3 research outputs found

    Real-Time Cardiac Arrhythmia Detection Using WOLA Filterbank Analysis of EGM Signals

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    <p/> <p>Novel methods of cardiac rhythm detection are proposed that are based on time-frequency analysis by a weighted overlap-add (WOLA) oversampled filterbank. Cardiac signals are obtained from intracardiac electrograms and decomposed into the time-frequency domain and analyzed by parallel peak detectors in selected frequency subbands. The coherence (synchrony) of the subband peaks is analyzed and employed to detect an optimal peak sequence representing the beat locations. By further analysis of the synchrony of the subband beats and the periodicity and regularity of the optimal beat, various possible cardiac events (including fibrillation, flutter, and tachycardia) are detected. The Ann Arbor Electrogram Library is used to evaluate the proposed detection method in clean and in additive noise. The evaluation results show that the method never misses any episode of fibrillation or flutter in clean or in noise and is robust to far-field R-wave interference. Furthermore, all other misclassification errors were within the acceptable limits.</p

    Research Article Real-Time Cardiac Arrhythmia Detection Using WOLA Filterbank Analysis of EGM Signals

    No full text
    Novel methods of cardiac rhythm detection are proposed that are based on time-frequency analysis by a weighted overlap-add (WOLA) oversampled filterbank. Cardiac signals are obtained from intracardiac electrograms and decomposed into the timefrequency domain and analyzed by parallel peak detectors in selected frequency subbands. The coherence (synchrony) of the subband peaks is analyzed and employed to detect an optimal peak sequence representing the beat locations. By further analysis of the synchrony of the subband beats and the periodicity and regularity of the optimal beat, various possible cardiac events (including fibrillation, flutter, and tachycardia) are detected. The Ann Arbor Electrogram Library is used to evaluate the proposed detection method in clean and in additive noise. The evaluation results show that the method never misses any episode of fibrillation or flutter in clean or in noise and is robust to far-field R-wave interference. Furthermore, all other misclassification errors were within the acceptable limits. Copyright © 2007 Hamid Sheikhzadeh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1
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