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Novel Methods for Measuring Depth of Anesthesia by Quantifying Dominant Information Flow in Multichannel EEGs

Authors
Cha, Kab-MunChoi, Byung-MoonNoh, Gyu-JeongShin, Hyun-Chool
Issue Date
Mar-2017
Publisher
HINDAWI LTD
Citation
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
Journal Title
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/7402
DOI
10.1155/2017/3521261
ISSN
1687-5265
Abstract
In this paper, we propose novel methods for measuring depth of anesthesia (DOA) by quantifying dominant information flow in multichannel EEGs. Conventional methods mainly use few EEG channels independently and most of multichannel EEG based studies are limited to specific regions of the brain. Therefore the function of the cerebral cortex over wide brain regions is hardly reflected in DOA measurement. Here, DOA is measured by the quantification of dominant information flow obtained from principle bipartition. Three bipartitioningmethods are used to detect the dominant information flowin entire EEG channels and the dominant information flow is quantified by calculating information entropy. High correlation between the proposedmeasures and the plasma concentration of propofol is confirmed fromthe experimental results of clinical data in 39 subjects. To illustrate the performance of the proposedmethodsmore easily we present the results formultichannel EEG on a two-dimensional (2D) brainmap.
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