SSVEP Enhancement Using Moving Average Filter Controlled by Phase Features

Table 1

EEG preprocessing steps and the description of obtained signals.

Symbolic name of the method	The signal for further analysis
CSP	Signal after applying the CSP linear combination
PLS	Signal after applying the PLS projection
MEC	Signal after applying the MEC projection
CAR	Signal after CAR filtration
AMUSE	Signal after applying the AMUSE and removing the first and the last components
SOBI-AF3	Signal after applying the SOBI ICA algorithm and removing the component which has highest correlation with the signal from AF3 electrode
SOBI-OZ	Signal after applying the SOBI ICA algorithm and removing the component which has lowest correlation with the signal from AF3 electrode
SOBI-FFT	Signal after applying the SOBI ICA algorithm and removing the component which has lowest value of the normalized amplitude
Infomax-AF3	Signal after applying the Infomax ICA algorithm and removing the component which has highest correlation with the signal from AF3 electrode
Infomax-OZ	Signal after applying the Infomax ICA algorithm and removing the component which has lowest correlation with the signal from AF3 electrode
Infomax-FFT	Signal after applying the Infomax ICA algorithm and removing the component which has lowest value of the normalized amplitude
JADE-AF3	Signal after applying the JADE ICA algorithm and removing the component which has highest correlation with the signal from AF3 electrode
JADE-OZ	Signal after applying the JADE ICA algorithm and removing the component which has lowest correlation with the signal from AF3 electrode
JADE-FFT	Signal after applying the JADE ICA algorithm and removing the component which has lowest value of the normalized amplitude