Automatic orientation determination for ECG measurements using multiple electrodes

• US 7,706,866 B2
• Filed: 06/24/2004
• Issued: 04/27/2010
• Est. Priority Date: 06/24/2004
• Status: Expired due to Fees

• 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
• Primary Examiner(s): Layno; Carl H
• Assistant Examiner(s): Behringer; Luther G
• Application Number:
  US10/876,008
• Publication Number:
  US 20050288600A1
• Time in Patent Office: 2,133 Days
• Field of Search: 600/509, 600/511, 600/512, 600/513
• US Class Current: 600/512
• 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 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, the target vector representative of a signal vector of the set of signal vectors associated with higher quality cardiac data relative to other signal vectors of the set of signal vectors;

detecting a change in a predetermined condition or an event occurrence indicating that changing which vector of the set of signal vectors is selected as the target vector may be useful in sensing cardiac activity; and

updating, in response to the change in the predetermined condition or event occurrence, selection of the target vector to update the target vector by performing a subsequent source separation on the detected plurality of composite signals and reselecting the same or a different vector associated with higher quality cardiac data relative to other signal vectors of the set of signal vectors as the target vector based on the subsequent source separation.

2. The method of claim 1, wherein the target vector is selected at least in part by identifying the target signal as a cardiac signal.

3. The method of claim 1, 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.

4. The method of claim 1, 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.

5. The method of claim 1, 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.

6. The method of claim 1, 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.

7. The method of claim 1, wherein updating the target vector is performed in response to detection of a pathologic change.

8. The method of claim 1, wherein updating the target vector is performed in response to detection of a change in orientation of a patient-internal medical device.

9. The method of claim 1, wherein updating the target vector is performed in response to exceeding an arrhythmia detection rate zone or threshold.

10. The method of claim 1, wherein updating the target vector is performed in response to detection of a change inpatient activity level.

11. The method of claim 1, wherein updating the target vector is performed in response to detection of a postural change.

12. The method of claim 1, wherein updating the target vector is performed in response to detection of a therapy change.

13. The method of claim 1, wherein the target vector is updated in response to detection of an activation stimulus.

14. The method of claim 1, wherein the target vector is updated periodically.

15. The method of claim 1, wherein updating the target vector is performed in response to a change of a signal to noise ratio of the target signal.

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

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

18. The method of claim 17, further comprising performing a principal component analysis on the spatial covariance matrix for the detected plurality of composite signals.

19. The method of claim 1, further comprising performing an independent component analysis on the detected plurality of composite signals.

20. The method of claim 1, further comprising performing a principal component analysis and an independent component analysis on the detected plurality of composite signals.

21. 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, the target vector associated with higher quality cardiac data relative to other vectors;

means for characterizing cardiac activity using the target signal; and

means for updating the target vector by initiating a subsequent source separation and selecting the same or a different vector as the target vector based on the subsequent source separation in response to detection of a change in a predetermined condition or an event occurrence indicating that use of the target vector may result in less than optimal sensing of cardiac activity.

22. The device of claim 21, wherein the separating means performs a principal component analysis on the detected plurality of composite signals.

23. The device of claim 21, 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.

24. The device of claim 21, 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.

25. The device of claim 21, further comprising means for identifying the separated target signal as a cardiac signal.

26. The device of claim 25, further comprising means for detecting a cardiac condition using the cardiac signal.

27. The device of claim 26, further comprising means for treating the cardiac condition.