Methods and apparatus for discriminating polymorphic tachyarrhythmias from monomorphic tachyarrhythmias facilitating detection of fibrillation

• US 8,332,022 B2
• Filed: 09/25/2006
• Issued: 12/11/2012
• Est. Priority Date: 08/29/2003
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Brown, Mark L., Sarkar, Shantanu
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): OROPEZA, FRANCES P
• Application Number:
  US11/534,927
• Publication Number:
  US 20070016257A1
• Time in Patent Office: 2,269 Days
• Field of Search: 607/4, 607/5, 607/14, 600515-518
• US Class Current: 600/515
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61N 1/3622 comprising two or more electrodes co-operating with different heart regions
• CPC Class Codes: A61N 1/3956 Implantable devices for applying electric shocks to the heart, e.g. for cardioversion

Abstract

Methods and apparatus are provided for discriminating high rate polymorphic QRS complexes from high rate monomorphic QRS complexes to increase the specificity of detection of polymorphic VT and VF employing wavelet transform signal processing of the QRS complexes are disclosed. Wavelet transforms are applied to the sampled amplitude values of a sequence of QRS complexes to develop wavelet transform coefficient (WTC) data sets. At least selected ones of the WTC data sets are processed and comparisons are made to determine a wavelet match score. A determination is made as a function of the wavelet match scores of the series of successive QRS complexes that characterizes the most recent QRS complex as more or less likely to signify polymorphic VT or VF.

Claims

1. A method of discriminating between a monomorphic tachyarrhythmia and a polymorphic tachyarrhythmia of a heart of a patient having a cardiac signal, comprising the steps of:

first deriving a plurality of data sets of signal amplitudes of at least a first number of measured time intervals of the cardiac signal satisfying a polymorphic tachyarrhythmia detection criteria;

then

deriving a corresponding plurality of sets of wavelet transform coefficients from the plurality of data sets of signal amplitudes;

comparing at least selected ones of the wavelet transform coefficients of each of the plurality of sets of wavelet transform coefficients to determine a match count of the plurality of sets of wavelet transform coefficients that match at least one other of the plurality of sets of wavelet transform coefficients within a predetermined match tolerance;

then

declaring a monomorphic tachyarrhythmia if the match count is greater than a morphologic stability threshold; and

declaring a polymorphic tachyarrhythmia if the match count is less than a morphologic stability threshold.

2. The method of claim 1, further comprising returning to the deriving step after the declaring a polymorphic tachyarrhythmia step.

3. The method of claim 2, further comprising the step of delivering a cardioversion/defibrillation therapy based upon a declaration of a polymorphic tachyarrhythmia.

4. The method of claim 2, wherein the deriving a plurality of wavelet transform coefficients step further comprises:

establishing a withhold count corresponding to z measured time intervals between sensed events of successive cardiac signals; and

wherein the deriving a plurality of data sets of signal amplitudes step, the deriving a plurality of wavelet transform coefficient step, and the comparing step are repeated at least z times.

5. The method of claim 2:

wherein the declaring a monomorphic tachyarrhythmia step further comprises establishing a withhold count corresponding to z measured time intervals between sensed events of successive cardiac signals;

wherein the deriving a plurality of data sets of signal amplitudes step, the deriving a plurality of wavelet transform coefficient step, and the comparing step are repeated at least z times; and

further comprising the step of;

delivering a cardioversion/defibrillation therapy upon declaration of a polymorphic tachyarrhythmia.

6. The method of claim 2, further comprising:

delivering a cardioversion/defibrillation therapy based upon a declaration of a polymorphic tachyarrhythmia; and

delivering an anti-tachycardia therapy based upon a declaration of a monomorphic tachyarrhythmia.

7. The method of claim 1, further comprising:

delivering a cardioversion/defibrillation therapy based upon a declaration of a polymorphic tachyarrhythmia; and

delivering an anti-tachycardia therapy based upon a declaration of a monomorphic tachyarrhythmia.

8. The method of claim 1, wherein the comparing step comprises:

comparing at least certain wavelet transform coefficients of the plurality of wavelet transform coefficients among the plurality of sets of wavelet transform coefficients to at least certain wavelet transform coefficients of a preceding plurality of sets of wavelet transform coefficients and determining corresponding match values representing the degree that the compared wavelet coefficients of the plurality of sets of wavelet transform coefficients match the wavelet transform coefficients of the preceding plurality of sets of wavelet transform coefficients;

comparing each of the corresponding match values to a match count threshold; and

determining a corresponding match count of the corresponding match values that meet the match count threshold.

9. The method of claim 1, wherein the comparing step comprises:

comparing individual ones of the wavelet transform coefficients to individual ones of a prior set of wavelet transform coefficients and determining a match value representing a degree that the individual ones of the wavelet transform coefficients match the individual ones of the prior set of wavelet transform coefficients;

accumulating a plurality of match values;

comparing each of the plurality of values to a match count threshold; and

determining a match count of the plurality of match values that meet the match count threshold.

10. The method of claim 1, wherein the comparing step comprises:

determining m median wavelet transform coefficient magnitudes from the wavelet transform coefficients in each of a preceding plurality of wavelet transform coefficient data sets preceding a current wavelet transform coefficient data set having p wavelet transform coefficient magnitudes;

ordering the m median wavelet transform coefficient magnitudes into a plurality of scales;

comparing the median wavelet transform coefficient magnitudes in each scale to one of a plurality of scale thresholds corresponding to an individual one of the plurality of scales to derive a subset of median wavelet transform coefficient magnitudes m_i that meet the one of the plurality of scale thresholds;

determining a subset of wavelet transform coefficient magnitudes p_i each corresponding in a wavelet number to wavelet numbers of the subset of median wavelet transform coefficient magnitudes m_i; and

deriving a selective wavelet coefficient stability index (SWCSI) equal to the match count by the equation;

11. The method of claim 10, further comprising determining the one of the plurality of scale thresholds of each individual one of the plurality of scales as a percentage of an absolute maximum median wavelet transform coefficient magnitude in the individual one of the plurality of scales.