Brain-actuated humanoid robot control using one class motor imagery task

Brain-computer interface (BCI) technology is a new control interface which can translate brain activities directly to computer commands. This paper presents a brain direct-control system for humanoid robot based on one class motor imagery (MI) BCI paradigm. In the paradigm, a hierarchical human-robot interaction protocol was designed based on special gestures of the robot, which can modulate four robot motion commands by only one class of MI task. With this protocol, more available commands can be exported using a small set of MI tasks. Furthermore, as only one MI task needed to be classified directly from the electroencephalograph (EEG) signals, the difficulty of classifier design was also reduced significantly comparing to the traditional multi-class BCI system. The proposed BCI control system was tested in a robot navigation experiment. The average accuracy of the BCI paradigm was 90.7%, and all the subjects could complete the robot navigation task successfully. The results showed that the present BCI control system is feasible and efficient, which can be applied to practical control applications.