Morphological Autoencoders for Beat-by-Beat Atrial Fibrillation Detection Using Single-Lead ECG

Engineered feature extraction can compromise the ability of Atrial Fibrillation (AFib) detection algorithms to deliver near real-time results. Autoencoders (AEs) can be used as an automatic feature extraction tool, tailoring the resulting features to a specific classification task. By coupling an en...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 23; no. 5; p. 2854
Main Authors:	Silva, Rafael, Fred, Ana, Plácido da Silva, Hugo
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01.03.2023 MDPI
Subjects:	Accuracy Algorithms Atrial fibrillation Atrial Fibrillation - diagnosis atrial fibrillation detection automatic feature extraction Cardiac arrhythmia Classification Data compression Diagnosis ECG morphological features Electrocardiogram Electrocardiography Electrocardiography - methods Embedded systems Feature selection Heart Heart Rate Humans Monitoring systems Morphology Neural networks Signal Processing, Computer-Assisted supervised autoencoder Wavelet transforms Portugal ECG morphological features atrial fibrillation detection automatic feature extraction supervised autoencoder
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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