Channel-Wise Average Pooling and 1D Pixel-Shuffle Denoising Autoencoder for Electrode Motion Artifact Removal in ECG

This paper presents a channel-wise average pooling and one dimension pixel-shuffle architecture for a denoising autoencoder (CPDAE) design that can be applied to efficiently remove electrode motion (EM) artifacts in an electrocardiogram (ECG) signal. The three advantages of the proposed design are a...

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Detalhes bibliográficos

Principais autores:	Yu-Syuan Jhang, Szu-Ting Wang, Ming-Hwa Sheu, Szu-Hong Wang, Shin-Chi Lai
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-07-01
Colecção:	Applied Sciences
Assuntos:	electrocardiogram (ECG) deep learning denoising autoencoder signal denoising
Acesso em linha:	https://www.mdpi.com/2076-3417/12/14/6957
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