Abstract
Aging process is related to serious decline in physical and cognitive functions. Thus, early detection of these health changes is important to improve classical assessments that are mainly based on interviews, and are insufficient to early diagnose all possible health changes. Therefore, we propose a technological approach that analyzes elderly people behavior on a daily basis, employs unobtrusive monitoring technologies, and applies statistical techniques to identify continuous changes in monitored behavior. We detect significant long-term changes that are highly related to physical and cognitive problems. We also present a real validation through data collected from 3-year deployments in nursing-home rooms.
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Acknowledgement
We give our special thanks to Saint Vincent de Paul nursing home in Occagnes, France. Our deployment in this nursing home is also supported by VHP inter@ctive project and the Quality Of Life chair.
Our work is part of the European project City4Age that received funding from the Horizon 2020 research and innovation program under grant agreement number 689731.
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Kaddachi, F., Aloulou, H., Abdulrazak, B., Fraisse, P., Mokhtari, M. (2018). Technological Approach for Early and Unobtrusive Detection of Possible Health Changes Toward More Effective Treatment. In: Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Smart Homes and Health Telematics, Designing a Better Future: Urban Assisted Living. ICOST 2018. Lecture Notes in Computer Science(), vol 10898. Springer, Cham. https://doi.org/10.1007/978-3-319-94523-1_5
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