A brain computer interface based on motion-onset VEPs

In this article, a novel brain-computer interface (BCI) based on motion-onset visual evoked potentials (mVEP) is proposed. Examination on the spatio-temporal pattern of motion-onset VEPs showed that the amplitude of N2 and P2 components of mVEP, evoked by attended target, was significantly higher than that by unattended ones. The area of N2 and P2 component was used as features for classifying the offline data of a five-class BCI, achieving an average accuracy of 98.33% in five subjects.

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