DocumentCode
476047
Title
EEG source localization of ERP based on multidimensional support vector regression approach
Author
Li, Jian-wei ; Wang, You-hua ; Wu, Qing ; Wei, Yu-fang ; An, Jin-long
Author_Institution
Sch. of Comput. Sci. & Software, Hebei Univ. of Technol., Tianjin
Volume
3
fYear
2008
fDate
12-15 July 2008
Firstpage
1238
Lastpage
1243
Abstract
A new integrated multi-method system is presented to estimate the location and moment of equivalent current dipole sources of event-related potentials (ERP). In order to handle the large-scale high dimension problems efficiently and quickly, the ISOMAP algorithm was used to find the low dimensional manifolds from recorded EEG. Then, based on reduced dimension data, multidimensional support vector regression (MSVR) with similar iterative re-weight least square (IRWLS) was used to discover the relationship between the observation potentials on the scalp and the internal sources within the brain. In our experiments, the two current dipole sources with four-shell concentric sphere model were reconstructed. Our experiments demonstrate that MSVR based on the support vector machine can obtain more robust estimations for EEG source localization problem.
Keywords
bioelectric potentials; electroencephalography; iterative methods; least squares approximations; medical signal processing; regression analysis; signal reconstruction; support vector machines; EEG source localization problem; ISOMAP algorithm; current dipole sources; event-related potentials; iterative reweight least square; large-scale high dimension problems; multidimensional support vector regression; reduced dimension data; Brain modeling; Electroencephalography; Enterprise resource planning; Iterative algorithms; Large-scale systems; Least squares methods; Multidimensional systems; Robustness; Scalp; Support vector machines; EEG; ERP; IRWLS; ISOMAP; Multidimensional support vector regression;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620594
Filename
4620594
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