The Experts below are selected from a list of 192 Experts worldwide ranked by ideXlab platform

Qing Wu - One of the best experts on this subject based on the ideXlab platform.

  • EEG source localization of ERP based on multidimensional support vector regression approach
    2008 International Conference on Machine Learning and Cybernetics, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    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.

  • The Method of Multidimensional Support Vector Regression for Moving Dipole Localization of Face Expression
    2008 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    Abstract:

    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.

  • Application of Multidimensional Support Vector Regression on the EEG source localization
    2008 World Automation Congress, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Xueqin Shen, Jin-long An
    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.

  • EEG source localization using differential evolution method
    The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004
    Co-Authors: Ying Li, Qing Wu, Haitao Li, Renjie He, Guizhi Xu, Xueqin Shen
    Abstract:

    Differential evolution (DE) method is used in This work to solve the EEG source localization problem based on equal current dipole model. The single dipole sources with four-shell Concentric Sphere model are reconstructed. Our simulations demonstrate that DE algorithm is robust in obtaining high quality reconstruction for EEG problems with single current dipole sources.

Jin-long An - One of the best experts on this subject based on the ideXlab platform.

  • EEG source localization of ERP based on multidimensional support vector regression approach
    2008 International Conference on Machine Learning and Cybernetics, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    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.

  • The Method of Multidimensional Support Vector Regression for Moving Dipole Localization of Face Expression
    2008 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    Abstract:

    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.

  • Application of Multidimensional Support Vector Regression on the EEG source localization
    2008 World Automation Congress, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Xueqin Shen, Jin-long An
    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.

Xueqin Shen - One of the best experts on this subject based on the ideXlab platform.

  • Application of Multidimensional Support Vector Regression on the EEG source localization
    2008 World Automation Congress, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Xueqin Shen, Jin-long An
    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.

  • EEG source localization using differential evolution method
    The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004
    Co-Authors: Ying Li, Qing Wu, Haitao Li, Renjie He, Guizhi Xu, Xueqin Shen
    Abstract:

    Differential evolution (DE) method is used in This work to solve the EEG source localization problem based on equal current dipole model. The single dipole sources with four-shell Concentric Sphere model are reconstructed. Our simulations demonstrate that DE algorithm is robust in obtaining high quality reconstruction for EEG problems with single current dipole sources.

Jianwei Li - One of the best experts on this subject based on the ideXlab platform.

  • EEG source localization of ERP based on multidimensional support vector regression approach
    2008 International Conference on Machine Learning and Cybernetics, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    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.

  • The Method of Multidimensional Support Vector Regression for Moving Dipole Localization of Face Expression
    2008 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Jin-long An
    Abstract:

    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.

  • Application of Multidimensional Support Vector Regression on the EEG source localization
    2008 World Automation Congress, 2008
    Co-Authors: Jianwei Li, Youhua Wang, Qing Wu, Xueqin Shen, Jin-long An
    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.

Bin He - One of the best experts on this subject based on the ideXlab platform.

  • Estimation of Cortical Dipole Sources by Equivalent Dipole Layer Imaging and Independent Component Analysis
    2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
    Co-Authors: Naotoshi Aoki, Junichi Hori, Bin He
    Abstract:

    We explored suitable estimation method for equivalent dipole sources in the brain. In a previous study, we solved an inverse problem that estimated an equivalent dipole-layer distribution from the scalp electroencephalogram by a spatio-temporal inverse filters constructed with parametric projection filter. In the present study, we estimated equivalent dipole sources from dipole layer distributions. Moreover, to identify the number, position, and moment of equivalent dipole sources, we separated each dipole layer distribution using independent component analysis (ICA). The performance of the proposed estimation method was evaluated by computer simulation and human experimental studies in an inhomogeneous three-Concentric Sphere head model. The present simulation results indicated that the equivalent dipole sources was accurately estimated by ICA and dipole imaging. We also applied the proposed method to human visual evoked potential

  • An equivalent current source model and Laplacian weighted minimum norm current estimates of brain electrical activity
    IEEE Transactions on Biomedical Engineering, 2002
    Co-Authors: Bin He, J. Lian, D. Wu
    Abstract:

    We have developed a method for estimating the three-dimensional distribution of equivalent current sources inside the brain from scalp potentials. Laplacian weighted minimum norm algorithm has been used in the present study to estimate the inverse solutions. A three-Concentric-Sphere inhomogeneous head model was used to represent the head volume conductor. A closed-form solution of the electrical potential over the scalp and inside the brain due to a point current source was developed for the three-Concentric-Sphere inhomogeneous head model. Computer simulation studies were conducted to validate the proposed equivalent current source imaging. Assuming source configurations as either multiple dipoles or point current sources/sinks, in computer simulations we used our method to reconstruct these sources, and compared with the equivalent dipole source imaging. Human experimental studies were also conducted and the equivalent current source imaging was performed on the visual evoked potential data. These results highlight the advantages of the equivalent current source imaging and suggest that it may become an alternative approach to imaging spatially distributed current sources-sinks in the brain and other organ systems.

  • A computer simulation study of cortical imaging from scalp potentials
    IEEE Transactions on Biomedical Engineering, 1998
    Co-Authors: Yunhua Wang, Bin He
    Abstract:

    Computer simulation studies were conducted to test the feasibility of imaging brain electrical activity from the scalp electroencephalograms. The inhomogeneous three-Concentric-Sphere head model was used to represent the head volume conductor. Closed spherical dipole layers, consisting of several thousand uniformly distributed dipoles, were used to reconstruct the cortical potential maps corresponding to neuronal sources located inside the brain. Simulation results indicate that the present procedure can image both cortical and deep sources, and for the cortical sources, a spatial resolution as high as 1.2 cm can be achieved.