A Novel Regression-based Algorithm for the recognition of SSVEP responses

The recognition of Steady State Visual Evoked Responses (SSVEP) is a problem that arises frequently into the Brain Computer Interface (BCI) concept. In this paper, we present a novel algorithm for their recognition by formulating the pattern recognition problem in terms of linear regression. The inverse problem is solved using the bayesian framework and the decision is ruled in favor of the class with the minimum distance. The experimental results demonstrate that the proposed algorithm achieves better performance, in terms of classification accuracy, than the competing approaches.