Linear and nonlinear EEG indexes in relation to the severity of coma

  • M. A. Lin*
  • , H. L. Chan
  • , S. C. Fang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Glascow's coma scale (GCS) is a clinical standard for assessing the severity of coma in intensive care units (ICUs). The EEG monitoring can be on-line work, soon responds to the change in the brain wave, and allows long-term continuous monitoring of brain activity. In this paper, several EEG parameters, including spectral possession distribution and nonlinear description (approximate entropy and Lempel-Ziv complexity) were used to assess the capability of EEG indexes for the severity of coma. Our results demonstrated that all EEG parameters are moderately related to the GCS, with the Spearman statistical correlation of 0.62-0.71 between the spectral possession distribution and the GCS and 0.62-0.66 between nonlinear measures and the GCS. The moderate correlation between EEG parameters and the GCS implies the possibility of the EEG-derived index to reveal the neurological status of patients in coma.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4580-4583
Number of pages4
ISBN (Print)0780387406, 9780780387409
DOIs
StatePublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 01 09 200504 09 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Conference

Conference2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period01/09/0504/09/05

Keywords

  • Electroencephalogram (EEG)
  • Glasgow coma scale
  • Nonlinear analysis

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