Tracking of EEG activity using motion estimation to understand brain wiring

Nisar, H. and Malik, A.S. and Ullah, R. and Shim, S.-O. and Bawakid, A. and Khan, M.B. and Subhani, A.R. (2015) Tracking of EEG activity using motion estimation to understand brain wiring. Advances in Experimental Medicine and Biology, 823. pp. 159-174. ISSN 00652598

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Abstract

The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes. © Springer International Publishing Switzerland 2015.

Item Type: Article
Additional Information: cited By 4
Uncontrolled Keywords: algorithm; alpha rhythm; Article; beta rhythm; brain cortex; brain mapping; central lobe; delta rhythm; diamond search algorithm; electroencephalogram; four step search algorithm; frontal lobe; full search block matching; gamma rhythm; mathematical model; motion estimation algorithm; new three step search algorithm; occipital lobe; orthogonal search algorithm; parietal lobe; process optimization; signal processing; temporal lobe; theta rhythm; three step search algorithm; two dimensional logarithmic search algorithm; biological model; brain; electroencephalography; human; motion; physiology; procedures, Algorithms; Brain; Brain Mapping; Electroencephalography; Humans; Models, Neurological; Motion
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:18
Last Modified: 09 Nov 2023 16:18
URI: https://khub.utp.edu.my/scholars/id/eprint/6428

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