The PRESLEEP project is aimed at the fine assessment and validation of the proposed proprietary methodology/technology, for the automatic detection and prediction of the transition between the behavioural states of a subject (e.g. wakefulness, drowsiness and sleeping) through a wearable Cyber Physical System (CPS). The Intellectual Property (IP) is based on a combined multi-factor and multi-domain analysis thus being able to extract a robust set of parameters despite of the, generally, low quality of the physiological signals measured through a wearable system applied to the wrist of the subject. An application experiment has been carried out at AVL, based on reduced wakefulness maintenance test procedure, to validate the algorithm’s detection and prediction capability once the subject is driving in the dynamic vehicle simulator.

Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS / Groppo, Sara; Armengaud, Eric; Pugliese, Luigi; Violante, Massimo; Garramone, Luciano (LECTURE NOTES IN MOBILITY). - In: Intelligent System Solutions for Auto Mobility and Beyond[s.l] : Springer, Cham, 2021. - ISBN 978-3-030-65870-0. - pp. 177-185 [10.1007/978-3-030-65871-7_13]

Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS

Pugliese, Luigi;Violante, Massimo;
2021

Abstract

The PRESLEEP project is aimed at the fine assessment and validation of the proposed proprietary methodology/technology, for the automatic detection and prediction of the transition between the behavioural states of a subject (e.g. wakefulness, drowsiness and sleeping) through a wearable Cyber Physical System (CPS). The Intellectual Property (IP) is based on a combined multi-factor and multi-domain analysis thus being able to extract a robust set of parameters despite of the, generally, low quality of the physiological signals measured through a wearable system applied to the wrist of the subject. An application experiment has been carried out at AVL, based on reduced wakefulness maintenance test procedure, to validate the algorithm’s detection and prediction capability once the subject is driving in the dynamic vehicle simulator.
2021
978-3-030-65870-0
978-3-030-65871-7
Intelligent System Solutions for Auto Mobility and Beyond
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2860071