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Santos, J., Postolache, O. & Mendes, D. (2022). Ambient assisted living using non-intrusive smart sensing and IoT for gait rehabilitation. In 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE). (pp. 489-494). Rome: IEEE.

J. V. Santos et al.,  "Ambient assisted living using non-intrusive smart sensing and IoT for gait rehabilitation", in 2022 IEEE Int. Conf. on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Rome, IEEE, 2022, pp. 489-494

@inproceedings{santos2022_1734531329032,
	author = "Santos, J. and Postolache, O. and Mendes, D.",
	title = "Ambient assisted living using non-intrusive smart sensing and IoT for gait rehabilitation",
	booktitle = "2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)",
	year = "2022",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/MetroXRAINE54828.2022.9967674",
	pages = "489-494",
	publisher = "IEEE",
	address = "Rome",
	organization = "IEEE",
	url = "https://ieeexplore.ieee.org/xpl/conhome/9967443/proceeding"
}

TY  - CPAPER
TI  - Ambient assisted living using non-intrusive smart sensing and IoT for gait rehabilitation
T2  - 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
AU  - Santos, J.
AU  - Postolache, O.
AU  - Mendes, D.
PY  - 2022
SP  - 489-494
DO  - 10.1109/MetroXRAINE54828.2022.9967674
CY  - Rome
UR  - https://ieeexplore.ieee.org/xpl/conhome/9967443/proceeding
AB  - 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.
ER  -