Drowsiness is one of the first casualty factors of car accidents. A large number of studies have been conducted to reduce the risk of car accidents and, many of them, are based on the detection of biological signals to determine driver drowsiness. In this way, several prototypes have been proposed but all of them are efficient in specific scenarios only. Photoplethysmography (PPG) is a non-invasive tool that allows monitoring heart activity, it is also used to evaluate driver drowsiness. This paper introduces a prototype based on PPG signals able to improve current systems in terms of evaluation time and results clearness. We performed a measurement campaign to compare experimental data with literature. The goal is to validate the prototype.

Amidei, A., Fallica, P.G., Conoci, S., Pavan, P. (2021). Validating Photoplethysmography (PPG) data for driver drowsiness detection. 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/MetroAutomotive50197.2021.9502865].

Validating Photoplethysmography (PPG) data for driver drowsiness detection

Amidei, A
;
Conoci, S;
2021

Abstract

Drowsiness is one of the first casualty factors of car accidents. A large number of studies have been conducted to reduce the risk of car accidents and, many of them, are based on the detection of biological signals to determine driver drowsiness. In this way, several prototypes have been proposed but all of them are efficient in specific scenarios only. Photoplethysmography (PPG) is a non-invasive tool that allows monitoring heart activity, it is also used to evaluate driver drowsiness. This paper introduces a prototype based on PPG signals able to improve current systems in terms of evaluation time and results clearness. We performed a measurement campaign to compare experimental data with literature. The goal is to validate the prototype.
2021
2021 IEEE International Workshop on Metrology for Automotive, MetroAutomotive 2021 - Proceedings
147
151
Amidei, A., Fallica, P.G., Conoci, S., Pavan, P. (2021). Validating Photoplethysmography (PPG) data for driver drowsiness detection. 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/MetroAutomotive50197.2021.9502865].
Amidei, A; Fallica, PG; Conoci, S; Pavan, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/943516
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