Elimination of Random Mixed Noise in ECG Using Convolutional Denoising Autoencoder With Transformer Encoder

Electrocardiogram (ECG) signals frequently encounter diverse types of noise, such as baseline wander (BW), electrode motion (EM) artifacts, muscle artifact (MA), and others. These noises often occur in combination during the actual data acquisition process, resulting in erroneous or perplexing inter...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. 28; H. 4; S. 1993 - 2004
Hauptverfasser:	Chen, Meng, Li, Yongjian, Zhang, Liting, Liu, Lei, Han, Baokun, Shi, Wenzhuo, Wei, Shoushui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.04.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive filters Algorithms Cardiac stress tests Coders Convolution Corruption Data acquisition Data processing Denoising autoencoder Distortion ECG denoising EKG Electrocardiography Electrocardiography - methods Exercise Test Feature extraction Humans Logic gates multi-head self-attention Noise Noise reduction point-wise convolution random mixed noise Signal Processing, Computer-Assisted Signal-To-Noise Ratio Training transformer encoder Transformers Wiener filters
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
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