Navigation Control of Humanoid Robot Based on Motor Imaginary

As a research focus in bio-rehabilitation field, Brain-Computer Interface that can efficiently improve or recover self-care ability of disabled people has obtained fast development in recent years. In this paper, the phenomenon of event-related de-synchronization in EEG was pre-processed and features were extracted by using common space pattern filtering algorithm. Higher classification accuracy was then obtained by employing C-SVM for left, right hand and leg movement discrimination. Then the algorithms were applied in the design of brain computer interface for the control of humanoid robot. The operations by EEG and manual device were compared to illustrate the effectiveness of the BCI system.