Arrhythmia Classification Using Higher Order Statistics

Kutlu Y., GÜRKAN KUNTALP D., KUNTALP M.

IEEE 16th Signal Processing and Communications Applications Conference, Aydın, Türkiye, 20 - 22 Nisan 2008, ss.733-736 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2008.4632718
  • Basıldığı Şehir: Aydın
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.733-736
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this work, the features are extracted for the arrhythmia classification from the electrocardiograph (ECG) signals by using Higher order statistics. K-nearest neighborhood algorithm is used as classifier. Cumulants are calculated from the raw signals obtained from consecutive sample values of each R peak in ECG signals and used as features. In addition to these features, different features obtained from the relations of cumulants are also used. Simulation results shows that features obtained from the relations among cumulants are more discriminative than the cumulants.