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Use of Dry Electrode Electroencephalography (EEG) to Monitor Pilot Workload and Distraction Based on P300 Responses to an Auditory Oddball Task

  • Zara GibsonEmail author
  • Joseph Butterfield
  • Matthew Rodger
  • Brian Murphy
  • Adelaide Marzano
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 775)

Abstract

This study aims to examine whether dry electrode EEG can detect and show changes in the P300, in a movement and noise polluted flight simulator environment with a view to using it for workload and distraction monitoring. Twenty participants completed take-off, cruise and landing flight phases in a flight simulator alongside an auditory oddball task. Dry EEG sensors monitored the participants’ brain activity throughout the task and P300 responses were extracted from the resulting data. Results show that dry EEG can extract P300 responses as participants register oddball tone stimuli. The method can indicate workload for each condition based on the outputs from the EEG electrodes; landing (M = 287.5) and take-off (M = 484.6) procedures were more difficult than cruising (M = 636.6). With the differences between cruising and landing being statistically significant (p = .001). Outcomes correlate with participant NASA-TLX scores of workload that report landing to be the most difficult.

Keywords

P300 Flight simulation Workload Dry EEG Human factors 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Zara Gibson
    • 1
    Email author
  • Joseph Butterfield
    • 1
  • Matthew Rodger
    • 1
  • Brian Murphy
    • 1
  • Adelaide Marzano
    • 2
  1. 1.Queen’s University BelfastBelfastNorthern Ireland
  2. 2.University of the West of ScotlandPaisleyScotland

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