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A new approach to the fusion of EEG and MEG signals using the LCMV beamformer

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  • H.R. Mohseni, University of Oxford
  • ,
  • Morten L. Kringelbach
  • M.W. Woolrich, University of Oxford
  • ,
  • T.Z. Aziz, John Radcliffe Hospital
  • ,
  • P.P. Smith, University of Oxford , United Kingdom
In this paper, we demonstrate a new approach for the fusion of multichannel signals. We show how this method can be used to combine signals from magnetometer and gradiometer sensors used in magnetoencephalography (MEG). This approach works by assuming that the lead-fields have multiplicative errors which in turn leads to an under-determined problem. To solve this problem, we impose two constraints that result in closed-from solutions: i) one set of sensors is error-free, ii) the norm of the multiplicative error is bounded. These prior assumptions to estimate the error are used in the linearly constraint minimum variance (LCMV) spatial filter to improve the optimisation. Although we focus on the fusion of MEG sensors, this approach can be employed for multimodal fusion of other multichannel signals such as MEG and EEG signals.
Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Number of pages5
Publication year18 Oct 2013
ISBN (print)9781479903566
Publication statusPublished - 18 Oct 2013

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