Classification Accuracy Improvement of Chromatic and High–Frequency Code–Modulated Visual Evoked Potential–Based BCI

  • Daiki Aminaka
  • Shoji Makino
  • Tomasz M. Rutkowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9250)


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.


Brain–computer interfaces ERP cVEP EEG classification 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Daiki Aminaka
    • 1
  • Shoji Makino
    • 1
  • Tomasz M. Rutkowski
    • 1
  1. 1.Life Science Center of TARA at University of TsukubaTsukuba, IbarakiJapan

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