Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks
Joint Authors
Zhang, Li
Xu, Xiaoyan
Ma, Caiyun
Luo, Kan
Liu, Chengyu
Wei, Shoushui
Source
Journal of Healthcare Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-02
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Atrial fibrillation (AF) is a serious cardiovascular disease with the phenomenon of beating irregularly.
It is the major cause of variety of heart diseases, such as myocardial infarction.
Automatic AF beat detection is still a challenging task which needs further exploration.
A new framework, which combines modified frequency slice wavelet transform (MFSWT) and convolutional neural networks (CNNs), was proposed for automatic AF beat identification.
MFSWT was used to transform 1 s electrocardiogram (ECG) segments to time-frequency images, and then, the images were fed into a 12-layer CNN for feature extraction and AF/non-AF beat classification.
The results on the MIT-BIH Atrial Fibrillation Database showed that a mean accuracy (Acc) of 81.07% from 5-fold cross validation is achieved for the test data.
The corresponding sensitivity (Se), specificity (Sp), and the area under the ROC curve (AUC) results are 74.96%, 86.41%, and 0.88, respectively.
When excluding an extremely poor signal quality ECG recording in the test data, a mean Acc of 84.85% is achieved, with the corresponding Se, Sp, and AUC values of 79.05%, 89.99%, and 0.92.
This study indicates that it is possible to accurately identify AF or non-AF ECGs from a short-term signal episode.
American Psychological Association (APA)
Xu, Xiaoyan& Wei, Shoushui& Ma, Caiyun& Luo, Kan& Zhang, Li& Liu, Chengyu. 2018. Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks. Journal of Healthcare Engineering،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1187007
Modern Language Association (MLA)
Xu, Xiaoyan…[et al.]. Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks. Journal of Healthcare Engineering No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1187007
American Medical Association (AMA)
Xu, Xiaoyan& Wei, Shoushui& Ma, Caiyun& Luo, Kan& Zhang, Li& Liu, Chengyu. Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks. Journal of Healthcare Engineering. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1187007
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187007