Discrimination of Cardiac Arrhythmia using a Fusion Classifier with ECG Morphological Features-Reference-Cited by-同舟云学术

Discrimination of Cardiac Arrhythmia using a Fusion Classifier with ECG Morphological Features

Published:2019-10-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 8th International Conference on Bioinformatics and Biomedical Science
language:
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Author:

Yang Hui¹,Wei Zhiqiang²

Affiliation:

1. Department of Computer Science and Technology, College of Information Science and Engineering, Ocean University of China, Qingdao, China and Department of Computer Foundation, Ocean University of China, Qingdao, China

2. Department of Computer Science and Technology, College of Information Science and Engineering, Ocean University of China, Qingdao, China

Funder

National Natural Science Foundation of China

Humanities and Social Sciences Project of Chinese Ministry of Education

Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3369166.3369167

Reference25 articles.

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3. An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks

4. Rakshit M. and Das S. 2018. An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filter. Biomedical Signal Processing and Control. 40 (Feb. 2018) 140--148. DOI= https://doi.org/10.1016/j.bspc.2017.09.020. Rakshit M. and Das S. 2018. An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filter. Biomedical Signal Processing and Control. 40 (Feb. 2018) 140--148. DOI= https://doi.org/10.1016/j.bspc.2017.09.020.