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Classification of visual stimuli with different spatial patterns for single-frequency, multi-class SSVEP BCI

Classification of visual stimuli with different spatial patterns for single-frequency, multi-class SSVEP BCI

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A new approach for a multi-class steady-state visual-evoked potential (SSVEP)-based brain–computer interface (BCI) is proposed. It was demonstrated through preliminary experiments that spatial patterns of SSVEP responses recorded using high-density electroencephalography while presenting pattern reversal checkerboard stimuli with different spatial patterns can be classified with fairly high accuracy. The average classification accuracies in two of the three subjects were 91.7% (12-class) and 93.3% (15-class), suggesting that the proposed visual stimulation can potentially be used for multi-class SSVEP-based BCI.


    1. 1)
      • 1. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: ‘Brain-computer interfaces for communication and control’, Clin. Neurophysiol., 2002, 113, (6), pp. 767791 (doi: 10.1016/S1388-2457(02)00057-3).
    2. 2)
      • 9. Materka, A., Byczuk, M.: ‘Alternate half-field stimulation technique for SSVEP-based brain–computer interfaces’, Electron. Lett., 2006, 42, (6), pp. 321322 (doi: 10.1049/el:20060171).
    3. 3)
      • 2. Hwang, H.J., et al: ‘Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard’, J. Neurosci. Meth., 2012, 208, (1), pp. 5965 (doi: 10.1016/j.jneumeth.2012.04.011).
    4. 4)
      • 8. Yan, Z., et al: ‘A half-field stimulation pattern for SSVEP-based brain-computer interface’. 31th Annual Int. Conf. IEEE EMBS, Minneapolis, MN, USA, 2009, pp. 64616464.
    5. 5)
      • 5. Hwang, H.J., Kim, D.H., Han, C.H., Im, C.H.: ‘A new dual-frequency stimulation method to increase the number of visual stimuli for multi-class SSVEP-based brain-computer interface (BCI)’, Brain Res., 2013, 1515, pp. 937950 (doi: 10.1016/j.brainres.2013.03.050).
    6. 6)
      • 7. Caruana, R., Lawrence, S., Giles, L.: ‘Overfitting in neural nets: backpropagation, conjugate gradient, and early stopping’ in Leen, T.K., Dietterich, T.G., Tresp, V. (Eds): ‘Advances in neural information processing systems’ (Massachusetts Institute of Technology, Cambridge, MA, USA, 2001), pp. 402408.
    7. 7)
      • 4. Shyu, K.K., Lee, P.L., Liu, Y.J., Sie, J.J.: ‘Dual-frequency steady-state visual evoked potential for brain computer interface’, Neurosci. Lett., 2010, 483, (1), pp. 2831 (doi: 10.1016/j.neulet.2010.07.043).
    8. 8)
      • 3. Vialatte, F.B., Maurice, M., Dauwels, J., Cichocki, A.: ‘Steady-state visually evoked potentials: focus on essential paradigms and future perspectives’, Prog. Neurobiol., 2010, 90, (4), pp. 418438 (doi: 10.1016/j.pneurobio.2009.11.005).
    9. 9)
      • 6. Zhang, Y., Xu, P., Liu, T., Hu, J., Zhang, R., Yao, D.: ‘Multiple frequencies sequential coding for SSVEP-based brain-computer interface’, Plos One, 2012, 7, (3), pp. e29519 (doi: 10.1371/journal.pone.0029519).

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