Special Section on Quality Control by Artificial Vision: Nonconventional Imaging Systems

Tracking of electroencephalography signals across brain lobes using motion estimation and cross-correlation

[+] Author Affiliations
Seng Hooi Lim, Humaira Nisar, Vooi Voon Yap

Universiti Tunku Abdul Rahman, Faculty of Engineering and Green Technology, Department of Electronic Engineering, Jalan Universiti, Bandar Barat, 31900 Kampar, Malaysia

Seong-O Shim

University of Jeddah, Department of Computer Science, Faculty of Computing and Information Technology, Jeddah, Saudi Arabia

J. Electron. Imaging. 24(6), 061106 (Oct 21, 2015). doi:10.1117/1.JEI.24.6.061106
History: Received June 17, 2015; Accepted September 21, 2015
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Abstract.  Electroencephalography (EEG) is the signal generated by electrical activity in the human brain. EEG topographic maps (topo-maps) give an idea of brain activation. Functional connectivity helps to find functionally integrated relationship between spatially separated brain regions. Brain connectivity can be measured by several methods. The classical methods calculate the coherence and correlation of the signal. We have developed an algorithm to map functional neural connectivity in the brain by using a full search block matching motion estimation algorithm. We have used oddball paradigm to examine the flow of activation across brain lobes for a specific activity. In the first step, the EEG signal is converted into topo-maps. The flow of activation between consecutive frames is tracked using full search block motion estimation, which appears in the form of motion vectors. In the second step, vector median filtering is used to obtain a smooth motion field by removing the unwanted noise. For each topo-map, several activation paths are tracked across various brain lobes. We have also developed correlation activity maps by following the correlation coefficient paths between electrodes. These paths are selected when the correlation coefficient between electrodes is >70%. We have compared the motion estimation path with the correlation coefficient activation maps. The tracked paths obtained by using motion estimation and correlation give very similar results. The inter-subject comparison shows that four out of five subjects tracked path involves all four (occipital, temporal, parietal, frontal) brain lobes for the same stimuli. The intra-subject analysis shows that three out of five subjects show different tracked lobes for different stimuli.

© 2015 SPIE and IS&T

Citation

Seng Hooi Lim ; Humaira Nisar ; Vooi Voon Yap and Seong-O Shim
"Tracking of electroencephalography signals across brain lobes using motion estimation and cross-correlation", J. Electron. Imaging. 24(6), 061106 (Oct 21, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.6.061106


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