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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Vydané v:	Sensors (Basel, Switzerland) Ročník 23; číslo 5; s. 2854
Hlavní autori:	Silva, Rafael, Fred, Ana, Plácido da Silva, Hugo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.03.2023 MDPI
Predmet:	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
On-line prístup:	Získať plný text
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