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

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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Bibliographic Details
Main Authors: Yu-Syuan Jhang, Szu-Ting Wang, Ming-Hwa Sheu, Szu-Hong Wang, Shin-Chi Lai
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Applied Sciences
Subjects:
electrocardiogram (ECG)
deep learning
denoising autoencoder
signal denoising
Online Access:https://www.mdpi.com/2076-3417/12/14/6957

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