Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm

作者：

Highlights：

• Correlation graphs are used to identify EEG sleep stages.

• Different modularity algorithms are tested and investigated.

• An ensemble machine learning is designed to classify graphs attributes.

• MCDM is used to select classifiers to design an ensemble machine learning.

摘要

•Correlation graphs are used to identify EEG sleep stages.•Different modularity algorithms are tested and investigated.•An ensemble machine learning is designed to classify graphs attributes.•MCDM is used to select classifiers to design an ensemble machine learning.

论文关键词：Community detection,EEG signal,Sleep stages classification,Ensemble model,Correlation coefficient

论文评审过程：Received 9 October 2018, Revised 27 April 2019, Accepted 3 July 2019, Available online 13 July 2019, Version of Record 19 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.007