Abstract
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.
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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)
Bakardjian, H., Tanaka, T., Cichocki, A.: Optimization of SSVEP brain responses with application to eight-command brain-computer interface. Neuroscience Letters 469(1), 34–38 (2010)
Bin, G., Gao, X., Wang, Y., Hong, B., Gao, S.: VEP-based brain-computer interfaces: time, frequency, and code modulations [Research Frontier]. IEEE Computational Intelligence Magazine 4(4), 22–26 (2009)
Bin, G., Gao, X., Wang, Y., Li, Y., Hong, B., Gao, S.: A high-speed BCI based on code modulation VEP. Journal of Neural Engineering 8(2), 025015 (2011)
Bin, G., Gao, X., Yan, Z., Hong, B., Gao, S.: An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. Journal of Neural Engineering 6(4), 046002 (2009)
Plum, F., Posner, J.B.: The Diagnosis of Stupor and Coma. FA Davis, Philadelphia (1966)
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)
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)
Wolpaw, J., Wolpaw, E.W. (eds.): Brain-Computer Interfaces: Principles and Practice. Oxford University Press (2012)
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Aminaka, D., Makino, S., Rutkowski, T.M. (2015). Classification Accuracy Improvement of Chromatic and High–Frequency Code–Modulated Visual Evoked Potential–Based BCI. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds) Brain Informatics and Health. BIH 2015. Lecture Notes in Computer Science(), vol 9250. Springer, Cham. https://doi.org/10.1007/978-3-319-23344-4_23
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DOI: https://doi.org/10.1007/978-3-319-23344-4_23
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