Title :
Whitening 1/f-type noise in electroencephalogram signals for steady-state visual evoked potential brain-computer interfaces
Author :
Paris, Alan ; Vosoughi, Azadeh ; Atia, George
Abstract :
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.
Keywords :
1/f noise; brain-computer interfaces; electroencephalography; spectral analysis; visual evoked potentials; α-pitch spectra; ∝-pitch domain; electroencephalogram data; electroencephalogram signals; gamma-band brain-computer interfaces; nonlinear spectral transformation; octave-averaged spectral rectification; resonance peaks; steady-state visual evoked potentials; whiten 1-f-type background noise; whitening 1/f-type noise; Decision support systems; Noise; Visualization;
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
DOI :
10.1109/ACSSC.2014.7094428
