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. 2007 Apr;37(4):517-23.
doi: 10.1016/j.compbiomed.2006.08.003. Epub 2006 Oct 2.

Wavelet transform analysis predicts outcome of DC cardioversion for atrial fibrillation patients

J N Watson  1 , P S Addison, N Uchaipichat, A S Shah, N R Grubb
Affiliations

Wavelet transform analysis predicts outcome of DC cardioversion for atrial fibrillation patients

J N Watson et al. Comput Biol Med. 2007 Apr.

Abstract

The aim of this study was to examine whether wavelet transform analysis of the electrocardiogram (ECG) can improve the prediction of the maintenance of sinus rhythm in patients with atrial fibrillation (AF) after external DC cardioversion. We examined a variety of wavelet transform-based statistical markers as potential candidates for the prediction of patient status post-cardioversion. Considering a 'success' as a patient who remains in normal sinus rhythm for one month post cardioversion and 'failure' as a patient who does not, it was shown the proposed non-parametric classification system can achieve 89% specificity at 100% sensitivity using a non-parametric classification method.

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