Multiscale Convolution and Attention based Denoising Autoencoder for Motion Artifact Removal in ECG Signals-Reference-Cited by-同舟云学术

Multiscale Convolution and Attention based Denoising Autoencoder for Motion Artifact Removal in ECG Signals

Published:2024-01-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2024 7th International Conference on Image and Graphics Processing
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Author:

Chen Meng¹^ORCID,Li Yongjian¹^ORCID,Zhang Xiuxin¹^ORCID,Gao Jiahui¹^ORCID,Sun Yiheng¹^ORCID,Shi Wenzhuo²^ORCID,Wei Shoushui¹^ORCID

Affiliation:

1. Shandong University, School of Control Science and Engineering, China

2. Shandong University, Institute of Marine Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3647649.3647718

Reference14 articles.

1. H. Kim "Motion artifact removal using cascade adaptive filtering for ambulatory ECG monitoring system " 2012 IEEE biomedical circuits and systems conference (BioCAS) pp. 160-163 2012.

2. S. Tian, J. Han, J. Yang, L. Zhou, and X. Zeng, "Motion artifact removal based on ICA for ambulatory ECG monitoring," 2015 IEEE 11th International Conference on ASIC (ASICON), pp. 1-4, 2015.

3. M. Zubair, G. N. V. S. C. Mouli, and R. A. Shaik, "Removal of Motion Artifacts from ECG signals by Combination of Recurrent Neural Networks and Deep Neural Networks," 2020 2nd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), pp. 1-7, 28-28 Nov. 2020.

4. Robust PPG motion artifact detection using a 1-D convolution neural network

5. Improved Electrode Motion Artefact Denoising in ECG Using Convolutional Neural Networks and a Custom Loss Function

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