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 Topic

Public Health
Medicine

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