Classification of EEG signals using vector quantization

Abstract

Proper identification and classification of the EEG data still pauses a problem in the field of brain diagnosis. However, the application of such algorithm is almost unlimited as they may be involved in applications such as, brain computer interface for controlling of prosthesis, wheelchair, etc.. In this paper we are focusing on applying data compression in the classification of EEG signals. We combine a vector quantization and the normalized compression distance for proper classification of a finger movement data. © 2014 Springer International Publishing.