A Brain-Robot Interface by BCI based on Repeated Binary CSP

In this paper, due to the low information transfer rate and low recognition accuracy in Brain-Computer Interface (BCI), a four-class motor imagery Brain-Robot Interface based on Repeated Binary Common Spatial Pattern (RB-CSP) and Support Vector Machine (SVM) is proposed. The control strategy is offline training first, online control next-after users finish learning to control their thinking, the system makes pattern recognition on the collected users' EEG signals and finally translates them into commands to control the movement of the robot. Experiments indicate that the system is able to extract users' EEG signal features quickly and correctly, translate them into robot's control instructions, which can be used to make real-time control on robots effectively.