Yunyong PunsawadYodchanan WongsawatMahidol University2018-06-112018-06-112012-12-14Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2012), 3837-38401557170X2-s2.0-84870844210https://repository.li.mahidol.ac.th/handle/20.500.14594/13996Steady-state visual evoked potential (SSVEP)- based brain-computer interface (BCI) system is one of the most accurate assistive technologies for the persons with severe disabilities. However, the existing visual stimulation patterns still lead to the eyes fatigue. Therefore, in this paper, we propose a novel visual stimulator using the idea of the motion visual stimulus to reduce the eyes fatigue while maintaining the merit of the SSVEP phenomena. Two corresponding feature extractions, i.e. 1) attention detection and 2) SSVEP detection, are also proposed to capture the phenomena of the proposed motion visual stimulus. Two-class classification accuracy of both features is approximately 80%, where the maximum accuracy using the attention detection is 90%, and the maximum accuracy using the SSVEP detection is 100%. © 2012 IEEE.Mahidol UniversityComputer ScienceEngineeringMedicineConference PaperSCOPUS10.1109/EMBC.2012.6346804