论文信息 - EEG source reconstruction based on the boundary-element method and weighted minimum norm approaches

EEG source reconstruction based on the boundary-element method and weighted minimum norm approaches

Within the frames of the boundary-element method (BEM) and weighted minimum norm (WMN) estimation, the electroencephalogram (EEG) sources distribution images are reconstructed. In order to solve the ill-conditioning problem caused by the low conductivity of the skull, an improved BEM with an adjustable parameter isolated problem is presented to solve the EEG forward problem. Combined with BEM results, a hybrid WMN solution to the EEG inverse problem is analyzed. The simulation experiments are also given.

[1] Mingni Sun,et al. An efficient algorithm for computing multishell spherical volume conductor models in EEG dipole source localization. , 1997, IEEE transactions on bio-medical engineering.

[2] M. Fuchs,et al. An improved boundary element method for realistic volume-conductor modeling , 1998, IEEE Transactions on Biomedical Engineering.

[3] Z. Koles,et al. Trends in EEG source localization. , 1998, Electroencephalography and clinical neurophysiology.

[4] S. Gonzalez-Andino,et al. A critical analysis of linear inverse solutions to the neuroelectromagnetic inverse problem , 1998, IEEE Transactions on Biomedical Engineering.

[5] S. Ueno,et al. Weighted minimum-norm source estimation of magnetoencephalography utilizing the temporal information of the measured data , 1998 .

[6] Bhaskar D. Rao,et al. Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm , 1997, IEEE Trans. Signal Process..