Detection of Drowsy Driving Using Wearable Sensors

Duarte Pereira, Brigida Faria, Brigida Faria, Luis Paulo Reis, Luis Paulo Reis

2023

Abstract

Drowsy driving is one of the leading causes of traffic accidents. Some solution provides feedback when the driver is drowsy, however, few tackle the issue in a way that allows for portability and early prevision. This study focuses on drowsiness detection during driving. Wearable sensors are used, for a low-cost, portable, automated, and non-intrusive solution. The wearable sensors chosen for biosignal acquisition are Empatica’s E4 wristband for heart activity acquisition and Brainlink Pro for brain activity. Features were mainly in the time domain and time-frequency, and algorithms, such as Nearest Neighbours, Radial Basis Function, Support Vector Machine, Decision Tree, Random Forest, Multi-layer Perceptron, Naive Bayes, and Logistic Regression were trained and validated through the use of a database developed for this study (11 adults with normal last-night sleep, and 2 without any last-night sleep). Participants answered Pittsburgh, and Satisfaction, Alertness, Timing, Efficiency and Duration questionnaires, after which photoplethysmography and electroencephalography physiological signals were acquired during driving in a simulation environment. The practice-run discrimination and individual classification had comparable results, both slightly above average (70 to 80%). The evaluation metric values showed that the discrimination of sleep-deprived exams yielded significantly better. This suggests that the proposed methodology is capable of classifying sleep deprivation and surpasses existing ones in its portability.

Paper Citation

in Harvard Style

Pereira D., Faria B. and Paulo Reis L. (2023). Detection of Drowsy Driving Using Wearable Sensors. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 414-421. DOI: 10.5220/0012089900003541

in Bibtex Style

@conference{data23,
author={Duarte Pereira and Brigida Faria and Luis Paulo Reis},
title={Detection of Drowsy Driving Using Wearable Sensors},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={414-421},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012089900003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Detection of Drowsy Driving Using Wearable Sensors
SN - 978-989-758-664-4
AU - Pereira D.
AU - Faria B.
AU - Paulo Reis L.
PY - 2023
SP - 414
EP - 421
DO - 10.5220/0012089900003541
PB - SciTePress