Application and Research Development of Spatial Filtering Method in Brain-Computer Interfaces
Wang Tao1, Ke Yufeng2#*, Wang Ningci1, Liu Wentao2, An Xingwei2, Ming Dong1,2#*
1(School of Precision Instruments and Optoelectronics Engineering, Tianjin University 300072, China) 2(Academy of Medical Engineering and Translational Medicine, Tianjin University. 300072, China)
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.
王韬, 柯余峰, 王宁慈, 刘文陶, 安兴伟, 明东. 空间滤波方法在脑-机接口中的应用及研究进展[J]. 中国生物医学工程学报, 2019, 38(5): 599-608.
Wang Tao, Ke Yufeng, Wang Ningci, Liu Wentao, An Xingwei, Ming Dong. Application and Research Development of Spatial Filtering Method in Brain-Computer Interfaces. Chinese Journal of Biomedical Engineering, 2019, 38(5): 599-608.
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