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Effective brain state estimation during propofol-induced sedation using advanced EEG microstate spectral analysis

  • Yamin Li
  • , Wen Shi
  • , Zhian Liu
  • , Jing Li
  • , Qiang Wang
  • , Xiangguo Yan
  • , Zehong Cao
  • , Gang Wang
  • Xi'an Jiaotong University
  • National Engineering Research Center for Healthcare Devices
  • Key Laboratory of Neuro-Informatics and Rehabilitation Engineering of Ministry of Civil Affairs
  • Shanghai Jiao Tong University
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • University of Tasmania

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Brain states are patterns of neuronal synchrony, and the electroencephalogram (EEG) microstate provides a promising tool to characterize and analyze the synchronous neural firing. However, the topographical spectral information for each predominate microstate is still unclear during the switch of consciousness, such as sedation, and the practical usage of the EEG microstate is worth probing. Also, the mechanism behind the anesthetic-induced alternations of brain states remains poorly understood. In this study, an advanced EEG microstate spectral analysis was utilized using multivariate empirical mode decomposition in Hilbert-Huang transform. The practicability was further investigated in scalp EEG recordings during the propofol-induced transition of consciousness. The process of transition from the awake baseline to moderate sedation was accompanied by apparent increases in microstate (A, B, and F) energy, especially in the whole-brain delta band, frontal alpha band and beta band. In comparison to other effective EEG-based parameters that commonly used to measure anesthetic depth, using the selected spectral features reached better performance (80% sensitivity, 90% accuracy) to estimate the brain states during sedation. The changes in microstate energy also exhibited high correlations with individual behavioral data during sedation. In a nutshell, the EEG microstate spectral analysis is an effective method to estimate brain states during propofol-induced sedation, giving great insights into the underlying mechanism. The generated spectral features can be promising markers to dynamically assess the consciousness level.

Original languageEnglish
Article number9136842
Pages (from-to)978-987
Number of pages10
JournalIEEE Journal of Biomedical and Health Informatics
Volume25
Issue number4
DOIs
StatePublished - Apr 2021

Keywords

  • Electroencephalogram
  • microstate spectral analysis
  • multivariate empirical mode decomposition
  • sedation
  • transition of consciousness

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