DocumentCode :
1702431
Title :
Application of Multidimensional Support Vector Regression on the EEG source localization
Author :
Li, Jianwei ; Wang, Youhua ; Wu, Qing ; Shen, Xueqin ; Hou, Shuping ; An, Jinlong
Author_Institution :
Sch. of Comput. Sci. & Software, Hebei Univ. of Technol., Tianjin
fYear :
2008
Firstpage :
1
Lastpage :
5
Abstract :
Multidimensional support vector regression (MSVR) with similar iterative re-weight least square (IRWLS) is firstly used in this paper to estimate the location and moment of an equivalent current dipole source in the inverse problem of electroencephalogram (EEG). In order to discover the relationship between the potentials on the scalp and internal source within the brain, the single current dipole source with four-shell concentric sphere model is reconstructed. Our simulation experiments demonstrate that MSVR based on the support vector machine can obtain more robust estimations for EEG source localization problem with equivalent current dipole model.
Keywords :
electroencephalography; inverse problems; iterative methods; least squares approximations; medical signal processing; regression analysis; signal reconstruction; support vector machines; EEG source localization; brain; electroencephalogram; equivalent current dipole source moment estimation; four-shell concentric sphere model reconstruction; inverse problem; iterative re-weight least square; multidimensional support vector regression; Brain modeling; Current measurement; Electrodes; Electroencephalography; Inverse problems; Magnetic heads; Multidimensional systems; Robustness; Scalp; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Congress, 2008. WAC 2008. World
Conference_Location :
Hawaii, HI
Print_ISBN :
978-1-889335-38-4
Electronic_ISBN :
978-1-889335-37-7
Type :
conf
Filename :
4699281
Link To Document :
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