Practical Use Technology for Robot Control in BCI Environment based on Motor Imagery-P300

Abstract

BCI (Brain Computer Interface) is technology to control external devices by measuring the brain activity, such as electroencephalogram (EEG), so that handicapped people communicate with environment physically using the technology. Among them, EEG is widely used in various fields, especially robot agent control by using several signal response characteristics, such as P300, SSVEP (Steady-State Visually Evoked Potential) and motor imagery. However, in order to control the robot agent without any constraint and precisely, it should take advantage of not only a signal response characteristic, but also combination. In this paper, we try to use the fusion of motor imagery and P300 from EEG for practical use of robot control in BCI environment. The results of experiments are confirmed that the recognition rate decreases compared with the case of using one kind of features, whereas it is able to classify each both characteristics and the practical use technology based on mobile robot and wireless BCI measurement system is implemented.