DocumentCode :
1445691
Title :
Projection Versus Prewhitening for EEG Interference Suppression
Author :
Wu, Shun Chi ; Swindlehurst, A. Lee ; Wang, Po T. ; Nenadic, Zoran
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Irvine, CA, USA
Volume :
59
Issue :
5
fYear :
2012
fDate :
5/1/2012 12:00:00 AM
Firstpage :
1329
Lastpage :
1338
Abstract :
Suppression of strong, spatially correlated background interference is a challenge associated with electroencephalography (EEG) source localization problems. The most common way of dealing with such interference is through the use of a prewhitening transformation based on an estimate of the covariance of the interference plus noise. This approach is based on strong assumptions regarding temporal stationarity of the data, which do not commonly hold in EEG applications. In addition, prewhitening cannot typically be implemented directly due to ill conditioning of the covariance matrix, and ad hoc regularization is often necessary. Using both simulation examples and experiments involving real EEG data with auditory evoked responses, we demonstrate that a straightforward interference projection method is significantly more robust than prewhitening for EEG source localization.
Keywords :
auditory evoked potentials; electroencephalography; interference suppression; magnetoencephalography; medical signal processing; signal classification; EEG; MEG; ad hoc regularizetion; auditory evoked responses; electroencephalography; interference plus noise; prewhitening transformation; source localization problems; spatially correlated background interference suppression; temporal stationarity; Brain modeling; Electroencephalography; Interference; Multiple signal classification; Nickel; Noise; Vectors; Electroencephalography (EEG); interference suppression; magnetoencephalography (MEG); sensor array processing; source localization; Algorithms; Brain; Computer Simulation; Electroencephalography; Evoked Potentials, Auditory; Humans; Magnetoencephalography; Models, Theoretical; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2012.2187335
Filename :
6151066
Link To Document :
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