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

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

8

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2012 International Joint Conference on

Conference_Location

Brisbane, QLD

ISSN

2161-4393

Print_ISBN

978-1-4673-1488-6

Electronic_ISBN

2161-4393

Type

conf

DOI

10.1109/IJCNN.2012.6252516

Filename

6252516