Comput Math Methods Med - An efficient frequency recognition method based on likelihood ratio test for SSVEP-based BCI.

Tópicos

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Resumo

An efficient frequency recognition method is very important for SSVEP-based BCI systems to improve the information transfer rate (ITR). To address this aspect, for the first time, likelihood ratio test (LRT) was utilized to propose a novel multichannel frequency recognition method for SSVEP data. The essence of this new method is to calculate the association between multichannel EEG signals and the reference signals which were constructed according to the stimulus frequency with LRT. For the simulation and real SSVEP data, the proposed method yielded higher recognition accuracy with shorter time window length and was more robust against noise in comparison with the popular canonical correlation analysis- (CCA-) based method and the least absolute shrinkage and selection operator- (LASSO-) based method. The recognition accuracy and information transfer rate (ITR) obtained by the proposed method was higher than those of the CCA-based method and LASSO-based method. The superior results indicate that the LRT method is a promising candidate for reliable frequency recognition in future SSVEP-BCI.

Resumo Limpo

effici frequenc recognit method import ssvepbas bci system improv inform transfer rate itr address aspect first time likelihood ratio test lrt util propos novel multichannel frequenc recognit method ssvep data essenc new method calcul associ multichannel eeg signal refer signal construct accord stimulus frequenc lrt simul real ssvep data propos method yield higher recognit accuraci shorter time window length robust nois comparison popular canon correl analysi cca base method least absolut shrinkag select oper lasso base method recognit accuraci inform transfer rate itr obtain propos method higher ccabas method lassobas method superior result indic lrt method promis candid reliabl frequenc recognit futur ssvepbci

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