Deep Learning-Based Stacked Denoising and Autoencoder for ECG Heartbeat Classification

The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds of noise. Such noise may cause deformation on the ECG heartbeat waveform, leading to cardiologists’ mislabeling or misinterpreting heartbeats...

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Vydané v:	Electronics (Basel) Ročník 9; číslo 1; s. 135
Hlavní autori:	Nurmaini, Siti, Darmawahyuni, Annisa, Sakti Mukti, Akhmad Noviar, Rachmatullah, Muhammad Naufal, Firdaus, Firdaus, Tutuko, Bambang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.01.2020
Predmet:	Arrhythmia Artificial neural networks Automation Bias Classification Deep learning Discriminant analysis Electrocardiography Feature extraction Machine learning Neural networks Noise reduction Principal components analysis Representations Signal processing Signal to noise ratio Training Waveforms Wavelet transforms
ISSN:	2079-9292, 2079-9292
On-line prístup:	Získať plný text
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