Investigation of Training by Visual Feedback for Subject in Electroencephalogram-based Control

Abstract

Recently, physical assisting equipments using biological information have been developed for crippled elderly or physically challenged people. This study focuses on electroencepharogram (EEG) as a biological information and aims to control various machines using EEG. In electroencephalogrambased control, it is often hard to generate effective discrimination model for thinkings because of changing thinking/EEG as time advances. The purpose of this study is to acquire effective and stable discrimination model by training, then to analyze measurement sites, frequency bands and thinking ways effective for discrimination. This paper investigates a visual real-time feedback for the training. This paper discusses the discrimination rate and the transition of affected measurement sites through the experiment by 4 subjects.