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Particle filters and beamforming for EEG source estimation

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Particle filters and beamforming for EEG source estimation. / Georgieva, Petia; Mihaylova, Lyudmila; Bouaynaya, Nidhal et al.
Neural Networks (IJCNN), The 2012 International Joint Conference on. Brisbane, Australia: IEEE, 2012. p. 1-8.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Georgieva, P, Mihaylova, L, Bouaynaya, N & Jain, L 2012, Particle filters and beamforming for EEG source estimation. in Neural Networks (IJCNN), The 2012 International Joint Conference on. IEEE, Brisbane, Australia, pp. 1-8, 2012 IEEE World Congress on Computational Intelligence, Brisbane, Australia, 10/06/12. https://doi.org/10.1109/IJCNN.2012.6252516

APA

Georgieva, P., Mihaylova, L., Bouaynaya, N., & Jain, L. (2012). Particle filters and beamforming for EEG source estimation. In Neural Networks (IJCNN), The 2012 International Joint Conference on (pp. 1-8). IEEE. https://doi.org/10.1109/IJCNN.2012.6252516

Vancouver

Georgieva P, Mihaylova L, Bouaynaya N, Jain L. Particle filters and beamforming for EEG source estimation. In Neural Networks (IJCNN), The 2012 International Joint Conference on. Brisbane, Australia: IEEE. 2012. p. 1-8 doi: 10.1109/IJCNN.2012.6252516

Author

Georgieva, Petia ; Mihaylova, Lyudmila ; Bouaynaya, Nidhal et al. / Particle filters and beamforming for EEG source estimation. Neural Networks (IJCNN), The 2012 International Joint Conference on. Brisbane, Australia : IEEE, 2012. pp. 1-8

Bibtex

@inproceedings{d03cdc1999a0467dad912eb41e665158,
title = "Particle filters and beamforming for EEG source estimation",
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 = "EEG, Source localisation, Particle filter (PF), Beamforming, Inverse problems, brain electrical source localization , filtering and state estimation , hidden markov models",
author = "Petia Georgieva and Lyudmila Mihaylova and Nidhal Bouaynaya and Lakhmi Jain",
year = "2012",
month = jun,
day = "1",
doi = "10.1109/IJCNN.2012.6252516",
language = "English",
isbn = "978-1-4673-1488-6",
pages = "1--8",
booktitle = "Neural Networks (IJCNN), The 2012 International Joint Conference on",
publisher = "IEEE",
note = "2012 IEEE World Congress on Computational Intelligence ; Conference date: 10-06-2012 Through 15-06-2012",

}

RIS

TY - GEN

T1 - Particle filters and beamforming for EEG source estimation

AU - Georgieva, Petia

AU - Mihaylova, Lyudmila

AU - Bouaynaya, Nidhal

AU - Jain, Lakhmi

PY - 2012/6/1

Y1 - 2012/6/1

N2 - 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.

AB - 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.

KW - EEG

KW - Source localisation

KW - Particle filter (PF)

KW - Beamforming

KW - Inverse problems

KW - brain electrical source localization

KW - filtering and state estimation

KW - hidden markov models

U2 - 10.1109/IJCNN.2012.6252516

DO - 10.1109/IJCNN.2012.6252516

M3 - Conference contribution/Paper

SN - 978-1-4673-1488-6

SP - 1

EP - 8

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

PB - IEEE

CY - Brisbane, Australia

T2 - 2012 IEEE World Congress on Computational Intelligence

Y2 - 10 June 2012 through 15 June 2012

ER -