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Microsleep Classifier Using EOG Channel Recording: A Feasibility Study

  • Martin HolubEmail author
  • Martina Šrutová
  • Lenka Lhotská
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9267)

Abstract

The microsleeps (MS) cause many accidents and can have a huge social impact. Automated prediction or early detection of the MS states could help to monitor level of fatigue. An automated MS classifier based on the EOG signal is proposed. There were analysed 28 episodes of MS. We observed slow eye movements without rapid changes during MS episodes. An automated feature extraction and classification using EOG channels showed promising results (sensitivity 93 %, positive predictivity 57 %). To confirm the hypothesis it is crucial to extend the study and to analyse larger amount of MS data.

Keywords

Microsleep Electrooculogram Automatic detection Classifier 

Notes

Acknowledgment

This work has been supported by the project No.SGS13/203/OHK3/3T/13 of the Czech Technical University in Prague.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Martin Holub
    • 1
    Email author
  • Martina Šrutová
    • 1
  • Lenka Lhotská
    • 1
  1. 1.Department of Cybernetics, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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