Classification of SSVEP-based BCIs using Genetic Algorithm

Abstract Brain computer interface (BCI) systems have been regarded as a new way of communication for humans. In this research, common methods such wavelet transform are applied in order to extract features. However, genetic algorithm (GA), an evolutionary method, is used select Finally, classification was done using the two approaches support vector machine (SVM) and Bayesian method. Five features were selected accuracy measured be 80% with dimension reduction. Ultimately, reached 90.4% SVM classifier. The results study indicate better feature selection effective reduction these features, well higher percentage comparison other studies.