Abstract
This paper describes an environment based on rich interactive diagrams, allowing the geriatricians and caregivers to access, analyze and precisely annotate or label specific granular cases of interest in a variety of heterogeneous data collected, to identify “behaviour changes” through Smart City IoT and Open Data infrastructures. The overall goal is to detect and contextualize, as early and precisely as possible, negative changes that may lead to onset of MCI/frailty in the elderly population. The environment is being developed and piloted within the City4Age project, partially funded by the EU.
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Urošević, V., Paolini, P., Tatsiopoulos, C. (2018). Integration of Complex IoT Data with Case-Specific Interactive Expert Knowledge Feedback, for Elderly Frailty Prevention. 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_25
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DOI: https://doi.org/10.1007/978-3-319-94523-1_25
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