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

• US 20070270912A1
• Filed: 05/04/2007
• Published: 11/22/2007
• 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 8,676,289 B2
• Time in Patent Office: Days
• US Class Current: 607/9
• 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 of detecting cardiac signals in a medical device that includes decomposing a cardiac signal using a wavelet function at a plurality of scales to form a corresponding wavelet transform, determining approximation coefficients in response to the plurality of scales, reconstructing a first wavelet representation of the wavelet transform using predetermined approximation coefficients of the determined approximation coefficients, and evaluating the detected cardiac signals in response to the reconstructing.

Claims

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

decomposing a cardiac signal using a first wavelet function at a first plurality of scales to form a corresponding wavelet transform;

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

comparing dispersion associated with the determined first approximation coefficients.

2. The method of claim 1, further comprising reconstructing a wavelet representation of the wavelet transform using predetermined approximation coefficients of the determined first approximation coefficients, wherein the comparing is in response to the reconstructed wavelet representation.

3. The method of claim 1, further comprising:

decomposing the cardiac signal using a second wavelet function at a second plurality of scales to form a corresponding second wavelet transform;

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

comparing dispersion associated with the determined second approximation coefficients.

4. The method of claim 3, further comprising reconstructing a wavelet representation of the second wavelet transform using predetermined approximation coefficients of the determined second approximation coefficients, wherein the comparing dispersion associated with the determined second approximation coefficients is in response to the reconstructed wavelet representation of the second wavelet transform.

5. The method of claim 4, further comprising analyzing the compared dispersion associated with the reconstructed wavelet representation of the first wavelet transform and the reconstructed wavelet representation of the second wavelet transform.

6. The method of claim 3, wherein the first approximation coefficients are different than the second approximation coefficients.

7. The method of claim 1, further comprising:

identifying the cardiac signal as being associated with ventricular fibrillation in response to the compared dispersion being less than a dispersion threshold; and

identifying the cardiac signal as being associated with a corruption of a lead in response to the compared dispersion not being less than the dispersion threshold.

8. The method of claim 1, wherein the wavelet function corresponds to a Haar wavelet.

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

decomposing a cardiac signal using a wavelet function at a plurality of scales to form a corresponding wavelet transform;

determining approximation coefficients in response to the plurality of scales;

reconstructing a first wavelet representation of the wavelet transform using predetermined approximation coefficients of the determined approximation coefficients; and

evaluating the detected cardiac signals in response to the reconstructing.

10. The method of claim 9, further comprising:

determining detail coefficients; and

reconstructing a second wavelet representation of the wavelet transform using predetermined detail coefficients of the determined detail coefficients.

11. The method of claim 10, 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.

12. The method of 9, wherein the wavelet function corresponds to Haar wavelet.

13. The method of claim 12, 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.

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

decomposing a cardiac signal using a wavelet function at a plurality of scales to form a corresponding wavelet transform;

determining approximation coefficients in response to the plurality of scales;

reconstructing a first wavelet representation of the wavelet transform using predetermined approximation coefficients of the determined first approximation coefficients;

determining detail coefficients in response to the plurality of scales;

reconstructing a second wavelet representation of the wavelet transform using predetermined detail coefficients of the determined detail coefficients; and

identifying the cardiac signal as being associated with a corruption of a lead in response to the reconstructed first wavelet and the reconstructed second wavelet representations.

15. The method of claim 14, 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.

16. The method of 14, wherein the wavelet function corresponds to Haar wavelet.

17. The method of claim 16, 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.