MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG

MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG

Automatic arrhythmia detection using 12-lead electrocardiogram (ECG) signal plays a critical role in early prevention and diagnosis of cardiovascular diseases. In the previous studies on automatic arrhythmia detection, most methods concatenated 12 leads of ECG into a matrix, and then input the matri...

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Bibliographic Details
Main Authors: Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Arrhythmia classification
multi-lead ECG analysis
co-optimization
deep learning
Online Access:https://ieeexplore.ieee.org/document/9373359/

Internet

https://ieeexplore.ieee.org/document/9373359/

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