Abstract
A four-class brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEPs) was developed by presenting phase-coded 60Hz stimulations on a 240Hz LCD monitor. The task-related component analysis (TRCA) algorithm was used to detect SSVEPs with individual training data. In the BCI experiment with 10 subjects, the system achieved high classification accuracy of 94.50±6.70% and 92.71±7.56% in offline and online BCI experiments, resulting in information transfer rates (ITR) of 19.95±4.36 and 18.81±4.74 bpm, respectively. The behavioral tests on visual comfortableness and perception of flickering reveal that the proposed BCI system is very comfortable to use without any perception of flicker.
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