wherein the assembly further comprises:

at least one storage device configured to store the cardiac signals received from the catheter, the at least one storage device accessible to the computer-readable medium to provide the cardiac signals to the computing device.

73. A method of reconstructing cardiac signals associated with a complex rhythm disorder received over a plurality of channels from a patient'"'"'s heart, the method comprising:

identifying a plurality of discernable beats on high-confidence channels that are adjacent to a low-confidence channel, the discernable beats on the high-confidence channels corresponding to a non-discernable beat on the low-confidence channel;

computing a vector between at least two activation onsets of the identified discernable beats on the adjacent channels through the non-discernable beat on the low-confidence channel;

defining a time interval associated with the non-discernable beat about a region where the vector crosses the non-discernable beat, the time interval indicating how early the non-discernable beat can activate based on a previous beat on the low-confidence channel that has a selected or determined activation onset and how late the non-discernable beat can terminate based on at least one predetermined property; and

selecting a possible activation onset during the defined time interval that is closest to the computed vector for the non-discernable beat.

74. The method according to claim 73, wherein the possible activation onset is selected in association with a deflection or a quiescent period during the defined time interval.

75. The method according to claim 73, wherein the method further comprises:

determining a second time interval between discernable beats on the low-confidence channel occurring before the non-discernable beat, the second time interval extending from a first activation onset to a second activation onset of the respective discernable beats on the low-confidence channel;

advancing the second time interval such that the first activation onset approximates the activation onset of a beat previous to the non-discernable beat;

reconciling the selected activation onset with the second activation onset to a reconciled activation onset; and

updating the selected activation onset with the reconciled activation onset for the non-discernable beat.

76. The method according to claim 73, wherein the method further comprises:

classifying high-confidence channels that include at least a predetermined percentage of discernable beats out of total beats, each discernable beat having an identifiable activation onset, and low-confidence channels that include a first number of discernable beats and a second number of non-discernable beats, each non-discernable beat having a plurality of deflections and quiescent periods associated with a possible activation onset, the first number of discernable beats being below the predetermined percentage.