METHOD AND APPARATUS FOR DISCRIMINATING CARDIAC SIGNALS IN A MEDICAL DEVICE BASED ON WAVELET DECOMPOSITION ANALYSIS

• US 20070260153A1
• Filed: 05/04/2007
• Published: 11/08/2007
• Est. Priority Date: 05/05/2006
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Ghanem, Raja N., Jackson, Troy E.
• Granted Patent: US 7,774,063 B2
• Time in Patent Office: Days
• US Class Current: 600/510
• CPC Class Codes: A61B 5/276 Protection against electrode failure
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61N 1/3706 Pacemaker parameters stimulation threshold A61N1/371
• CPC Class Codes: G06F 2218/12 Classification; Matching

Abstract

A method and device for detecting cardiac signals in a medical device that includes decomposing sensed cardiac signals using a wavelet function to form a corresponding wavelet transform, generating a first wavelet representation corresponding to the wavelet transform that is responsive to RR intervals of the sensed cardiac signals, generating a second wavelet representation that is not responsive to RR intervals associated with the sensed cardiac signals, determining a no lead failure zone in response to the first wavelet representation and the second wavelet representation, and distinguishing the cardiac event from a device failure in response to the determined no lead failure zone. The method and device may also include generating a wavelet representation corresponding to the wavelet transform that is not responsive to RR intervals of the sensed cardiac signals, determining RR intervals associated with the sensed cardiac signals, and determining a no lead failure zone in response to the wavelet representation and the determined RR intervals.

Claims

1. A method of detecting cardiac signals in a medical device, comprising:

sensing cardiac signals to identify a predetermined cardiac event;

decomposing the sensed cardiac signals using a wavelet function to form a corresponding wavelet transform;

generating a first wavelet representation corresponding to the wavelet transform, the first wavelet representation being responsive to RR intervals of the sensed cardiac signals;

generating a second wavelet representation corresponding to the wavelet transform, the second wavelet representation not being responsive to RR intervals associated with the sensed cardiac signals;

determining a no lead failure zone in response to the first wavelet representation and the second wavelet representation; and

distinguishing the cardiac event from a device failure in response to the determined no lead failure zone.

2. The method of claim 1, wherein the wavelet transform is a Haar wavelet transform, the first wavelet representation corresponds to a detail sequence, and the second wavelet representation corresponds to an approximation sequence.

3. The method of claim 1, wherein the wavelet transform is a Haar wavelet transform and the sensed cardiac signals are decomposed at a plurality of scales, the method further comprising:

determining approximation coefficients and detail coefficients in response to the plurality of scales;

reconstructing the second wavelet representation using predetermined approximation coefficients of the determined approximation coefficients; and

reconstructing the first wavelet representation using predetermined detail coefficients of the determined detail coefficients, wherein the no lead failure zone is defined by a first boundary associated with the reconstructed first wavelet representation and a second boundary associated with the reconstructed second wavelet representation.

4. The method of claim 3, wherein the first boundary is determined in response to one of a mean absolute difference and a dispersion of RR intervals of the reconstructed first wavelet representation and the second boundary is determined in response to one of a mean rectified amplitude, a mean absolute difference, and a dispersion of the reconstructed second wavelet representation.

5. The method of claim 3, wherein the predetermined approximation coefficients correspond to a coarsest scale of the plurality of scales and the detail coefficients correspond to a finest scale of the plurality of scales.

6. The method of claim 5, wherein the approximation coefficients are determined at a fourth scale of the plurality of scales and the detail coefficients are determined at a first scale of the plurality of scales.

7. The method of claim 3, wherein the detail coefficients are determined at a first scale of the plurality of scales to form a first detail sequence and a second scale of the plurality of scales to form a second detail sequence, and wherein the first wavelet representation is reconstructed in response to a sum of the first detail sequence and the second detail sequence.

8. A method of detecting cardiac signals in a medical device, comprising:

sensing cardiac signals;

decomposing the sensed cardiac signals using a wavelet function to form a corresponding wavelet transform;

generating a wavelet representation corresponding to the wavelet transform, the wavelet representation not being responsive to RR intervals of the sensed cardiac signals;

determining RR intervals associated with the sensed cardiac signals;

determining a no lead failure zone in response to the wavelet representation and the determined RR intervals; and

distinguishing the cardiac event from a device failure in response to the determined no lead failure zone.

9. The method of claim 8, wherein the wavelet transform is a Haar wavelet transform and the wavelet representation corresponds to an approximation sequence.

