Biomedical signal analysis techniques using wavelets

• US 20040210147A1
• Filed: 04/16/2003
• Published: 10/21/2004
• Est. Priority Date: 04/16/2003
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Houben, Richard P.M.
• Granted Patent: US 7,082,327 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06F 2218/00 Aspects of pattern recognition specially adapted for signal processing

Abstract

The invention is directed to signal processing techniques for electrograms or other biomedical signals. In particular, the signal processing techniques make use of wavelet transformation of the electrograms. For example, an electrogram can be represented by a finite set of wavelets which comprise a decomposition of the electrogram in the scale-time domain. In accordance with the invention, wavelet analysis techniques can be used to distinguish specific phenomena in electrograms. For example, wavelet analysis can be used to distinguish between occurrences of large amplitude steep deflections, small amplitude steep deflections, and large amplitude shallow deflections of an electrogram.

Claims

1. An implantable medical device comprising:

a wavelet transform unit to convert an electrogram into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

a wavelet analysis unit to identify features of the electrogram based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

2. The implantable medical device of claim 1, wherein the electrogram comprises a digital electrogram, the medical device further comprising an analog-to-digital converter to convert an analog electrogram to the digital electrogram, wherein the wavelet transform unit converts the digital electrogram into the set of wavelet and the wavelet analysis unit distinguishes features of the digital electrogram.

3. The implantable medical device of claim 1, further comprising a digital signal processor, wherein the wavelet transform unit and the wavelet analysis unit comprise software modules executed by the digital signal processor.

4. The implantable medical device of claim 1, further comprising one or more electrodes to sense the electrogram.

5. The implantable medical device of claim 1, wherein the medical device comprises one of an external medical device and an implanted medical device.

6. The implantable medical device of claim 1, wherein the medical device receives the electrogram from another medical device via telemetry.

7. The implantable medical device of claim 1, wherein wavelets in the coarse scale have a scale factor greater than or equal to 10 multiplied by a scale factor associated with wavelets in the fine scale.

8. The implantable medical device of claim 1, wherein the wavelet analysis unit identifies a particular feature in the electrogram as a large amplitude steep deflection when the particular feature appears in the fine and coarse scale wavelets.

9. The implantable medical device of claim 1, wherein the wavelet analysis unit identifies a particular feature in the electrogram as a small amplitude steep deflection when the particular feature appears in the fine scales wavelets but not the coarse scale wavelets.

10. The implantable medical device of claim 1, wherein the wavelet analysis unit identifies a particular feature in the electrogram as a large amplitude shallow deflection when the particular feature appears in the coarse scale wavelets but not the fine scale wavelets.

11. The implantable medical device of claim 1, wherein the electrogram comprises an atrial electrocardiogram, wherein the wavelet analysis unit:

identifies a first feature in the atrial electrocardiogram as an indication of primary near field depolarization when the first feature appears in the fine and coarse scale wavelets;

identifies a second feature in the atrial electrocardiogram as a secondary near field depolarization when the second feature appears in the fine scales wavelets but not the coarse scale wavelets; and

identifies a third feature in the atrial electrocardiogram as a far field primary depolarization when the third feature appears in the coarse scale wavelets but not the fine scale wavelets.

12. An implantable medical device comprising:

a wavelet transform unit to convert a biomedical signal into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

a wavelet analysis unit to identify features of the biomedical signal based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

13. A method comprising:

converting an electrogram into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

identifying features of the electrogram based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

14. The method of claim 13, wherein wavelets in the coarse scale have scale factors greater than or equal to 10 multiplied by a scale factor associated with wavelets in the fine scale.

15. The method of claim 13, further comprising identifying a particular feature in the electrogram as a large amplitude steep deflection when the particular feature appears in the fine and coarse scale wavelets.

16. The method of claim 13, further comprising identifying a particular feature in the electrogram as a small amplitude steep deflection when the particular feature appears in the fine scales wavelets but not the coarse scale wavelets.

17. The method of claim 13, further comprising identifying a particular feature in the electrogram as a large amplitude shallow deflection when the particular feature appears in the coarse scale wavelets but not the fine scale wavelets.

18. The method of claim 13, wherein the electrogram comprises an atrial electrocardiogram, and identifying features further comprises:

identifying a first feature in the atrial electrocardiogram as an indication of primary near field depolarization when the first feature appears in the fine and coarse scale wavelets;

identifying a second feature in the atrial electrocardiogram as a secondary near field depolarization when the second feature appears in the fine scales wavelets but not the coarse scale wavelets; and

identifying a third feature in the atrial electrocardiogram as a far field primary depolarization when the third feature appears in the coarse scale wavelets but not the fine scale wavelets.

19. A computer readable medium comprising computer readable instructions that when executed:

convert an electrogram into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

identify features of the electrogram based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

20. The computer readable medium of claim 19, wherein wavelets in the coarse scale have a scale factor greater than or equal to 10 multiplied by a scale factor associated with wavelets in the fine scale.

21. The computer readable medium of claim 19, further comprising computer readable instructions that when executed identify a particular feature in the electrogram as a large amplitude steep deflection when the particular feature appears in the fine and coarse scale wavelets.

22. The computer readable medium of claim 19, further comprising computer readable instructions that when executed identify a particular feature in the electrogram as a small amplitude steep deflection when the particular feature appears in the fine scales wavelets but not the coarse scale wavelets.

23. The computer readable medium of claim 19, further comprising computer readable instructions that when executed identify a particular feature in the electrogram as a large amplitude shallow deflection when the particular feature appears in the coarse scale wavelets but not the fine scale wavelets.

24. The computer readable medium of claim 19, wherein the electrogram comprises an atrial electrocardiogram, further comprising computer readable instructions that when executed:

identify a first feature in the atrial electrocardiogram as an indication of primary near field depolarization when the first feature appears in the fine and coarse scale wavelets;

identify a second feature in the atrial electrocardiogram as a secondary near field depolarization when the second feature appears in the fine scales wavelets but not the coarse scale wavelets; and

identify a third feature in the atrial electrocardiogram as a far field primary depolarization when the third feature appears in the coarse scale wavelets but not the fine scale wavelets.

25. An apparatus comprising:

means for converting an electrogram into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

means for identifying features of the electrogram based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

26. The apparatus of claim 25, further comprising means for identifying a particular feature in the electrogram as a large amplitude steep deflection when the particular feature appears in the fine and coarse scale wavelets.

27. The apparatus of claim 25, further comprising means for identifying a particular feature in the electrogram as a small amplitude steep deflection when the particular feature appears in the fine scales wavelets but not the coarse scale wavelets.

28. The apparatus of claim 25, further comprising means for identifying a particular feature in the electrogram as a large amplitude shallow deflection when the particular feature appears in the coarse scale wavelets but not the fine scale wavelets.

29. A method comprising:

converting an biomedical signal into a set of wavelets, the set of wavelets including wavelets at a fine scale and wavelets at a coarse scale; and

identifying features of the biomedical signal based on whether the features appear in only the fine scale wavelets, only the coarse scale wavelets or both the fine and coarse scale wavelets.

30. The method of claim 29, wherein the biomedical signal comprises a signal selected from the group consisting of:

an electrogram measured via external sensors, an electrogram measured via implanted sensors, and a signal measured by a biomedical sensor.