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

机译:通过量化多通道脑电图中主要信息流来测量麻醉深度的新方法

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摘要

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 bipartitioning methods are used to detect the dominant information flow in entire EEG channels and the dominant information flow is quantified by calculating information entropy. High correlation between the proposed measures and the plasma concentration of propofol is confirmed from the experimental results of clinical data in 39 subjects. To illustrate the performance of the proposed methods more easily we present the results for multichannel EEG on a two-dimensional (2D) brain map.
机译:在本文中,我们提出了一种通过量化多通道脑电图的主要信息流来测量麻醉深度(DOA)的新方法。常规方法主要独立地使用很少的EEG通道,并且大多数基于多通道EEG的研究仅限于大脑的特定区域。因此,在DOA测量中很难反映出大脑皮层在整个大脑区域的功能。在这里,DOA是通过从原理划分中获得的主导信息流的量化来衡量的。三种划分方法用于检测整个EEG通道中的主导信息流,并通过计算信息熵来量化主导信息流。从39名受试者的临床数据的实验结果证实了拟议措施与丙泊酚血浆浓度之间的高度相关性。为了更轻松地说明所提出方法的性能,我们在二维(2D)脑图上展示了多通道脑电图的结果。

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