Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study
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- 作者：U Rajendra Acharyaa ; b ; c ; Hamido Fujitad ; HFujita-799@acm.org" class="auth_mail" title="E-mail the corresponding author ; Muhammad Adama ; Oh Shu Liha ; Vidya K Sudarshana ; Tan Jen Honga ; Joel EW Koha ; Yuki Hagiwaraa ; Chua K. Chuaa ; Chua Kok Pooa ; Tan Ru Sane
- 关键词：Coronary artery disease ; Myocardial infarction ; Electrocardiogram ; Discrete cosine transform ; Discrete wavelet transform ; Empirical mode decomposition
- 刊名：Information Sciences
- 出版年：2017
- 出版时间：20 January 2017
- 年：2017
- 卷：377
- 期：Complete
- 页码：17-29
- 全文大小：1264 K
文摘
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Classification of three types of ECG beats are proposed.
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Normal, CAD and MI are three classes considered in this work.
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DCT, DWT and EMD decomposition methods are employed on ECG beat.
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Decomposed signals are fed to Locality Preserving Projections method.
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KNN classifier yielded 98.5% accuracy with seven features for DCT method.