A statistical model of brain signals with application to brain-computer interface

作者：Zhang Haihong^*; Guan Cuntai; Wang Chuanchu

来源：27th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, 2005-08-31 to 2005-09-03.

This paper presents a novel. approach to improving the robustness of brain-computer interfaces by using a statistical model of brain signals-especially P300. We study the distributions of support vector machine scores for the signals and derive a posteriori probability model of P300/non-P300. We further derive a statistical model for multi-trial brain signals, and apply, it to the rejection of undesired signals. Six subjects have been involved in an experimental study. The results demonstrate that the P300 model and the rejection method are appropriate and can help improve the robustness of the system significantly.

• 出版日期2005