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.
