Classification of propofol-induced sedation states using brain connectivity analysis

Dheeraj Rathee, Hubert Cecotti, Girijesh Prasad

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Abstract

Brain connectivity measurements can provide key information about ongoing brain processes. In this paper, we propose to investigate the performance of the binary classification of Propofol-induced sedation states using partial granger causality analysis. Based on the brain connectivity measurements obtained from EEG signals in a database that contains four sedation states: baseline, mild, moderate, and recovery, we consider eight sensors and evaluate the area under the ROC curve with five classifiers: the k-nearest neighbor (density method), support vector machine, linear discriminant analysis, Bayesian discriminant analysis, and a model based on extreme learning machine. The results support the conclusion that the different Propofol-induced sedation states can be identified with anAUCofaround0.75,byconsideringsignalsegmentsofonly4 second. These results highlight the discriminant power that can be obtained from scalp level connectivity measures for online brain monitoring.
Original languageEnglish
Title of host publicationProc. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Number of pages4
ISBN (Electronic)978-1-5386-3646-6
Publication statusPublished - 29 Oct 2018
Event2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, United States
Duration: 18 Jul 201921 Jul 2019
https://ieeexplore.ieee.org/xpl/conhome/8471725/proceeding

Conference

Conference2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
CountryUnited States
CityHonolulu, HI
Period18/07/1921/07/19
Internet address

Keywords

  • propofol-induced sedation
  • brain connectivity analysis
  • EEG
  • Classification

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  • Cite this

    Rathee, D., Cecotti, H., & Prasad, G. (2018). Classification of propofol-induced sedation states using brain connectivity analysis. In Proc. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)