Classification of arrhythmias using spectral features with K nearest neighbor method Ari̇tmi̇leri̇n spektral özelli̇kler kullanilarak en yakin k komsu metoduyla siniflandirilmasi

Hilavin I., KUNTALP M., GÜRKAN KUNTALP D.

2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011, Antalya, Türkiye, 20 - 22 Nisan 2011, ss.411-414 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2011.5929675
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.411-414
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this work, five types of arrhythmias observed in electrocardiograph (ECG) signals are analyzed by using their spectral features. K-Nearest Neighbor (KNN) method is used as the classifier. The frequency spectrum of the samples are divided into a variable number of distinct bands and average band powers are used as the feature vectors. The performance of the classifier is tested by changing the width of the frequency bands, the number of neighbors and distance metric. The results are examined based on the average sensitivity, specificity, selectivity and accuracy values. The results show that the optimal KNN classifier is the one which uses 1 nearest neighbor, cityblock distance metric and 0.7Hz width frequency band. © 2011 IEEE.