Reduction of noise from magnetoencephalography data

@article{Okawa2005ReductionON,
  title={Reduction of noise from magnetoencephalography data},
  author={S. Okawa and S. Honda},
  journal={Medical and Biological Engineering and Computing},
  year={2005},
  volume={43},
  pages={630-637}
}
A noise reduction method for magnetoencephalography (MEG) data is proposed. The method is a combination of Kalman filtering and factor analysis. A statespace model for a Kalman filter was constructed using the forward problem in MEG measurement. Factor analysis provide estimations of noise covariances required by the Kalman filter to eliminate independent additive sensor noise. The proposed method supports independent component analysis (ICA), which is difficult to use in MEG analysis owing to… CONTINUE READING

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