Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

Abstract

OBJECTIVE Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, as the number of commands increases. This paper develops a novel unsupervised method based on canonical… (More)
DOI: 10.1088/1741-2552/aa5847

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Cite this paper

@article{Islam2017UnsupervisedFM, title={Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.}, author={Md Rabiul Islam and Md Khademul Islam Molla and Masaki Nakanishi and Toshihisa Tanaka}, journal={Journal of neural engineering}, year={2017}, volume={14 2}, pages={026007} }