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Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs

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4 Author(s)
Zhonglin Lin ; Dept. of Autom., Tsinghua Univ., Beijing ; Changshui Zhang ; Wei Wu ; Xiaorong Gao

Canonical correlation analysis (CCA) is applied to analyze the frequency components of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG). The essence of this method is to extract a narrowband frequency component of SSVEP in EEG. A recognition approach is proposed based on the extracted frequency features for an SSVEP-based brain computer interface (BCI). Recognition Results of the approach were higher than those using a widely used fast Fourier transform (FFT)-based spectrum estimation method

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Biomedical Engineering, IEEE Transactions on  (Volume:53 ,  Issue: 12 )