Paper Info
Title
A new approach to the fusion of EEG and MEG signals using the LCMV beamformer
Abstract
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.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6637841
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
array signal processing,electroencephalography,magnetoencephalography,magnetometers,medical signal processing,optimisation,sensor fusion,spatial filters,EEG signal fusion,LCMV beamformer,MEG sensors,MEG signal fusion,gradiometer sensors,linearly constraint minimum variance spatial filter,magnetoencephalography,magnetometer sensors,multichannel signal fusion,multimodal fusion,multiplicative errors,optimisation,under-determined problem,LCMV beamformer,gradiometer,magnetoencephalography,magnetometer,sensor fusion
Minimum-variance unbiased estimator,Multiplicative function,Pattern recognition,Computer science,Gradiometer,Sensor fusion,Artificial intelligence,Electroencephalography,Magnetoencephalography,Spatial filter,Bounded function
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
6
5
Name
Order
Citations
PageRank
Hamid Reza Mohseni1754.65
Morten L. Kringelbach218521.07
Mark W Woolrich3172394.51
Tipu Z. Aziz416813.34
Penny Probert Smith5153.59