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Evaluation of Adaptive Parafac Alogorithms for Tracking of Simulated Moving Brain Sources Publisher Pubmed



Fotouhi A1 ; Eqlimi E1 ; Makkiabadi B1
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Authors Affiliations
  1. 1. Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran

Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS Published:2015


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. © 2015 IEEE.
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