面向运动意图解码的共空间模式及其扩展算法研究综述

doi:10.3969/j.issn.0258-8021.2022.05.007

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Abstract Motor imagery based-brain-computer interfaces (MI-BCIs) are of important research significance and application value in rehabilitation, replacement, and enhancement of human motor function. Common spatial pattern (CSP) algorithm aims to enhance the difference of electroencephalography (EEG) features induced by MI, which is currently one of the most widely used feature extraction algorithms for MI paradigm. However, it does not focus on the time and frequency domain information of EEG, and is sensitive to noise and deviation values, resulting in the limited recognition performance and the low robustness of classifiers. This paper reviewed the development history of CSP and its extended algorithms. We introduced the basic principles and key calculation steps of representative extended algorithms in detail from three aspects: multi-modal information optimization, regularization optimization and other spatial mapping optimization methods. In addition, we discussed the actual challenges and predict the future development trend, aiming to promote the in-depth research and application of relevant BCI technology.

Key words： common spatial pattern brain-computer interface motor imagery feature extraction

Received: 04 March 2021

PACS:

R318

Corresponding Authors: * E-mail: flora_wk@tju.edu.cn

About author:: ^#Member, Chinese Society of Biomedical Engineering

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	Pan Lincong
	Wang Kun
	Xu Minpeng
	Ni Guangjian
	Ming Dong

Cite this article:

Pan Lincong,Wang Kun,Xu Minpeng, et al. Review of Researches on Common Spatial Pattern and its Extended Algorithms for MovementIntention Decoding[J]. Chinese Journal of Biomedical Engineering, 2022, 41(5): 577-588.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2022.05.007 OR http://cjbme.csbme.org/EN/Y2022/V41/I5/577

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