中图分类号： TP391.4
文献标识码： A
DOI： 10.19358/j.issn.2096-5133.2021.01.011
引用格式： 郭闽榕。 基于运动想象的脑电信号特征提取研究[J].信息技术与网络安全，2021，40（1）：62-66.

Feature extraction of EEG signals based on motor imagery Guo Minrong

Abstract： The brain-computer interface（BCI） system based on motor imagery（MI） electroencephalogram（EEG） has a broad application prospect in the medical field, which can be applied to the auxiliary control of the disabled and the prognosis and rehabilitation of the brain.Because of the low SNR, instability and significant difference of EEG signal in motion imagination, it has a negative effect on EEG signal recognition.An effective feature extraction method can enhance the accuracy of EEG in BCI system. In this paper, a multi-channel feature extraction method for EEG signals is proposed.First of all,the data matrix is decomposed into the product of the basis matrix and the coefficient matrix.Then the coefficient matrix is extracted by using the inter-class dispersion as the performance criterion to extract the features with higher separability and less dimension.The experiment of BCI 2008 competition data set shows that the method is effective.

Key words : brain-computer interface；electroencephalogram；motor imagery；feature extraction；matrix decomposition