EEG SOURCE LOCALIZATION OF ERP BASED ON MULTIDIMENSIONAL SUPPORT VECTOR REGRESSION APPROACH
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.
EEG ISOMAP ERP IRWLS Multidimensional support vector regression IRWLS
JIAN-WEI LI YOU-HUA WANG QING WU YU-FANG WEI JIN-LONG AN
School of Computer Science and Software, Hebei University of Technology, Tianjin 300130 China School of Electrical Engineering and Automation, Hebei University of Technology, Tianjin 300130, Chi
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
1238-1243
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）