A High-Speed Brain Speller using steady-State Visual evoked potentials

By Masaki Nakanishi, Yu-Te Wang, Yasue Mitsukura, Tzyy-Ping Jung. International Journal of Neural Systems, 2014

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Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis (2017, methodology): “In our recent studies, we proposed an extended CCA-based method to combine CCA-based spatial filtering and template matching to detect SSVEPs [4], [18].”
Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface (2015, methodology): “%) and ITR (151 bits min − 1 ) in the online BCI experiments, which was very close to the BCI performance reported in the study by Nakanishi et al (2014b) (accuracy: 91%; ITR: 167 bits min − 1 ).”
High-speed spelling with a noninvasive brain–computer interface (2015, background): “In two recent studies, we demonstrated the prototype systems of SSVEP-based BCI spellers with ITRs around 2.5 bps (17, 19).”
A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials (2015, methodology): “Nakanishi et al. [5] suggested 5 trials for a 32-target BCI system for the combination method.”