Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network

Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network

The reliable monitoring of the depth of anesthesia (DoA) is essential to control the anesthesia procedure. Electroencephalography (EEG) has been widely used to estimate DoA since EEG could reflect the effect of anesthetic drugs on the central nervous system (CNS). In this study, we propose that a de...

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Bibliographic Details
Main Authors: Meng Shi, Ziyu Huang, Guowen Xiao, Bowen Xu, Quansheng Ren, Hong Zhao
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
deep learning
depth of anesthesia
electroencephalogram
patient state index
Online Access:https://www.mdpi.com/1424-8220/23/2/1008

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