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Open AccessArticle

Application of Heartbeat-Attention Mechanism for Detection of Myocardial Infarction Using 12-Lead ECG Records

The Division of Information Science and Technology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
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Appl. Sci. 2019, 9(16), 3328; https://doi.org/10.3390/app9163328
Received: 12 June 2019 / Revised: 2 August 2019 / Accepted: 6 August 2019 / Published: 13 August 2019
(This article belongs to the Special Issue Signal Processing and Machine Learning for Biomedical Data)
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Abstract

Early detection and effective treatment of myocardial infarction can prevent the deterioration of ischemic heart disease and greatly reduce the possibility of sudden death. On the basis of standard 12-lead electrocardiogram (ECG) records, this paper proposes a bidirectional, long short-term memory (Bi-LSTM) network with a heartbeat-attention mechanism to effectively and automatically detect myocardial infarction (MI). First, we divide the standard 12-lead ECG records into sliding windows with the same number of heartbeats. Subsequently, we do not use any labels of heartbeats to train the Bi-LSTM network and the heartbeat-attention mechanism is applied to automatically weight the difference between unlabeled heartbeats. Finally, our method is validated by patients’ complete ECG records and real labels in the Physikalisch-Technische Bundesanstalt (PTB) diagnostic ECG database. When compared with the same network without the heartbeat-attention mechanism or other existing methods, our method achieves comparable or better performance. The accuracy, sensitivity, and specificity reach 94.77%, 95.58%, and 90.48%, respectively. View Full-Text
Keywords: myocardial infarction; heartbeat-attention mechanism; 12-lead ECG records myocardial infarction; heartbeat-attention mechanism; 12-lead ECG records
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zhang, Y.; Li, J. Application of Heartbeat-Attention Mechanism for Detection of Myocardial Infarction Using 12-Lead ECG Records. Appl. Sci. 2019, 9, 3328.

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