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Algorithms
Volume 16
Issue 11
10.3390/a16110502
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Article

Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces

by
Alexey Kozin
†,
Anton Gerasimov
†,
Maxim Bakaev
*,
Anton Pashkov
and
Olga Razumnikova
*
Department of Data Collection and Processing Systems, Novosibirsk State Technical University, 630087 Novosibirsk, Russia
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Algorithms 2023, 16(11), 502; https://doi.org/10.3390/a16110502
Submission received: 20 September 2023 / Revised: 21 October 2023 / Accepted: 25 October 2023 / Published: 29 October 2023
(This article belongs to the Special Issue Artificial Intelligence for Medical Imaging)
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Abstract

Brain–computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) are inexpensive and do not require user training. However, the highly personalized reaction to visual stimulation is an obstacle to the wider application of this technique, as it can be ineffective, tiring, or even harmful at certain frequencies. In our experimental study, we proposed a new approach to the selection of optimal frequencies of photostimulation. By using a custom photostimulation device, we covered a frequency range from 5 to 25 Hz with 1 Hz increments, recording the subjects’ brainwave activity (EEG) and analyzing the signal-to-noise ratio (SNR) changes at the corresponding frequencies. The proposed set of SNR-based coefficients and the discomfort index, determined by the ratio of theta and beta rhythms in the EEG signal, enables the automation of obtaining the recommended stimulation frequencies for use in SSVEP-based BCIs.
Keywords: brain–computer interface; steady-state visually evoked potentials; personal response; visual stimulation; frequency selection algorithm; discomfort index brain–computer interface; steady-state visually evoked potentials; personal response; visual stimulation; frequency selection algorithm; discomfort index

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MDPI and ACS Style

Kozin, A.; Gerasimov, A.; Bakaev, M.; Pashkov, A.; Razumnikova, O. Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces. Algorithms 2023, 16, 502. https://doi.org/10.3390/a16110502

AMA Style

Kozin A, Gerasimov A, Bakaev M, Pashkov A, Razumnikova O. Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces. Algorithms. 2023; 16(11):502. https://doi.org/10.3390/a16110502

Chicago/Turabian Style

Kozin, Alexey, Anton Gerasimov, Maxim Bakaev, Anton Pashkov, and Olga Razumnikova. 2023. "Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces" Algorithms 16, no. 11: 502. https://doi.org/10.3390/a16110502

APA Style

Kozin, A., Gerasimov, A., Bakaev, M., Pashkov, A., & Razumnikova, O. (2023). Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces. Algorithms, 16(11), 502. https://doi.org/10.3390/a16110502

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