Classification of branch block beats using higher order spectral analysis and neural networks
IEEE 14th Signal Processing and Communications Applications, Antalya, Türkiye, 16 - 19 Nisan 2006, ss.437-438, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası:
- Doi Numarası: 10.1109/siu.2006.1659736
- Basıldığı Şehir: Antalya
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.437-438
- Dokuz Eylül Üniversitesi Adresli: Evet
Özet
In this study, it is aimed to classify branch block beats. A total number of 6170 beats related to 3 types of classes are extracted from MIT/BIH arrhythmia database and their bispectrums are calculated using TOR method. The area defined by the frequency values where the value of the energy of bispectrum is 95% of the maximum value in both axes is calculated. This area information is used as a one dimensional feature vector to feed the neural network designed as a classifier. The overall performance of the system is calculated as 94.2%. This study shows that higher order spectral analysis is a promising tool for arrhythmia beat classification.