Title :
Particle filters and beamforming for EEG source estimation
Author :
Georgieva, Petia ; Mihaylova, Lyudmila ; Bouaynaya, Nidhal ; Jain, Lakhmi
Author_Institution :
Dept. of Electron. Telecommun. & Inf. (DETI), Univ. of Aveiro, Aveiro, Portugal
Abstract :
This is a proof of concept work that proposes a solution to the inverse problem of EEG source estimation by combining two techniques, namely a Particle Filter (PF) for geometrical (3D) localization of the most active brain zones (expressed by two dipoles) and a beamformer (BF) as a spatial filter for estimation of the oscillations that have originated the recorded EEG data. The estimation is reliable for uncorrelated brain sources.
Keywords :
array signal processing; electroencephalography; medical signal processing; particle filtering (numerical methods); 3D localization; EEG source estimation; active brain zones; beamforming; geometrical localization; inverse problem; oscillation estimation; particle filters; spatial filter; uncorrelated brain sources; Atmospheric measurements; Brain models; Computational modeling; Electroencephalography; Estimation; Hidden Markov models; brain electrical source localization; filtering and state estimation; hidden markov models;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252516
