Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network
文献类型:期刊论文
作者 | Wang, Tao1![]() ![]() |
刊名 | ENTROPY
![]() |
出版日期 | 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 |
WOS记录号 | WOS:000610109500001 |
出版者 | MDPI |
资助机构 | Science and Technology Service Network Initiative of the Chinese Academy of Sciences |
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.Hefei Univ Technol, Sch Comp & Informat, Hefei 230009, Peoples R China 2.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China 3.Beijing Huaru Technol Co Ltd, Hefei Branch, Hefei 230088, Peoples R China 4.Hefei Univ Technol, Sch Elect Engn & Automat, 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). |
入库方式: OAI收割
来源:合肥物质科学研究院
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。