Classification Accuracy Improvement of Chromatic and High–Frequency Code–Modulated Visual Evoked Potential–Based BCI
We present results of a classification improvement approach for a code–modulated visual evoked potential (cVEP) based brain–computer interface (BCI) paradigm using four high–frequency flashing stimuli. Previously published research reports presented successful BCI applications of canonical correlation analysis (CCA) to steady–state visual evoked potential (SSVEP) BCIs. Our team already previously proposed the combined CCA and cVEP techniques’ BCI paradigm. The currently reported study presents the further enhanced results using a support vector machine (SVM) method in application to the cVEP–based BCI.
KeywordsBrain–computer interfaces ERP cVEP EEG classification
Unable to display preview. Download preview PDF.
- 1.Aminaka, D., Makino, S., Rutkowski, T.M.: Chromatic and high-requency cVEP-based BCI paradigm. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE Engineering in Medicine and Biology Society, August 25–29, 2015. (accepted, in press)Google Scholar
- 6.Plum, F., Posner, J.B.: The Diagnosis of Stupor and Coma. FA Davis, Philadelphia (1966)Google Scholar
- 7.Renard, Y., Lotte, F., Gibert, G., Congedo, M., Maby, E., Delannoy, V., Bertrand, O., Lécuyer, A.: Openvibe: an open-source software platform to design, test, and use brain-computer interfaces in real and virtual environments. Presence: Teleoperators and Virtual Environments 19(1), 35–53 (2010)CrossRefGoogle Scholar
- 8.Sakurada, T., Kawase, T., Komatsu, T., Kansaku, K.: Use of high-frequency visual stimuli above the critical flicker frequency in a SSVEP-based BMI. Clinical Neurophysiology (2014). (online first)Google Scholar
- 9.Wolpaw, J., Wolpaw, E.W. (eds.): Brain-Computer Interfaces: Principles and Practice. Oxford University Press (2012)Google Scholar