Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia-Reference-Cited by-同舟云学术

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Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia

Published:2019-10-01 Issue: Volume:13 Page:
ISSN:1662-5188
Container-title:Frontiers in Computational Neuroscience
language:
Short-container-title:Front. Comput. Neurosci.

Author:

Dubost Clement,Humbert Pierre,Benizri Arno,Tourtier Jean-Pierre,Vayatis Nicolas,Vidal Pierre-Paul

Publisher

Frontiers Media SA

Subject

Cellular and Molecular Neuroscience,Neuroscience (miscellaneous)

Reference34 articles.

1. Predicting age from brain eeg signals–a machine learning approach;Al Zoubi;Front. Aging Neurosci.,2018

2. “Effect of feature and channel selection on eeg classification,”;Al-Ani,2006

3. A review of channel selection algorithms for eeg signal processing;Alotaiby;EURASIP J. Adv. Sig. Process.,2015

4. Classification of eeg signals based on pattern recognition approach;Amin;Front. Comput. Neurosci.,2017

5. Optimizing the channel selection and classification accuracy in eeg-based bci;Arvaneh;IEEE Trans. Biomed. Eng.,2011

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1. Spatio-temporal electroencephalographic power distribution in experimental pigs receiving propofol;PLOS ONE;2024-05-14

2. Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment;Artificial Intelligence in Medicine;2024-05

3. Dynamic Cortical Connectivity During Propofol Sedation in Glioma Patients;Journal of Neurosurgical Anesthesiology;2024-04-05

4. Efficacy of tDCS in chronic migraine: A multiprotocol randomized controlled trial;Clinical Neurophysiology;2023-06

5. A Novel Channel Selection Approach for Human Neonate’s Pain EEG Data Analysis;2022-12-28

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