Feature extraction and classification of neuromuscular diseases using scanning EMG

ARTUĞ N. T., Göker I., Bölat B., TULUM G., Osman O., BASLO M. B.

2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014, Alberobello, İtalya, 23 - 25 Haziran 2014, ss.262-265, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/inista.2014.6873628
  • Basıldığı Şehir: Alberobello
  • Basıldığı Ülke: İtalya
  • Sayfa Sayıları: ss.262-265
  • Anahtar Kelimeler: classification, Feature extraction, neuromuscular diseases, scanning EMG
  • İstanbul Yeni Yüzyıl Üniversitesi Adresli: Evet

Özet

In this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum amplitude times phase duration, and number of peaks. By using statistical values such as mean and variance, number of features has increased up to eight. This dataset was classified by using multi layer perceptron (MLP), support vector machines (SVM), k-nearest neighbours algorithm (k-NN), and radial basis function networks (RBF). The best accuracy is obtained as 97.78% with SVM algorithm and 3-NN algorithm. © 2014 IEEE.