Monitoring Depth of Anesthesia Based on Hybrid Features and Recurrent Neural Network

Monitoring Depth of Anesthesia Based on Hybrid Features and Recurrent Neural Network

Electroencephalogram (EEG) signals contain valuable information about the different physiological states of the brain, with a variety of linear and nonlinear features that can be used to investigate brain activity. Monitoring the depth of anesthesia (DoA) with EEG is an ongoing challenge in anesthes...

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Bibliographic Details
Main Authors: Ronglin Li, Qiang Wu, Ju Liu, Qi Wu, Chao Li, Qibin Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-02-01
Series:Frontiers in Neuroscience
Subjects:
autoencoder
LSTM
EEG
anesthesia
feature extraction
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00026/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2020.00026/full

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