Increase in regularity and decrease in variability seen in electroencephalography (EEG) signals from alert to fatigue during a driving simulated task

Y. Tran*, N. Wijesuryia, R. A. Thuraisingham, A. Craig, H. T. Nguyen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

10 Citations (Scopus)

Abstract

Driver fatigue is a prevalent problem and a major risk for road safety accounting for approximately 20-40% of all motor vehicle accidents. One strategy to prevent fatigue related accidents is through the use of countermeasure devices. Research on countermeasure devices has focused on methods that detect physiological changes from fatigue, with the fast temporal resolution from brain signals, using the electroencephalogram (EEG) held as a promising technique. This paper presents the results of nonlinear analysis using sample entropy and second-order difference plots quantified by central tendency measure (CTM) on alert and fatigue EEG signals from a driving simulated task. Results show that both sample entropy and second-order difference plots significantly increases the regularity and decreases the variability of EEG signals from an alert to a fatigue state.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1096-1099
Number of pages4
ISBN (Print)9781424418152, 9781424418145
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period20/08/0825/08/08

Keywords

  • Central tendency measure (CTM)
  • Countermeasure
  • Driver fatigue
  • Electroencephalography (EEG)
  • Fatigue
  • Nonlinear analysis
  • Sample entropy
  • Second-order difference plot

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