A novel electrocardiogram arrhythmia classification method based on stacked sparse auto-encoders and softmax regression

A novel electrocardiogram arrhythmia classification method based on stacked sparse auto-encoders and softmax regression

Arrhythmia classification is crucial in electrocardiogram (ECG) based automatic cardiovascular disease diagnosis, e.g., to help prevent stroke or sudden cardiac death. However, the complex individual differences in ECG morphology make it challenging in accurately categorizing arrhythmia heartbeats....

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Bibliographic Details
Main Authors: Yang, Jianli, Bai, Yang, Lin, Feng, Liu, Ming, Hou, Zengguang, Liu, Xiuling
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2020
Subjects:
Engineering::Computer science and engineering
Stacked Sparse Auto-encoders
ECG Arrhythmia Classification
Online Access:https://hdl.handle.net/10356/139611

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