Data driven MCI and frailty prevention: Geriatric modelling in the City4Age project
Authors:
- 1 September 2017
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
Abstract
This paper presents a step toward the development of a data-centric approach to prevention of Mild Cognitive Impairment and frailty in the elderly population. The scientific literature provides a large number of “indicators” for assessing the quality of behavior for aged individuals, in order to predict possible decaying. On the opposite side, a large variety of sensors and datasets today allows the effective collection of elementary data about actions performed by individuals. This paper proposes to build a bridge between these two sides. In a bottom-up vision, data from sensors and smart cities' datasets are aggregated and interpreted in a way that leads to reliable assessment of the indicators. In a top-down vision, indicators are translated into data analysis. The work described in this paper is part of City4age, a project partially funded by the EU within the H2020 Programme.Keywords
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