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

İŞCAN Z., Ölmez Z.

Pattern Recognition and Image Analysis, vol.25, no.2, pp.321-326, 2015 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 2
  • Publication Date: 2015
  • Doi Number: 10.1134/s1054661815020121
  • Journal Name: Pattern Recognition and Image Analysis
  • Journal Indexes: Scopus
  • Page Numbers: pp.321-326
  • Keywords: applications of MCTW method, obtained classification performances
  • Istanbul Medipol University Affiliated: No

Abstract

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.