Intelligent system based on Genetic Algorithm and support vector machine for detection of myocardial infarction from ECG signals

Diker A., CÖMERT Z., Avci E., Velappan S.

26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Türkiye, 2 - 05 Mayıs 2018, ss.1-4, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2018.8404299
  • Basıldığı Şehir: İzmir
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1-4
  • Anahtar Kelimeler: Biomedical signal processing, Clinical decision support system, Electrocardiogram, Myocardial infarction
  • Samsun Üniversitesi Adresli: Hayır

Özet

Myocardial Infarction (MI) is one of the well-known heart attacks. This cardiac abnormality occurs when the artery connecting the heart is blocked. The main aim of this paper is to identify electrocardiogram (ECG) signals using morphological, time-domain and discrete wavelet transform (DWT) features in order to distinguish MI samples from normal. To this end, a model based on support vector machine (SVM) and Genetic algorithm (GA) is proposed. The whole experimental study was conducted on an open database called PTBDB. According to experimental study, 9 features were determined by GA as most relevant. Also, the dimension of feature set was decreased from 23 to 9. Lastly, the sensitivity and specificity were achieved as 87.80% and 85.97%, respectively.