基于运动想象的脑机接口关键技术研究

doi:10.3969/j.issn.0258-8021.2014. 06.02

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Abstract Motor imagery based braincomputer interface (MI BCI) has been considered as the most promising BCI in practical application. However, several urgent problems need to be solved for MI BCI. Based on our research experience in past several years, this paper discusses the developed methods in our group for signal acquisition, feature extraction, pattern recognition and online BCI system. As for the acquisition aspect, we designed an amplifier that can remove the DC offset effectively. Several improved algorithms based on common spatial pattern (CSP) are developed to increase the immunity to noises. As for pattern recognition, several variants of linear discriminative analysis are developed to improve the recognition rates. Based on those methods, we built a hybrid online BCI system that combined motor imagery and motion onset visual evoked potential (MOVEP).

Key words： motor imagery amplifier common spatial pattern (CSP) pattern recognition motion onset visual evoked potential

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	LIU Tie Jun^＃ZHANG Rui XU Peng^＃*

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LIU Tie Jun^＃ZHANG Rui XU Peng^＃*. Key Techniques in Motor Imagery Based BrainComputer Interface[J]. journal1, 2014, 33(6): 644-651.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2014. 06.02 OR http://cjbme.csbme.org/EN/Y2014/V33/I6/644

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