Classification of steady state visual evoked potentials by Multi-Class T-Weight Method

İŞCAN Z., Ölmez Z.

Pattern Recognition and Image Analysis, cilt.25, sa.2, ss.321-326, 2015 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 2
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1134/s1054661815020121
  • Dergi Adı: Pattern Recognition and Image Analysis
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.321-326
  • Anahtar Kelimeler: applications of MCTW method, obtained classification performances
  • İstanbul Medipol Üniversitesi Adresli: Hayır

Özet

In this paper, Multi-Class T-Weight Method (MCTW) is presented for classification in brain-computer interface (BCI) systems. Proposed method is an extension of the existing Improved T-Weight method for multi-class problems. The method was tested on the frequency and correlation based features obtained from electroencephalogram data of 20 Subjects in a steady state visual evoked potential (SSVEP) based offline BCI classification task. Obtained classification performances with different classifiers show that the MCTW method compete with the other well-known classifiers like linear discriminant analysis (LDA) and support vector machines (SVMs). Therefore, it can be used in classifying SSVEP based electroencephalogram data with proper features.