A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees

When assessing trainees’ progresses during a driving training program, instructors can only rely on the evaluation of a trainee’s explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing h...

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Main Authors: Gianluca Di Flumeri, Andrea Giorgi, Daniele Germano, Vincenzo Ronca, Alessia Vozzi, Gianluca Borghini, Luca Tamborra, Ilaria Simonetti, Rossella Capotorto, Silvia Ferrara, Nicolina Sciaraffa, Fabio Babiloni, Pietro Aricò
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/20/8389
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author Gianluca Di Flumeri
Andrea Giorgi
Daniele Germano
Vincenzo Ronca
Alessia Vozzi
Gianluca Borghini
Luca Tamborra
Ilaria Simonetti
Rossella Capotorto
Silvia Ferrara
Nicolina Sciaraffa
Fabio Babiloni
Pietro Aricò
author_facet Gianluca Di Flumeri
Andrea Giorgi
Daniele Germano
Vincenzo Ronca
Alessia Vozzi
Gianluca Borghini
Luca Tamborra
Ilaria Simonetti
Rossella Capotorto
Silvia Ferrara
Nicolina Sciaraffa
Fabio Babiloni
Pietro Aricò
author_sort Gianluca Di Flumeri
collection DOAJ
description When assessing trainees’ progresses during a driving training program, instructors can only rely on the evaluation of a trainee’s explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing how to drive safely in a complex scenario such as the road traffic. Indeed, the latter point involves mental aspects, such as the ability to manage and allocate one’s mental effort appropriately, which are difficult to assess objectively. In this scenario, this study investigates the validity of deploying an electroencephalographic neurometric of mental effort, obtained through a wearable electroencephalographic device, to improve the assessment of the trainee. The study engaged 22 young people, without or with limited driving experience. They were asked to drive along five different but similar urban routes, while their brain activity was recorded through electroencephalography. Moreover, driving performance, subjective and reaction times measures were collected for a multimodal analysis. In terms of subjective and performance measures, no driving improvement could be detected either through the driver’s subjective measures or through their driving performance. On the other side, through the electroencephalographic neurometric of mental effort, it was possible to catch their improvement in terms of mental performance, with a decrease in experienced mental demand after three repetitions of the driving training tasks. These results were confirmed by the analysis of reaction times, that significantly improved from the third repetition as well. Therefore, being able to measure when a task is less mentally demanding, and so more automatic, allows to deduce the degree of users training, becoming capable of handling additional tasks and reacting to unexpected events.
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spelling doaj.art-eed3dca2fc4342c1a8d3374ed52c76802023-11-19T18:02:09ZengMDPI AGSensors1424-82202023-10-012320838910.3390/s23208389A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers TraineesGianluca Di Flumeri0Andrea Giorgi1Daniele Germano2Vincenzo Ronca3Alessia Vozzi4Gianluca Borghini5Luca Tamborra6Ilaria Simonetti7Rossella Capotorto8Silvia Ferrara9Nicolina Sciaraffa10Fabio Babiloni11Pietro Aricò12Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, ItalyBrainSigns srl, 00198 Rome, ItalyWhen assessing trainees’ progresses during a driving training program, instructors can only rely on the evaluation of a trainee’s explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing how to drive safely in a complex scenario such as the road traffic. Indeed, the latter point involves mental aspects, such as the ability to manage and allocate one’s mental effort appropriately, which are difficult to assess objectively. In this scenario, this study investigates the validity of deploying an electroencephalographic neurometric of mental effort, obtained through a wearable electroencephalographic device, to improve the assessment of the trainee. The study engaged 22 young people, without or with limited driving experience. They were asked to drive along five different but similar urban routes, while their brain activity was recorded through electroencephalography. Moreover, driving performance, subjective and reaction times measures were collected for a multimodal analysis. In terms of subjective and performance measures, no driving improvement could be detected either through the driver’s subjective measures or through their driving performance. On the other side, through the electroencephalographic neurometric of mental effort, it was possible to catch their improvement in terms of mental performance, with a decrease in experienced mental demand after three repetitions of the driving training tasks. These results were confirmed by the analysis of reaction times, that significantly improved from the third repetition as well. Therefore, being able to measure when a task is less mentally demanding, and so more automatic, allows to deduce the degree of users training, becoming capable of handling additional tasks and reacting to unexpected events.https://www.mdpi.com/1424-8220/23/20/8389neuroergonomicswearable EEGPassive Brain–Computer Interface (BCI)mental effortdriving educationlearning
spellingShingle Gianluca Di Flumeri
Andrea Giorgi
Daniele Germano
Vincenzo Ronca
Alessia Vozzi
Gianluca Borghini
Luca Tamborra
Ilaria Simonetti
Rossella Capotorto
Silvia Ferrara
Nicolina Sciaraffa
Fabio Babiloni
Pietro Aricò
A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
Sensors
neuroergonomics
wearable EEG
Passive Brain–Computer Interface (BCI)
mental effort
driving education
learning
title A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
title_full A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
title_fullStr A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
title_full_unstemmed A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
title_short A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees
title_sort neuroergonomic approach fostered by wearable eeg for the multimodal assessment of drivers trainees
topic neuroergonomics
wearable EEG
Passive Brain–Computer Interface (BCI)
mental effort
driving education
learning
url https://www.mdpi.com/1424-8220/23/20/8389
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