Development of SSVEP-based BCI using common frequency pattern to enhance system performance

Li-Wei Ko,Wei-Gang Liang,Shih-Chuan Lin,Meng-Shue Song,Oleksii Komarov

doi:10.1109/cibci.2014.7007789

Development of SSVEP-based BCI using common frequency pattern to enhance system performance

Li-Wei Ko, Wei-Gang Liang + Show 3 more

https://doi.org/10.1109/cibci.2014.7007789

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Publication Date: Dec 1, 2014

Citations: 5

Affiliation: National Tsing Hua University, Institute of Bioinformatics, Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Institute of Molecular Medicine

#Brain Computer Interface System #Steady-state Visual Evoked Potentials + Show 8 more

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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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