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

Author:

Di Flumeri Gianluca12ORCID,Giorgi Andrea23ORCID,Germano Daniele14,Ronca Vincenzo24ORCID,Vozzi Alessia23ORCID,Borghini Gianluca12ORCID,Tamborra Luca23ORCID,Simonetti Ilaria23,Capotorto Rossella1ORCID,Ferrara Silvia2,Sciaraffa Nicolina2,Babiloni Fabio125ORCID,Aricò Pietro24ORCID

Affiliation:

1. Laboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy

2. BrainSigns srl, 00198 Rome, Italy

3. Department of Anatomical, Histological, Forensic and Orthopaedic Sciences, Sapienza University of Rome, 00185 Rome, Italy

4. Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University of Rome, 00185 Rome, Italy

5. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China

Abstract

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.

Funder

European Commission

Sapienza University of Rome

INAIL institute

Italian Ministry of Health

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference75 articles.

1. Semin, G.R., and Fiedler, K. (1996). Applied Social Psychology, Sage.

2. De Waard, D. (1996). The Measurement of Drivers’ Mental Workload, University of Groningen, Traffic Research Centre.

3. Evans, L. (1991). Traffic Safety and the Driver, Science Serving Society.

4. Simonetti, I., Tamborra, L., Giorgi, A., Ronca, V., Vozzi, A., Aricò, P., Borghini, G., Sciaraffa, N., Trettel, A., and Babiloni, F. (2023). Neurophysiological Evaluation of Students’ Experience during Remote and Face-to-Face Lessons: A Case Study at Driving School. Brain Sci., 13.

5. Istituto Nazionale di Statistica (2020). Incidenti Stradali, Istituto Nazionale di Statistica (ISTAT).

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