文献类型：期刊文献

英文题名：Robust frequency recognition for SSVEP-based BCI with temporally local multivariate synchronization index

作者：Zhang, Yangsong[1];Guo, Daqing[2];Xu, Peng[2];Zhang, Yu[3];Yao, Dezhong[2]

机构：[1]Southwest Univ Sci & Technol, Sch Comp Sci & Technol, Mianyang 621010, Peoples R China;[2]Univ Elect Sci & Technol China, Med Informat Ctr, Key Lab NeuroInformat, Minist Educ, Chengdu 610054, Peoples R China;[3]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2016

卷号：10

期号：6

起止页码：505

外文期刊名：COGNITIVE NEURODYNAMICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000387852900005)】；

基金：This work is supported in part by the National Natural Science Foundation of China (Nos. 81401484, 61527815, 81571770, 61305028) the Doctoral Fund of Southwest University of Science and Technology (Grant No. 15zx7115), and Shanghai Chenguang Program under Grant 14CG31.

语种：英文

外文关键词：Steady-state visual evoked potential (SSVEP); Brain-computer interface (BCI); Multivariate synchronization index (MSI); Temporally local information

摘要：Multivariate synchronization index (MSI) has been proved to be an efficient method for frequency recognition in SSVEP-BCI systems. It measures the correlation according to the entropy of the normalized eigenvalues of the covariance matrix of multichannel signals. In the MSI method, the estimation of covariance matrix omits the temporally local structure of samples. In this study, a new spatio-temporal method, termed temporally local MSI (TMSI), was presented. This new method explicitly exploits temporally local information in modelling the covariance matrix. In order to evaluate the performance of the TMSI, we performs a comparison between the two methods on the real SSVEP datasets from eleven subjects. The results show that the TMSI outperforms the standard MSI. TMSI benefits from exploiting the temporally local structure of EEG signals, and could be a potential method for robust performance of SSVEP-based BCI.