Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
505766 | Computers in Biology and Medicine | 2007 | 7 Pages |
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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Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
J.N. Watson, P.S. Addison, N. Uchaipichat, A.S. Shah, N.R. Grubb,