Single-Trial VEP Estimation Using Support Vector Machines in Single-Channel

Using imitating-natural-reading induced potentials as communication carriers, we are constructing a brain-computer interface based mental speller which enables users to interaction with computers. The carriers were induced in this way: in a trial, sentences consisted of target and non-target symbols were moving smoothly from right to left through a little visual window at the center of computer screen. Subject was instructed to stare at the visual window to count the target, and thus potentials were evoked. In practical applications, fewer electroencephalograph recording channels are preferred. We explored the single-trial estimating of event-related potentials recorded in single-channel using support vector machines in three subjects. With carefully feature selections, we obtained satisfying results of correct classification rate, which is 92.1%, 94.1% and 91.5%, respectively. The results demonstrated the advantages of the inducing paradigm used in our experiments