An improved model for the use of facial stimulation in hybrid SSVEP+P300 brain-computer interfaces
1 Research Scholar, Institute of Engineering and Technology, Srinivas University, Mangalore, India,
2 Associate Professor, College of Computer Science and Information Science, Srinivas University, India,
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2023, 08(01), 330–339.
Article DOI: 10.30574/wjaets.2023.8.1.0046
Publication history:
Received on 06 January 2023; revised on 15 February 2023; accepted on 17 February 2023
Abstract:
Purpose: This research proposes a hybrid BCI that integrates Steady State Visual Evoked Potentials (SSVEP) and Event Related Potentials (P300) simultaneously. We included human facial structure into a visual stimulus to elicit stronger cortical responses in a hybrid SSVEP+P300 BCI. We also discussed the possibilities of triggering one potential with facial stimuli and another with non-facial stimuli.
Methods: To elicit SSVEP and P300 responses, non-face and neutral-face stimulus paradigms are presented. We also tested the neutral-face and flicker paradigm, in which non-face stimuli would elicit SSVEP and neutral-face stimuli would elicit P300.
Results: The results showed that the latter paradigm evoked more robust cortical potentials, leading to enhanced system accuracy and ITR. The neutral-face and flicker paradigm has an average accuracy of 91.62%, with an average system communication rate of 22.04 bits per second.
Conclusions: The author talked about visual stimulus characteristics that might change the way that multiple brain potentials are activated simultaneously and how that affects the individual potentials.
Keywords:
Neutral-face stimuli; Non-face stimuli; Hybrid SSVEP+P300 BCI; Visual stimulus characteristics
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0