EEG sub-bands based sleep stages classification using Fourier Synchrosqueezed transform features-Reference-Cited by-同舟云学术

EEG sub-bands based sleep stages classification using Fourier Synchrosqueezed transform features

Published:2023-02 Issue: Volume:212 Page:118752
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Zaidi Tehreem Fatima,Farooq Omar

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference41 articles.

1. Sleep stage classification using EEG signal analysis: A comprehensive survey and new investigation;Aboalayon;Entropy,2016

2. Nonlinear dynamics measures for automated EEG-based sleep stage detection;Acharya;European Neurology,2015

3. Non-linear analysis of EEG signals at various sleep stages;Acharya;Computer Methods and Programs in Biomedicine,2005

4. Time-frequency reassignment and synchrosqueezing: An overview;Auger;IEEE Signal Processing Magazine,2013

5. A graph-temporal fused dual-input convolutional neural network for detecting sleep stages from EEG signals;Cai;IEEE Transactions on Circuits and Systems II: Express Briefs,2021

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