Power Spectrum Estimation Method to Detect Target Frequency from SSVEP Brain Signals

The most critical and important issue is determining the target flicker from the steady-state visual evoked potential (SSVEP) brain signal. SSVEP-based BCI technology is mainly utilized to control external devices by detecting the target frequency when the user concentrates on the visual flickering frequency. The effectiveness of several power spectrum estimating (PSE) techniques for identifying SSVEP responses from recorded EEG time series data is evaluated by the authors in this work. The IMFs that fall in the range of target frequency are further passed through PSE methods for target frequency detection. Various PSE methods such as FFT, Welch, Burg, and Yule-walker are applied to plot the magnitude spectrum of corresponding IMFs. The performances of the proposed methods are evaluated using two online single-channel datasets. The recorded EEG signals contain the stimulus frequencies from 6Hz to 15.8Hz. The accuracy of detection of each SSVEP frequency was computed to evaluate the effectiveness of the recommended approach. The final results show that the proposed method EMD + Welch periodogram estimation method outperforms the other proposed methods EMD <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$+\text{FFT}$</tex>, EMD + Burg method, and EMD +Yul-walker.