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Research Article | Open Access

Overview of recognition methods for SSVEP-based BCIs in World Robot Contest 2022: MATLAB undergraduate group

Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
College of Science, Beijing Forestry University, Beijing 100083, China
Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China
Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China

§ These authors contributed equally to this work.

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Abstract

The steady-state visual evoked potential (SSVEP)-based speller has emerged as a widely adopted paradigm in current brain–computer interface (BCI) systems due to its rapid processing and consistent performance across different individuals. Calibration-free SSVEP algorithms, as opposed to their calibration-based counterparts, offer clear and intuitive mathematical principles, making them accessible to novice developers. During the World Robot Contest (WRC) 2022, participants in the undergraduate category utilized various approaches to accomplish target detection in the calibration-free setting, successfully implementing the algorithms using MATLAB. The winning approach achieved an average information transfer rate of 198.94 bits/min in the final test, which is notably high given the calibration-free scenario. This paper presents an introduction to the underlying principles of the selected methods, accompanied by a comparison of their effectiveness through analysis of results from both the final test and offline experiments. Additionally, we propose that the youth competition of WRC could serve as an ideal starting point for beginners interested in studying and developing their own BCI systems.

Keywords

brain–computer interfaceselectroencephalogramsteady-state visual evoked potentialBCI spellerscalibration-freeMATLAB

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Brain Science Advances
Volume 9 Issue 3,
September 2023
Pages 224-236
DOI: 10.26599/BSA.2023.9050018
Cite this article:
Yi C, Wu Y, Ye F, et al. Overview of recognition methods for SSVEP-based BCIs in World Robot Contest 2022: MATLAB undergraduate group. Brain Science Advances, 2023, 9(3): 224-236. https://doi.org/10.26599/BSA.2023.9050018

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Received: 14 April 2023
Revised: 21 May 2023
Accepted: 06 June 2023
Published: 05 September 2023
© The authors 2023.

This article is published with open access at journals.sagepub.com/home/BSA

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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