10. The method of claim 8, wherein the wavelet transform is a Haar wavelet transform and the sensed cardiac signals are decomposed at a plurality of scales, the method further comprising:

determining approximation coefficients in response to the plurality of scales; and

reconstructing the wavelet representation using predetermined approximation coefficients of the determined approximation coefficients, wherein the no lead failure zone is defined by a first boundary associated with the reconstructed wavelet representation and a second boundary associated with the determined RR intervals.

11. The method of claim 10, wherein the first boundary is determined in response to one of a mean rectified amplitude, a mean absolute difference, and a dispersion of the reconstructed wavelet representation and the second boundary is determined in response to one of a mean absolute difference and a dispersion of the determined RR intervals.

12. The method of claim 10, wherein the predetermined approximation coefficients correspond to a coarsest scale of the plurality of scales.

22. The device of claim 11, wherein the wavelet transform is a Haar wavelet transform and the sensed cardiac signals are decomposed at a plurality of scales, the device further comprising:

means for determining approximation coefficients in response to the plurality of scales; and

means for reconstructing the wavelet representation using predetermined approximation coefficients of the determined approximation coefficients, wherein the no lead failure zone is defined by a first boundary associated with the reconstructed wavelet representation and a second boundary associated with the determined RR intervals.

23. The device of claim 22, wherein the first boundary is determined in response to one of a mean rectified amplitude, a mean absolute difference, and a dispersion of the reconstructed wavelet representation and the second boundary is determined in response to one of a mean absolute difference and a dispersion of the determined RR intervals.

24. The device of claim 22, wherein the predetermined approximation coefficients correspond to a coarsest scale of the plurality of scales.

13. A medical device, comprising:

means for sensing cardiac signals to identify a predetermined cardiac event;

means for decomposing the sensed cardiac signals using a wavelet function to form a corresponding wavelet transform;

means for generating a first wavelet representation corresponding to the wavelet transform, the first wavelet representation being responsive to RR intervals of the sensed cardiac signals;

means for generating a second wavelet representation corresponding to the wavelet transform, the second wavelet representation not being responsive to RR intervals associated with the sensed cardiac signals;

means for determining a no lead failure zone in response to the first wavelet representation and the second wavelet representation; and

means for distinguishing the cardiac event from a device failure in response to the determined no lead failure zone.

14. The device of claim 13, wherein the wavelet transform is a Haar wavelet transform, the first wavelet representation corresponds to a detail sequence, and the second wavelet representation corresponds to an approximation sequence.

15. The device of claim 13, wherein the wavelet transform is a Haar wavelet transform and the sensed cardiac signals are decomposed at a plurality of scales, the device further comprising:

means for determining approximation coefficients and detail coefficients in response to the plurality of scales;

means for reconstructing the second wavelet representation using predetermined approximation coefficients of the determined approximation coefficients; and

means for reconstructing the first wavelet representation using predetermined detail coefficients of the determined detail coefficients, wherein the no lead failure zone is defined by a first boundary associated with the reconstructed first wavelet representation and a second boundary associated with the reconstructed second wavelet representation.

16. The device of claim 15, wherein the first boundary is determined in response to one of a mean absolute difference and a dispersion of RR intervals of the reconstructed first wavelet representation and the second boundary is determined in response to one of a mean rectified amplitude, a mean absolute difference, and a dispersion of the reconstructed second wavelet representation.

17. The device of claim 15, wherein the predetermined approximation coefficients correspond to a coarsest scale of the plurality of scales and the detail coefficients correspond to a finest scale of the plurality of scales.

18. The device of claim 17, wherein the approximation coefficients are determined at a fourth scale of the plurality of scales and the detail coefficients are determined at a first scale of the plurality of scales.

19. The device of claim 15, wherein the detail coefficients are determined at a first scale of the plurality of scales to form a first detail sequence and a second scale of the plurality of scales to form a second detail sequence, and wherein the first wavelet representation is reconstructed in response to a sum of the first detail sequence and the second detail sequence.

20. A medical device, comprising:

means for sensing cardiac signals;

means for decomposing the sensed cardiac signals using a wavelet function to form a corresponding wavelet transform;

means for generating a wavelet representation corresponding to the wavelet transform, the wavelet representation not being responsive to RR intervals of the sensed cardiac signals;

means for determining RR intervals associated with the sensed cardiac signals;

means for determining a no lead failure zone in response to the wavelet representation and the determined RR intervals; and

means for distinguishing the cardiac event from a device failure in response to the determined no lead failure zone.

21. The device of claim 20, wherein the wavelet transform is a Haar wavelet transform and the wavelet representation corresponds to an approximation sequence.