An Implementation Of Ssvep-bci System Based On A Cluster Measure For Feature Selection

The main objective of a brain-computer interface (BCI) is to create alternative communication channels between the brain and a machine using information from cerebral responses. Among the possible paradigms to design a BCI system, this work focuses on Steady-State Visually Evoked Potentials (SSVEP). SSVEP are brain responses synchronized with fast repetitive external visual stimuli. The SSVEP-BCI system is able to meet many of the requirements of a strict BCI, but still needs to reduce the influence of noise on the Electroencephalogram (EEG) signal in order to improve its performance. In this paper, a novel SSVEP-BCI system is presented and analyzed in detail. The system is based on three pillars: spectrum estimation, systematic feature selection-for which different heuristics were proposed here-, and linear classification. © 2014 IEEE.Guger, C., Allison, B., Edlinger, G., State of the art in bci research: Bci award 2011 (2013) Brain-Computer Interface Research, Ser. SpringerBriefs in Electrical and Computer Engineering, pp. 1-5. , http://dx.doi.org/10.1007/978-3-642-36083-11, C. Guger, B. Z. Allison, and G. Edlinger, Eds. Springer Berlin Heidelberg, [Online]Millán, J.D.R., Rupp, R., Müller-Putz, G., Murray-Smith, R., Giugliemma, C., Tangermann, M., Combining brain-computer interfaces and assistive technologies: State-of-the-art and challenges (2010) Frontiers in Neuroscience, 4, pp. 1-15. , http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2944670\ &tool=pmcentrez\&rendertype=abstract, September, [Online]Bashashati, A., Fatourechi, M., Ward, R.K., Birch, G.E., A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals (2007) Journal of Neural Engineering, 4 (2), pp. R32-57. , http://www.ncbi.nlm.nih.gov/pubmed/17409474, Jun., [Online]Bin, G., Gao, X., Wang, Y., VEP-based brain-computer interfaces: Time, frequency, and code modulations (2009) Computational Intelligence Magazine IEEE, 4 (4), pp. 22-26. , http://ieeexplore.ieee.org/xpls/abs\all.jsp?arnumber=5294934, November, [Online]Mller, S.M.T., Salezze, B., Bastos Filho, T.F., Sarcinelli Filho, M., Estimativa de picos espectrais para compo-sio de vetor de caractersticas de uma interface crebro-computador (2010) XVIII Congresso Brasileiro de Automtica-CBA2010, NICO, pp. 3794-3799Davies, D.L., Bouldin, D.W., A cluster separation measure (1979) Pattern Analysis and Machine Intelligence IEEE Transactions on, PAMI-1 (2), pp. 224-227Theodoridis, S., Koutroumbas, K., (2008) Pattern Recognition, Fourth Edition, , 4th ed. Academic PressNg, K.B., Bradley, A.P., Cunnington, R., Stimulus specificity of a steady-state visual-evoked potential-based brain-computer interface (2012) Journal of Neural Engineering, 9 (3), p. 036008. , http://www.ncbi.nlm.nih.gov/pubmed/22589242, Jun., [Online]Duda, R.O., Hart, P.E., Stork, D.G., (2001) Pattern Classification, 2nd Ed, , New York: WileyFabiani, G.E., McFarland, D.J., Wolpaw, J.R., Pfurtscheller, G., Conversion of eeg activity into cursor movement by a brain-computer interface (bci) (2004) IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of the IEEE Engineering in Medicine and Biology Society, 12 (3), pp. 331-338. , http://www.ncbi.nlm.nih.gov/pubmed/15473195, Sep., [Online]Wu, C.-H., Lakany, H., Impact of stimulus configuration on steady state visual evoked potentials (ssvep) response (2012) COGNITIVE 2012 the Fourth International Conference on Advanced Cognitive Technologies and Applications, (3), pp. 77-82. , http://www.thinkmind.org/index.php?view=article\&articleid=cognitive\ 2012\4\20\40040, Nice, France, [Online]Mnguez Zafra, J., Montesano Del Campo, L., Horna Prat, E.M., (2011) Decodificacin de Los Objetivos Finales (3d) Del Movimiento Del Brazo en Tareas de Alcance A Partir de Potenciales de Movimiento Anticipatorio Para Eeg Brain Computer Interfac