Abstract
Brain Computer Interface(BCI) systems provide an additional way for people to interact with external environment without using peripheral nerves or muscles[1]. In a variety of BCI systems, a BCI system based on the steady-state visual evoked potentials (SSVEP) is one most common system known for application, because of its ease of use and good performance with little user training. In this study, the common frequency pattern method (CFP) is used to improve the accuracy of our EEG-based SSVEP BCI system. There are four basic classifiers (SVM, KNNC, PARZENDC, LDC) in this paper to estimate the accuracy of our SSVEP system. Without using CFP, the highest accuracy of the EEG-based SSVEP system was 80%. By using CFP, the accuracy could be upgraded to 95%.
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