Skill, Rule and Knowledge - based Behaviour Detection by Means of ATCOs’ Brain Activity

Gianluca Borghini 1 Pietro Aricò 1 Gianluca Di Flumeri 2 Ilenia Graziani 3 Alfredo Colosimo 2 Serenella Salinari 3 Fabio Babiloni 3 Jean-Paul Imbert 4 Géraud Granger 5 Raïlane Benhacene 5 Alessia Golfetti 6 Stefano Bonelli 6 Simone Pozzi 6
1 Sapienza University [Rome]
2 Università degli Studi di Roma "La Sapienza" [Rome]
3 Dept. Human Physiology
4 LII - ENAC - Laboratoire d'Informatique Interactive
5 IHM Aero - ENAC - Programme transverse IHM Aéronautique
ENAC - Ecole Nationale de l'Aviation Civile
6 Deep Blue Research and Consulting
Abstract : The aim of this work was to test a neuro-physiological methodology able to discriminate the Skill (S), Rule (R) and Knowledge (K) based cognitive control levels of Air-Traffic-Controllers’ performing realistic traffic management tasks . The three categories of human behaviours have been associated to specific cognitive functions (e.g. attention, memory, decision making) already investigated with Electroencephalography (EEG) measurements. A link between S-R-K behaviours and expected frequency bands configurations has been hypothesized. Eventually, specific events have been designed to trigger S, R and K like behaviours and then integrated into realistic Air Traffic Management (ATM) simulations. A machine-learning algorithm has been used to differentiate the three different levels of cognitive control by using brain features extracted from the EEG rhythms of different brain areas, that is, the frontal theta and the parietal alpha activities. Twelve professional Air-Traffic-Controllers (ATCOs) from the École Nationale de l’Aviation Civile (ENAC) of Toulouse (France) have been involved in the study. The results showed that the algorithm was able to differentiate with high discrimination accuracy (AUC > 0.7) the three S-R-K cognitive behaviours during simulated air-traffic scenarios in an ecological ATM environment
Keywords : EEG Skill Rule Knowledge ATM ATCO
Type de document :
Communication dans un congrès
5th SESAR Innovation days, Dec 2015, Bologna, Italy
Liste complète des métadonnées

Littérature citée [17 références]  Voir  Masquer  Télécharger
https://hal-enac.archives-ouvertes.fr/hal-01240319
Contributeur : Laurence Porte <>
Soumis le : jeudi 10 décembre 2015 - 15:23:44
Dernière modification le : mardi 30 janvier 2018 - 13:32:06
Document(s) archivé(s) le : samedi 29 avril 2017 - 11:27:32

Fichier

SIDs_2015_paper_8-v2.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01240319, version 2

Collections

ENAC | IHM

Citation

Gianluca Borghini, Pietro Aricò, Gianluca Di Flumeri, Ilenia Graziani, Alfredo Colosimo, et al.. Skill, Rule and Knowledge - based Behaviour Detection by Means of ATCOs’ Brain Activity. 5th SESAR Innovation days, Dec 2015, Bologna, Italy. 〈hal-01240319v2〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

251

Téléchargements de fichiers

347

Picto

Contact  : publications@enac.fr