Summary
International Technical Conference on Circuits/Systems, Computers and Communications
2016
Session Number:W2-1
Session:
Number:W2-1-1
Brain Wave Pattern Classification from Virtual Training Environment by Self-Organizing Maps
Bruno Senzio-Savino, Mohammad Reza Alsharif, Carlos E. Gutierrez, Christian Penaloza, Katsumi Yamashita, Faramarz Alsharif, Mahdi Khosravy, Mousa Shamsi ,
pp.779-782
Publication Date:2016/7/10
Online ISSN:2188-5079
Summary:
The main purpose of this research is to perform and analyze the performance of a simple brain wave password signal pattern feature classifier by Self Organizing Maps (SOM) and the processing time dedicated to build it. These signals are composed by attention/meditation signal patterns obtained with the aid of a virtual training environment. The signal treatment for the obtained data is explained and the output results from 10-fold cross validation are presented for different feature vector classification by a simple Kohonen layer SOM. The best result represents a 60% average recognition rate for an average processing time of about 132 seconds.