TY - GEN
T1 - Development of SSVEP-based BCI using common frequency pattern to enhance system performance
AU - Ko, Li Wei
AU - Lin, Shih Chuan
AU - Liang, Wei Gang
AU - Komarov, Oleksii
AU - Song, Meng Shue
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/12
Y1 - 2015/1/12
N2 - 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%.
AB - 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%.
KW - Brain computer interface(BCI)
KW - common frequency pattern(CFP)
KW - electroencephalography(EEG)
KW - steady-state visual evoked potential(SSVEP)
UR - http://www.scopus.com/inward/record.url?scp=84923025808&partnerID=8YFLogxK
U2 - 10.1109/CIBCI.2014.7007789
DO - 10.1109/CIBCI.2014.7007789
M3 - Conference contribution
AN - SCOPUS:84923025808
T3 - IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014: 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings
SP - 30
EP - 35
BT - IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, CIBCI 2014
Y2 - 9 December 2014 through 12 December 2014
ER -