Vol.125, No.1, 2020, pp.365-382, doi:10.32604/cmes.2020.010798
OPEN ACCESS
ARTICLE
PDNet: A Convolutional Neural Network Has Potential to be Deployed on Small Intelligent Devices for Arrhythmia Diagnosis
  • Fei Yang1,2,#, Xiaoqing Zhang1,*,#, Yong Zhu3
1 Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
2 Cooperative Innovtion Center of Internet Healthcare, Zhengzhou University, Zhengzhou, 450052, China
3 College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China
* Corresponding Author: Xiaoqing Zhang. Email: dbozhang@foxmail.com
# Fei Yang and Xiaoqing Zhang contributed equally to this work
(This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Received 21 March 2020; Accepted 20 July 2020; Issue published 18 September 2020
Abstract
Heart arrhythmia is a group of irregular heartbeat conditions and is usually detected by electrocardiograms (ECG) signals. Over the past years, deep learning methods have been developed to classify different types of heart arrhythmias through ECG based on computer-aided diagnosis systems (CADs), but these deep learning methods usually cannot trade-off between classi
Keywords
Electrocardiograms; heart arrhythmia; convolutional neural network; PDblock; loss
Cite This Article
Yang, F., Zhang, X., Zhu, Y. (2020). PDNet: A Convolutional Neural Network Has Potential to be Deployed on Small Intelligent Devices for Arrhythmia Diagnosis. CMES-Computer Modeling in Engineering & Sciences, 125(1), 365–382.
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