On the Use of Cognitive Neurometric Indexes in Aeronautic and Air Traffic Management Environments

Gianluca di Flumeri, Gianluca Borghini, Pietro Arico, Alfredo Colosimo, Simone Pozzi, Stefano Bonelli, Alessia Golfetti, Wanzeng Kong, Fabio Babiloni

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

Abstract

In this paper the use of neurophysiological indexes for an objective evaluation of mental workload, during an ecological Air Traffic Management (ATM) task, has been proposed. Six professional Air Traffic Controllers from the Italian ENAV (Societa Na-zionale per l'Assistenza al Volo) have been involved in this study. They had to perform an ecological Air Traffic Management task by using the eDEP software, a validated simulation platform developed by EUROCONTROL. In order to simulate a realistic situation, the task was developed with a continuously varying difficulty level, i.e. starting form an easy level, then increasing up to a harder one and finishing with an easy one again. During the whole task for each subject the electroencephalographic (EEG) signals were recorded in order to compute the neurophysiological workload index, and at the same time the subjective perception of the mental workload by using the Instantaneous Self-Assessment (ISA) technique. Thus, the EEG-based workload index, estimated by means of machine learning approach, by one side, and the subjective assessed workload index by the other side, have been compared in terms of correlation and difficulty levels discrimination. By the results it emerged: i) a high positive and significant correlation between the two measures, and ii) a significantly discriminability of the task different difficulty levels by using the EEG-based workload indexes, according to the ISA results. In conclusion, this study validated the EEG-based mental workload index as an efficient objective evaluation method of the cognitive resources demand in a real operative scenario, and moreover as an index able to monitor its variations.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages45-56
Number of pages12
Volume9359
ISBN (Print)9783319249162
DOIs
Publication statusPublished - 2015
Event4th International Workshop on Symbiotic Interaction, Symbiotic 2015 - Berlin, Germany
Duration: Oct 7 2015Oct 8 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9359
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Workshop on Symbiotic Interaction, Symbiotic 2015
CountryGermany
CityBerlin
Period10/7/1510/8/15

Keywords

  • ATCO
  • ATM
  • EDEP
  • EEG
  • EOG
  • Machine learning
  • Mental workload
  • Self-assessment

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    di Flumeri, G., Borghini, G., Arico, P., Colosimo, A., Pozzi, S., Bonelli, S., Golfetti, A., Kong, W., & Babiloni, F. (2015). On the Use of Cognitive Neurometric Indexes in Aeronautic and Air Traffic Management Environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9359, pp. 45-56). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9359). Springer Verlag. https://doi.org/10.1007/978-3-319-24917-9_5