Whitening 1/f-type noise in electroencephalogram signals for steady-state visual evoked potential brain-computer interfaces

A method is proposed to whiten 1-f-type background noise in electroencephalogram data by a nonlinear spectral transformation from the frequency domain to a newly-defined ∝-pitch domain. Based on the α-pitch spectra of steady-state visual evoked potentials, an algorithm called octave-averaged spectral rectification is applied which simultaneously attenuates 1-f noise while enhancing resonance peaks. This has important potential benefits for gamma-band brain-computer interfaces.