Automated Classification of Atrial Fibrillation Using Artificial Neural Network for Wearable Devices
Joint Authors
Ma, Fengying
Zhang, Jingyao
Liang, Wei
Xue, Jingyu
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-25
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Atrial fibrillation (AF), as one of the most common arrhythmia diseases in clinic, is a malignant threat to human health.
However, AF is difficult to monitor in real time due to its intermittent nature.
Wearable electrocardiogram (ECG) monitoring equipment has flourished in the context of telemedicine due to its real-time monitoring and simple operation in recent years, providing new ideas and methods for the detection of AF.
In this paper, we propose a low computational cost classification model for robust detection of AF episodes in ECG signals, using RR intervals of the ECG signals and feeding them into artificial neural network (ANN) for classification, to compensate the defect of the computational complexity in traditional wearable ECG monitoring devices.
In addition, we compared our proposed classifier with other popular classifiers.
The model was trained and tested on the AF Termination Challenge Database and MIT-BIH Arrhythmia Database.
Experimental results achieve the highest sensitivity of 99.3%, specificity of 97.4%, and accuracy of 98.3%, outperforming most of the others in the recent literature.
Accordingly, we observe that ANN using RR intervals as an input feature can be a suitable candidate for automatic classification of AF.
American Psychological Association (APA)
Ma, Fengying& Zhang, Jingyao& Liang, Wei& Xue, Jingyu. 2020. Automated Classification of Atrial Fibrillation Using Artificial Neural Network for Wearable Devices. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1202025
Modern Language Association (MLA)
Ma, Fengying…[et al.]. Automated Classification of Atrial Fibrillation Using Artificial Neural Network for Wearable Devices. Mathematical Problems in Engineering No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1202025
American Medical Association (AMA)
Ma, Fengying& Zhang, Jingyao& Liang, Wei& Xue, Jingyu. Automated Classification of Atrial Fibrillation Using Artificial Neural Network for Wearable Devices. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1202025
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202025