Evaluation of adaptive parafac alogorithms for tracking of simulated moving brain sources

Author

Ardeshir Fotouhi;Ehsan Eqlimi;Bahador Makkiabadi

Author_Institution

Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS) and Research Center for Biomedical Technologies and Robotics (RCBTR), Institute for Advanced Medical Technologies (IAMT), Iran

fYear

2015

Firstpage

3819

Lastpage

3822

Abstract

In this paper, we proposed an online 2D localization method for tracking of dynamic moving brain sources. For this purpose, we used an adaptive version of PARAllel FACtor (PARAFAC) analysis for factorization of electroencephalographic (EEG) signals. We utilized Boundary Element Method (BEM) with four layers to solve the forward problem for the simulated EEG signals caused by two moving dipoles within the brain. Then, we created an appropriate tensor built by second order statistics of EEG signals. We adopted an online method to brain source localization called the Recursive Least Squares Tracking (RLST) as an adaptive PARAFAC algorithm with two windowing schemes. Finally, we evaluated the performance of the method applied to EEG signals.

Keywords

"Electroencephalography","Tensile stress","Brain modeling","Covariance matrices","Scalp","Computational modeling","Trajectory"

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE

ISSN

1094-687X

Electronic_ISBN

1558-4615

Type

conf

DOI

10.1109/EMBC.2015.7319226

Filename

7319226