Construction of real-time BMI control system based on motor imagery

Abstract

Recently, a lot of BMIs (Brain-Machine Interfaces) using EEG (electroencephalogram) signals are developed to control external devices such as prostheses and robots. In this paper, in order to develop a new BMI for rehabilitation and/or power support, four different tasks corresponding to different brain excitation degrees are designed. Their EEG spectra are analyzed with short-time FFT, and their features of mu and beta rhythms corresponding to the different tasks are extracted. Finally, one-joint robot arm is controlled by the extracted features, and the proposed approach is confirmed.