Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography
Institute of Electrical and Computer Engineering, National Chiao-Tung University, Hsinchu 30010, Taiwan
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Sensors 2020, 20(24), 7246; https://doi.org/10.3390/s20247246
Received: 18 November 2020
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Revised: 13 December 2020
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Accepted: 14 December 2020
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Published: 17 December 2020
(This article belongs to the Special Issue Advanced Signal Processing in Wearable Sensors for Health Monitoring)
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases worldwide and most patients suffer from MI without awareness. Therefore, early diagnosis and timely treatment are crucial to guarantee the life safety of MI patients. Most wearable monitoring devices only provide single-lead electrocardiography (ECG), which represents a major limitation for their applicability in diagnosis of MI. Incorporating the derived vectorcardiography (VCG) techniques can help monitor the three-dimensional electrical activities of human hearts. This study presents a patient-specific reconstruction method based on long short-term memory (LSTM) network to exploit both intra- and inter-lead correlations of ECG signals. MI-induced changes in the morphological and temporal wave features are extracted from the derived VCG using spline approximation. After the feature extraction, a classifier based on multilayer perceptron network is used for MI classification. Experiments on PTB diagnostic database demonstrate that the proposed system achieved satisfactory performance to differentiating MI patients from healthy subjects and to localizing the infarcted area.
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Keywords:
electrocardiography; vectorcardiography; myocardial infarction; long short-term memory; spline; multilayer perceptron
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MDPI and ACS Style
Chuang, Y.-H.; Huang, C.-L.; Chang, W.-W.; Chien, J.-T. Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography. Sensors 2020, 20, 7246. https://doi.org/10.3390/s20247246
AMA Style
Chuang Y-H, Huang C-L, Chang W-W, Chien J-T. Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography. Sensors. 2020; 20(24):7246. https://doi.org/10.3390/s20247246
Chicago/Turabian StyleChuang, Yu-Hung, Chia-Ling Huang, Wen-Whei Chang, and Jen-Tzung Chien. 2020. "Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography" Sensors 20, no. 24: 7246. https://doi.org/10.3390/s20247246
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