Automatic Cardiac Arrhythmia Classification Using Combination of Deep Residual Network and Bidirectional LSTM

Automatic Cardiac Arrhythmia Classification Using Combination of Deep Residual Network and Bidirectional LSTM

Cardiac arrhythmia is associated with abnormal electrical activities of the heart, which can be reflected by altered characteristics of electrocardiogram (ECG). Due to the simplicity and non-invasive nature, the ECG has been widely used for detecting arrhythmias and there is an urgent need for autom...

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Bibliographic Details
Main Authors: Runnan He, Yang Liu, Kuanquan Wang, Na Zhao, Yongfeng Yuan, Qince Li, Henggui Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cardiac arrhythmia
electrocardiogram (ECG)
deep neural networks (DNNs)
deep residual network
bidirectional long short-term memory (LSTM)
Online Access:https://ieeexplore.ieee.org/document/8778643/

Internet

https://ieeexplore.ieee.org/document/8778643/

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