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

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.