How Neurophysiological Measures Can be Used to Enhance the Evaluation of Remote Tower Solutions.

ECG EEG GSR asSWLDA eye blink machine learning mental workload remote tower air traffic management

Journal

Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954

Informations de publication

Date de publication:
2019
Historique:
received: 30 04 2019
accepted: 14 08 2019
entrez: 26 9 2019
pubmed: 26 9 2019
medline: 26 9 2019
Statut: epublish

Résumé

New solutions in operational environments are often, among objective measurements, evaluated by using subjective assessment and judgment from experts. Anyhow, it has been demonstrated that subjective measures suffer from poor resolution due to a high intra and inter-operator variability. Also, performance measures, if available, could provide just partial information, since an operator could achieve the same performance but experiencing a different workload. In this study, we aimed to demonstrate: (i) the higher resolution of neurophysiological measures in comparison to subjective ones; and (ii) how the simultaneous employment of neurophysiological measures and behavioral ones could allow a holistic assessment of operational tools. In this regard, we tested the effectiveness of an electroencephalography (EEG)-based neurophysiological index (W

Identifiants

pubmed: 31551735
doi: 10.3389/fnhum.2019.00303
pmc: PMC6743038
doi:

Types de publication

Journal Article

Langues

eng

Pagination

303

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Auteurs

Pietro Aricò (P)

Department of Molecular Medicine, "Sapienza" University of Rome, Rome, Italy.
BrainSigns srl, Rome, Italy.
IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.

Maxime Reynal (M)

French Civil Aviation University (ENAC), University of Toulouse, Toulouse, France.

Gianluca Di Flumeri (G)

Department of Molecular Medicine, "Sapienza" University of Rome, Rome, Italy.
BrainSigns srl, Rome, Italy.
IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.

Gianluca Borghini (G)

Department of Molecular Medicine, "Sapienza" University of Rome, Rome, Italy.
BrainSigns srl, Rome, Italy.
IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.

Nicolina Sciaraffa (N)

BrainSigns srl, Rome, Italy.
IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.
Department of Anatomical, Histological, Forensic & Orthopedic Sciences, "Sapienza" University of Rome, Rome, Italy.

Jean-Paul Imbert (JP)

French Civil Aviation University (ENAC), University of Toulouse, Toulouse, France.

Christophe Hurter (C)

French Civil Aviation University (ENAC), University of Toulouse, Toulouse, France.

Michela Terenzi (M)

DeepBlue srl, Rome, Italy.

Ana Ferreira (A)

DeepBlue srl, Rome, Italy.

Simone Pozzi (S)

DeepBlue srl, Rome, Italy.

Viviana Betti (V)

IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.
Department of Psychology, "Sapienza" University of Rome, Rome, Italy.

Matteo Marucci (M)

Department of Psychology, "Sapienza" University of Rome, Rome, Italy.
Braintrends Limited, Applied Neuroscience, Rome, Italy.

Alexandru C Telea (AC)

Department of Mathematics and Computing Science, University of Groningen, Groningen, Netherlands.

Fabio Babiloni (F)

Department of Molecular Medicine, "Sapienza" University of Rome, Rome, Italy.
BrainSigns srl, Rome, Italy.
IRCCS Fondazione Santa Lucia, Neuroelectrical Imaging and BCI Lab, Rome, Italy.
College Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China.

Classifications MeSH