A New Multichannel Parallel Network Framework for the Special Structure of Multilead ECG
Joint Authors
Zhang, Yabin
Zhou, Bing
Zhang, Hongpo
Lin, Yusong
Chen, Liwei
Lu, Peng
Xi, Hao
Hu, Yanhua
Gao, Yang
Source
Journal of Healthcare Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-03
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Electrocardiogram (ECG) contains the rhythmic features of continuous heartbeat and morphological features of ECG waveforms and varies among different diseases.
Based on ECG signal features, we propose a combination of multiple neural networks, the multichannel parallel neural network (MLCNN-BiLSTM), to explore feature information contained in ECG.
The MLCNN channel is used in extracting the morphological features of ECG waveforms.
Compared with traditional convolutional neural network (CNN), the MLCNN can accurately extract strong relevant information on multilead ECG while ignoring irrelevant information.
It is suitable for the special structures of multilead ECG.
The Bidirectional Long Short-Term Memory (BiLSTM) channel is used in extracting the rhythmic features of ECG continuous heartbeat.
Finally, by initializing the core threshold parameters and using the backpropagation algorithm to update automatically, the weighted fusion of the temporal-spatial features extracted from multiple channels in parallel is used in exploring the sensitivity of different cardiovascular diseases to morphological and rhythmic features.
Experimental results show that the accuracy rate of multiple cardiovascular diseases is 87.81%, sensitivity is 86.00%, and specificity is 87.76%.
We proposed the MLCNN-BiLSTM neural network that can be used as the first-round screening tool for clinical diagnosis of ECG.
American Psychological Association (APA)
Lu, Peng& Xi, Hao& Zhou, Bing& Zhang, Hongpo& Lin, Yusong& Chen, Liwei…[et al.]. 2020. A New Multichannel Parallel Network Framework for the Special Structure of Multilead ECG. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1186648
Modern Language Association (MLA)
Lu, Peng…[et al.]. A New Multichannel Parallel Network Framework for the Special Structure of Multilead ECG. Journal of Healthcare Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1186648
American Medical Association (AMA)
Lu, Peng& Xi, Hao& Zhou, Bing& Zhang, Hongpo& Lin, Yusong& Chen, Liwei…[et al.]. A New Multichannel Parallel Network Framework for the Special Structure of Multilead ECG. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1186648
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186648