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A Neuroergonomics Approach to Measure Pilot’s Cognitive Incapacitation in the Real World with EEG

  • Frédéric DehaisEmail author
  • Bertille Somon
  • Tim Mullen
  • Daniel E. Callan
Conference paper
  • 333 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1201)

Abstract

手机体育投注平台Mental overload and mental fatigue are two degraded cognitive states that are known to promote cognitive incapacitation. We adopted a neuroergonomics approach to investigate these states that remain difficult to induce under laboratory settings thus impeding their measurement. Two experiments were conducted under real flight conditions to respectively measure the electrophysiological correlates of mental fatigue and mental overload with a 32 channel-dry EEG system. Our findings revealed that the occurrence of mental fatigue was related to higher theta and alpha band power. Mental overload was associated with higher beta band power over frontal sites. We performed single trial classification to detect mental fatigue and over-load states. Classification accuracy reached 76.9% and 89.1%, respectively, in discriminating mental fatigue vs. no fatigue and mental overload vs. low-high load. These preliminary results provide evidence for the feasibility of detecting neural correlates of cognitive fatigue and load during real flight conditions and provide promising perspectives on the implementation of neuroadaptive technology especially in the context of single pilot-operation.

Keywords

Mental overload Mental fatigue EEG Neuroergonomics 

Notes

Acknowledgments

This study was supported by AID (Agence Innovation de la Défense) and ANITI ANR-19-PI3A-0004 and the AXA research fund (Neuroergonomics chair).

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Frédéric Dehais
    • 1
    • 2
    Email author
  • Bertille Somon
    • 1
  • Tim Mullen
    • 3
  • Daniel E. Callan
    • 1
    • 4
  1. 1.ISAE-SUPAERO, University of ToulouseToulouseFrance
  2. 2.Drexel UniversityPhiladelphiaUSA
  3. 3.ISA Intheon LabsSand DiegoUSA
  4. 4.Center for Information and Neural Networks CiNet, National Institute of Information and Communications Technology NICTOsaka UniversitySuitaJapan

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