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.
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Acknowledgment
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 761708.
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Groppo, S., Armengaud, E., Pugliese, L., Violante, M., Garramone, L. (2021). Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS. In: Zachäus, C., Meyer, G. (eds) Intelligent System Solutions for Auto Mobility and Beyond. AMAA 2020. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-030-65871-7_13
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DOI: https://doi.org/10.1007/978-3-030-65871-7_13
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