Brain-computer interface (BCI) is a new system which does not rely on the peripheral nervous and muscle tissue, can autonomously control the external devices by inducing human brain ERD/ERS characteristic signals. However, the study found that about 15% to 30% of users existed “BCI blind” problem, which means it is difficult for these users to induce a strong (Event-Related De-synchronization) ERD/(Event-Related Synchronization) ERS signal. This paper are focus on the EEG time series that can be converted into a network whose measures are associated with consciousness, and the results show that PLV binary network can achieve asynchronous BCI system classification.it can be achieved asynchronous BCI system classification, the accuracy is up to 88.60%. It is concluded that the asynchronous BCI system based on brain network technology is feasible and can be used as a new way.
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张微,解承军. 基于复杂网络技术的异步脑-机接口分类系统[J]. 科学技术与工程, 2020, 20(11): 4383-4388. Zhang Wei, Xie Chengjun. Brain-Computer Interface Based on Brain Network Techniques[J]. Science Technology and Engineering,2020,20(11):4383-4388.