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EnglishThe 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. - (2021), pp. 177-185.
| Titolo: | Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS | |
| Autori: | ||
| Data di pubblicazione: | 2021 | |
| Titolo del libro: | Intelligent System Solutions for Auto Mobility and Beyond | |
| Serie: | ||
| Abstract: | The PRESLEEP project is aimed at the fine assessment and validation of the proposed proprietary m...ethodology/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. | |
| ISBN: | 978-3-030-65870-0 978-3-030-65871-7 | |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Springer_book.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia | |
| AMAA 2020_PRESLEEP_Review_v1.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2860071
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