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Tracking single dynamic MEG dipole sources using the projected extended Kalman filter

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2 Author(s)
Yuchen Yao ; Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA ; A. Lee Swindlehurst

This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

Published in:

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Date of Conference:

Aug. 30 2011-Sept. 3 2011