Publicação em atas de evento científico
Ambient assisted living using non-intrusive smart sensing and IoT for gait rehabilitation
Joel Santos (Santos, J.); Octavian Postolache (Postolache, O.); Diana Mendes (Mendes, D.);
2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
Ano (publicação definitiva)
2022
Língua
Inglês
País
Estados Unidos da América
Mais Informação
Web of Science®

N.º de citações: 2

(Última verificação: 2024-11-16 19:18)

Ver o registo na Web of Science®

Scopus

N.º de citações: 4

(Última verificação: 2024-11-14 13:52)

Ver o registo na Scopus

Google Scholar

N.º de citações: 4

(Última verificação: 2024-11-17 13:26)

Ver o registo no Google Scholar

Abstract/Resumo
Health monitoring of users in medical centers, nursing homes, physiotherapy clinics or other healthcare centers, is an important and recurring task. In addition, these facilities require a structured, organized system with access to all users’ medical history. The design of a system that can measure individuals’ physiological health characteristics (PHC) may also be applied to physical rehabilitation. In this context, this study presents a possible solution using a non-intrusive smart sensing system as part of an IoT ecosystem, that aims to solve all the issues stated. This IoT system uses a smart carpet, SensFloor, to measure several physical indicators, such as users’ position and gait characteristics. The produced data by the system is stored in a real-time cloud database, thus physical therapists and patients are able to access it. Also, several dashboards are produced in real-time, to provide further analysis on users’ gait and PHCs, so that action can be taken to improve the training plan with personalized exercises.
Agradecimentos/Acknowledgements
--
Palavras-chave