**1.4. Feature extraction**

Various features are procured from the properties of the brain signals that have discriminative information embedded in them. Various feature extraction techniques are used to extract such features when overlapped in time and space by several brain signals.

The feature extraction in SSVEP signals was often done with the study of amplitude in the target frequency [12–14], followed by independent component analysis (ICA) [16], the fast Fourier transform (FFT) [15], continuous wavelet transform (CWT) [17, 18], Hilbert-Huang transform (HHT) [19, 20] or the PSD [21] can be used.
