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Entropy 2015, 17(9), 6179-6199; doi:10.3390/e17096179

Wavelet Entropy Automatically Detects Episodes of Atrial Fibrillation from Single-Lead Electrocardiograms

1
Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Albacete 02071, Spain
2
Biomedical Synergy, Universidad Politécnica de Valencia, Gandía 46730, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Kevin H. Knuth
Received: 15 June 2015 / Revised: 15 August 2015 / Accepted: 28 August 2015 / Published: 7 September 2015
(This article belongs to the Special Issue Wavelet Entropy: Computation and Applications)
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Abstract

This work introduces for the first time the application of wavelet entropy (WE) to detect episodes of the most common cardiac arrhythmia, atrial fibrillation (AF), automatically from the electrocardiogram (ECG). Given that AF is often asymptomatic and usually presents very brief initial episodes, its early automatic detection is clinically relevant to improve AF treatment and prevent risks for the patients. After discarding noisy TQ intervals from the ECG, the WE has been computed over the median TQ segment obtained from the 10 previous noise-free beats under study. In this way, the P-waves or the fibrillatory waves present in the recording were highlighted or attenuated, respectively, thus enabling the patient’s rhythm identification (sinus rhythm or AF). Results provided a discriminant ability of about 95%, which is comparable to previous works. However, in contrast to most of them, which are mainly based on quantifying RR series variability, the proposed algorithm is able to deal with patients under rate-control therapy or with a reduced heart rate variability during AF. Additionally, it also presents interesting properties, such as the lowest delay in detecting AF or sinus rhythm, the ability to detect episodes as brief as five beats in length or its integration facilities under real-time beat-by-beat ECG monitoring systems. Consequently, this tool may help clinicians in the automatic detection of a wide variety of AF episodes, thus gaining further knowledge about the mechanisms initiating this arrhythmia. View Full-Text
Keywords: atrial fibrillation; electrocardiogram; wavelet entropy; wavelet transform atrial fibrillation; electrocardiogram; wavelet entropy; wavelet transform
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. (CC BY 4.0).

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MDPI and ACS Style

Ródenas, J.; García, M.; Alcaraz, R.; Rieta, J.J. Wavelet Entropy Automatically Detects Episodes of Atrial Fibrillation from Single-Lead Electrocardiograms. Entropy 2015, 17, 6179-6199.

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