空间滤波方法在脑-机接口中的应用及研究进展

doi:10.3969/j.issn.0258-8021.2019.05.011

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Abstract With the development of brain-computer interface (BCI) technology, it has become a hot research topic to improve the classification accuracy of BCI system by optimizing data processing algorithms. In recent years, in a variety of BCI paradigms, spatial filtering has been found to improve the signal-to-noise ratio of EEG signals and optimize feature extraction, thus improving the classification accuracy of BCIs. Therefore, spatial filtering has an important application value in EEG-based BCIs. This paper reviewed the commonly used spatial filtering methods for EEG signal processing in BCIs, including basic spatial filters, spatial filters for EEG preprocessing and feature dimensionality reduction, and spatial filters used for feature extraction in BCIs based on induced rhythms and evoked potentials. Finally, we summarized the current problems and future developments of spatial filtering methods for EEG in BCIs.

Key words： brain-computer interface data processing spatial filter

Received: 07 January 2019

PACS:

R318

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	Articles by authors
	Wang Tao
	Ke Yufeng
	Wang Ningci
	Liu Wentao
	An Xingwei
	Ming Dong

Cite this article:

Wang Tao,Ke Yufeng,Wang Ningci, et al. Application and Research Development of Spatial Filtering Method in Brain-Computer Interfaces[J]. Chinese Journal of Biomedical Engineering, 2019, 38(5): 599-608.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2019.05.011 OR http://cjbme.csbme.org/EN/Y2019/V38/I5/599

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