Reduced spatially correlated noise influence using subspace source localization method FINES

Author

Ding, Lei ; Xiaoliang Xu ; Xu, Bobby ; Ni, Ying ; He, Bin

Author_Institution

Minnesota Univ., MN, USA

Volume

2

fYear

2004

fDate

1-5 Sept. 2004

Firstpage

4393

Lastpage

4396

Abstract

We have developed a high resolution subspace approach for EEG source localization within a realistic geometry inhomogeneous head model. The present study aims to reduce the influence caused by spatially correlated noise from background activities using FINES. Computer simulations were conducted on the realistic geometry head volume conductor model and compared with the classic MUSIC algorithm. The FINES approach was also applied to source localization of motor potentials induced by the execution of finger movement in a human subject. The present results suggest that FINES is insensitive to spatially correlated noise, and has enhanced performance as compared with MUSIC.

Keywords

bioelectric potentials; biomechanics; brain models; electroencephalography; medical signal processing; noise; EEG; FINES method; MUSIC algorithm; finger movement; inhomogeneous head model; motor potentials; realistic geometry head volume conductor model; reduced spatially correlated noise influence; subspace source localization method; Background noise; Brain modeling; Computational geometry; Computer simulation; Conductors; Electroencephalography; Multiple signal classification; Noise reduction; Solid modeling; Spatial resolution; EEG; FINES; MUSIC; brain array manifold; multiple dipole localization; subspace;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-8439-3

Type

conf

DOI

10.1109/IEMBS.2004.1404222

Filename

1404222