Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving

Baptiste Chevallier, Baptiste Chevallier, Dan Istrate, Vincent Zalc, Nicolas Vera, Christophe Labrousse, Christophe Labrousse

2023

Abstract

Drowsy driving is a major issue in road safety. In this paper, we propose a description of an experimental data collection to develop a drowsiness detection model. The objective of this data collection was mainly to gather physiological data of individuals in simulated driving situations. We designed a realistically annoying scenario to induce fatigue while staying close to real driving conditions. The experiment was run on an augmented reality platform called CAVE. The need for contextualization came early in the design of the experiment. Therefore, in addition to physiological data, we added much more data sources, from driving habits to driving behaviour in addition to self-assessment of fatigue levels and the gold standard (EEG). As a result, this experience helped us create a data set of physiological data completed by elements of context and driving behaviour. Thus allowing us to perform a very rich analysis of these physiological data.

Paper Citation

in Harvard Style

Chevallier B., Istrate D., Zalc V., Vera N. and Labrousse C. (2023). Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF; ISBN 978-989-758-631-6, SciTePress, pages 408-415. DOI: 10.5220/0011698100003414

in Bibtex Style

@conference{healthinf23,
author={Baptiste Chevallier and Dan Istrate and Vincent Zalc and Nicolas Vera and Christophe Labrousse},
title={Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF},
year={2023},
pages={408-415},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011698100003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF
TI - Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving
SN - 978-989-758-631-6
AU - Chevallier B.
AU - Istrate D.
AU - Zalc V.
AU - Vera N.
AU - Labrousse C.
PY - 2023
SP - 408
EP - 415
DO - 10.5220/0011698100003414
PB - SciTePress