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Pre-stimulus antero-posterior EEG connectivity predicts performance in a UAV monitoring task

Senoussi, Mehdi and Verdière, Kevin J. and Bovo, Angela and Ponzoni Carvalho Chanel, Caroline and Dehais, Frédéric and Roy, Raphaëlle N. Pre-stimulus antero-posterior EEG connectivity predicts performance in a UAV monitoring task. (2017) In: IEEE International Conference on Systems, Man, and Cybernetics (SMC 2017), 5 October 2017 - 8 October 2017 (Banff, Canada).

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Official URL: http://dx.doi.org/10.1109/SMC.2017.8122770

Abstract

Long monitoring tasks without regular actions, are becoming increasingly common from aircraft pilots to train conductors as these systems grow more automated. These task contexts are challenging for the human operator because they require inputs at irregular and highly interspaced moments even though these actions are often critical. It has been shown that such conditions lead to divided and distracted attentional states which in turn reduce the processing of external stimuli (e.g. alarms) and may lead to miss critical events. In this study we explored to which extent it is possible to predict an operator’s behavioural performance in a Unmanned Aerial Vehicle (UAV) monitoring task using electroencephalographic (EEG) activity. More specifically we investigated the relevance of large-scale EEG connectivity for performance prediction by correlating relative coherence with reaction times (RT). We show that long-range EEG relative coherence, i.e. between occipital and frontal electrodes, is significantly correlated with RT and that different frequency bands exhibit opposite effects. More specifically we observed that coherence between occipital and frontal electrodes was: negatively correlated with RT at 6Hz (theta band), more coherence leading to better performance, and positively correlated with RT at 8Hz (lower alpha band), more coherence leading to worse performance. Our results suggest that EEG connectivity measures could be useful in predicting an operator’s attentional state and her/his performances in ecological settings. Hence these features could potentially be used in a neuro-adaptive interface to improve operator-system interaction and safety in critical systems.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to the IEEE (Institute of Electrical and Electronics Engineers). This paper is available at : http://ieeexplore.ieee.org/document/8122770 “© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Audience (conference):International conference proceedings
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Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
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Deposited By: Caroline Ponzoni Carvalho Chanel
Deposited On:08 Jan 2018 15:56

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