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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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%.

Original languageEnglish
Title of host publicationIEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014
Subtitle of host publication2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-35
Number of pages6
ISBN (Electronic)9781479945443
DOIs
StatePublished - 12 Jan 2015
Event2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, CIBCI 2014 - Orlando, United States
Duration: 9 Dec 201412 Dec 2014

Publication series

NameIEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014: 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings

Conference

Conference2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, CIBCI 2014
CountryUnited States
CityOrlando
Period9/12/1412/12/14

Keywords

  • Brain computer interface(BCI)
  • common frequency pattern(CFP)
  • electroencephalography(EEG)
  • steady-state visual evoked potential(SSVEP)

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    Ko, L. W., Lin, S. C., Liang, W. G., Komarov, O., & Song, M. S. (2015). Development of SSVEP-based BCI using common frequency pattern to enhance system performance. In IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014: 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings (pp. 30-35). [7007789] (IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014: 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIBCI.2014.7007789