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Review Article | Open Access

Algorithm contest of motor imagery BCI in the World Robot Contest 2022: A survey

Jiayu An1,2,§, Xinru Chen1,2,§, Dongrui Wu1,2( )
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei, China
Shenzhen Huazhong University of Science and Technology Research Institute, Shenzhen, Guangdong, China

§ These authors contributed equally to this work.

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Abstract

From August 19 to 21, 2022, the BCI Controlled Robot Contest finals in the World Robot Contest 2022 were held in Beijing, China. Fifteen teams participated in the finals in the Algorithm Contest of Motor Imagery BCI. This paper introduces the algorithms in the motor imagery (MI) classification area, describes the competition content and set, and summarizes the algorithms and results of the top five teams in the finals.

First, the MI paradigm and the overview of the existing motor imagery brain–computer interface classification algorithms are introduced, followed by the introduction of the algorithms of the top five teams in the final step by step, including electroencephalography channel selection, data length selection, data preprocessing, data augmentation, classification network, training, and testing settings. Finally, the highlights and results of each algorithm are discussed.

Keywords

convolutional neural networkmotor imageryEEGNetbrain–computer interfaceWorld Robot Contest 2022

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Brain Science Advances
Volume 9 Issue 3,
September 2023
Pages 166-181
DOI: 10.26599/BSA.2023.9050011
Cite this article:
An J, Chen X, Wu D. Algorithm contest of motor imagery BCI in the World Robot Contest 2022: A survey. Brain Science Advances, 2023, 9(3): 166-181. https://doi.org/10.26599/BSA.2023.9050011

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Received: 16 February 2023
Revised: 07 April 2023
Accepted: 19 April 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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