EEG-based Classification of Microsleep by Means of Feature Selection: An Application in Aviation

Bijay Guragain, Ali Bahrami Rad, Chunwu Wang, Ajay K. Verma, Lewis Archer, Nicholas Wilson, Kouhyar Tavakolian

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

Abstract

This paper presents a method for classification of microsleep (MS) from baseline utilizing linear and non-linear features derived from electroencephalography (EEG), which is recorded from five brain regions: frontal, central, parietal, occipital, and temporal. The EEG is acquired from sixteen commercially-rated pilots during the window of circadian low (2:00 am-6:00 am). MS events are annotated using the Driver Monitoring System and further verified using electrooculogram (EOG). A total of 55 features are extracted from EEG. A subset of these features is then selected using a wrapper-based method. The selected features are fed into a linear or quadratic discriminant analysis (LDA or QDA) classifier to automatically differentiate baseline from MS states. The overall classification performance of the best-proposed algorithm is 87.11% in terms of F1 score. This preliminary result highlights the potential of the proposed method towards automatic drowsiness detection which could assist mitigating aviation accidents in the future, pending hardware development to record such EEG signals from the confines of the aviation headset.

Original languageEnglish
Title of host publicationProceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherIEEE
Pages4060-4063
Number of pages4
ISBN (Electronic)9781538613115
DOIs
Publication statusPublished - 1 Jul 2019
MoE publication typeA4 Article in a conference publication
EventAnnual International Conference of the IEEE Engineering in Medicine and Biology Society - Berlin, Germany
Duration: 23 Jul 201927 Jul 2019
Conference number: 41

Conference

ConferenceAnnual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBC
CountryGermany
CityBerlin
Period23/07/201927/07/2019

Keywords

  • Drowsiness
  • EEG
  • LDA
  • Microsleep
  • QDA

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