Title
Whitening 1/F-Type Noise In Electroencephalogram Signals For Steady-State Visual Evoked Potential Brain-Computer Interfaces
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.
Publication Date
4-24-2015
Publication Title
Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume
2015-April
Number of Pages
204-207
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ACSSC.2014.7094428
Copyright Status
Unknown
Socpus ID
84940482435 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84940482435
STARS Citation
Paris, Alan; Vosoughi, Azadeh; and Atia, George, "Whitening 1/F-Type Noise In Electroencephalogram Signals For Steady-State Visual Evoked Potential Brain-Computer Interfaces" (2015). Scopus Export 2015-2019. 1857.
https://stars.library.ucf.edu/scopus2015/1857