The Method of Multidimensional Support Vector Regression for Moving Dipole Localization of Face Expression

Brain signal source localization is a process of inverse calculation from electroencephalogram (EEG) signal. A new method of Multidimensional Support Vector Regression (MSVR) with similar iterative re-weight least square (IRWLS) is firstly used in source localization of face expression. In order to discover the relationship between sensor information and internal source in the brain, the moving dipole with four-shell concentric sphere model was reconstructed. Its location parameters and components were fitted in a series of time points. EEG signals of face expression were adopted in our experiments. Satisfactory results demonstrate that MSVR based on the support vector machine can obtain more robust estimations for EEG inverse problem.