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sensor fusion refers to algorithms which could be applied to a number of sensors in order to extract low noise source signals
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In EEG signal processing, we could apply beamformers and spatial filters to dense EEG sensors in 3d head volume in order to extract source signals from desired brain locations. These algorithms are called solutions for the inverse problem.
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To extract source signals from inverse solutions, the transfer function from source to sensors is needed, which is considered as a forward problem.
published paper: A robust beamforming approach for early detection of readiness potential with application to brain-computer interface systems
https://github.com/MaryMahmoodi/EEG_forward_inverse_problem
- lcmv beamformer
- Laplacian spatial filter
- tangential electric field
https://github.com/MaryMahmoodi/spatial-filter-for-dense-EEG-analysis