ECG Arrhythmias Detection Using Auxiliary Classifier Generative Adversarial Network and Residual Network

ECG Arrhythmias Detection Using Auxiliary Classifier Generative Adversarial Network and Residual Network

This paper aims at proposing an abnormality detection framework for electrocardiogram (ECG) signals, which owns unbalance distribution among different classes and gaining high accuracy in rhythm/morphology abnormalities classification. The proposed framework is composed of two models: data augmentat...

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Bibliographic Details
Main Authors: Pu Wang, Borui Hou, Siyu Shao, Ruqiang Yan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Electrocardiogram signals
heartbeat arrhythmias detection
auxiliary classifier generative adversarial network
data augmentation
long short-term memory network
residual network
Online Access:https://ieeexplore.ieee.org/document/8771369/

Internet

https://ieeexplore.ieee.org/document/8771369/

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