Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network

doi:10.3390/e23010119

	Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network
	Wang, Tao 4; Lu, Changhua 4; Sun, Yining 1; Yang, Mei 2; Liu, Chun 3; Ou, Chunsheng 4
刊名	ENTROPY
	2021
卷号	23
关键词	arrhythmia continuous wavelet transform convolutional neural network deep learning ECG classification heartbeat classification
DOI	10.3390/e23010119
通讯作者	Wang, Tao(wtustc@mail.ustc.edu.cn) ; Ou, Chunsheng(ouchunsheng@hfut.edu.cn)
英文摘要	Early detection of arrhythmia and effective treatment can prevent deaths caused by cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the electrocardiogram (ECG) beat-by-beat, but this is usually time-consuming and laborious. In the paper, we propose an automatic ECG classification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Network (CNN). CWT is used to decompose ECG signals to obtain different time-frequency components, and CNN is used to extract features from the 2D-scalogram composed of the above time-frequency components. Considering the surrounding R peak interval (also called RR interval) is also useful for the diagnosis of arrhythmia, four RR interval features are extracted and combined with the CNN features to input into a fully connected layer for ECG classification. By testing in the MIT-BIH arrhythmia database, our method achieves an overall performance of 70.75%, 67.47%, 68.76%, and 98.74% for positive predictive value, sensitivity, F1-score, and accuracy, respectively. Compared with existing methods, the overall F1-score of our method is increased by 4.75 similar to 16.85%. Because our method is simple and highly accurate, it can potentially be used as a clinical auxiliary diagnostic tool.
资助项目	Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-STS-ZDTP-079]
WOS研究方向	Physics
语种	英语
出版者	MDPI
WOS记录号	WOS:000610109500001
资助机构	Science and Technology Service Network Initiative of the Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/119763]
专题	中国科学院合肥物质科学研究院
通讯作者	Wang, Tao; Ou, Chunsheng
作者单位	1.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China 2.Beijing Huaru Technol Co Ltd, Hefei Branch, Hefei 230088, Peoples R China 3.Hefei Univ Technol, Sch Elect Engn & Automat, Hefei 230009, Peoples R China 4.Hefei Univ Technol, Sch Comp & Informat, Hefei 230009, Peoples R China
推荐引用方式 GB/T 7714	Wang, Tao,Lu, Changhua,Sun, Yining,et al. Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network[J]. ENTROPY,2021,23.
APA	Wang, Tao,Lu, Changhua,Sun, Yining,Yang, Mei,Liu, Chun,&Ou, Chunsheng.(2021).Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network.ENTROPY,23.
MLA	Wang, Tao,et al."Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network".ENTROPY 23(2021).