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Research Article | Open Access

Overview of the winning approaches in BCI Controlled Robot Contest in World Robot Contest 2021: Calibration-free SSVEP

School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
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Abstract

Recently, steady-state visual evoked potential (SSVEP) has become one of the most popular electroencephalography paradigms due to its high information transfer rate. Several approaches have been proposed to improve the performance of SSVEP. The calibration- free scenario is significant in SSVEP-based brain-computer interface systems, where the subject is the first time to use the system. The participating teams proposed several effective calibration-free algorithm frameworks in the SSVEP competition (calibration-free) of the BCI Controlled Robot Contest in World Robot Contest 2021. This paper introduces the approaches used in the algorithms of the top five teams in the final. The results of the five subjects in the final proved the effectiveness of the approaches. This paper discusses the effectiveness of each approach in improving the system performance in the calibration-free scenario and gives suggestions on how to use these approaches in a real-world system.

Keywords

steady-state visual evoked potentialbrain-computer interfaceselectroencephalogramSSVEP spellerscalibration-free

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Brain Science Advances
Volume 8 Issue 2,
June 2022
Pages 99-110
DOI: 10.26599/BSA.2022.9050002
Cite this article:
Bian R, Wu D. Overview of the winning approaches in BCI Controlled Robot Contest in World Robot Contest 2021: Calibration-free SSVEP. Brain Science Advances, 2022, 8(2): 99-110. https://doi.org/10.26599/BSA.2022.9050002

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Received: 03 January 2022
Revised: 20 February 2022
Accepted: 04 March 2022
Published: 29 June 2022
© The authors 2022.

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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