Evaluating the Performance of Kalman-Filter-Based EEG Source Localization

@article{Barton2009EvaluatingTP,
  title={Evaluating the Performance of Kalman-Filter-Based EEG Source Localization},
  author={Matthew J. Barton and Peter A. Robinson and Suresh Kumar and Andreas Galka and Hugh F. Durrant-Whyte and Jos{\'e} E. Guivant and Tohru Ozaki},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2009},
  volume={56},
  pages={122-136}
}
Electroencephalographic (EEG) source localization is an important tool for noninvasive study of brain dynamics, due to its ability to probe neural activity more directly, with better temporal resolution than other imaging modalities. One promising technique for solving the EEG inverse problem is Kalman filtering, because it provides a natural framework for incorporating dynamic EEG generation models in source localization. Here, a recently developed inverse solution is introduced, which uses… CONTINUE READING

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