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 scienti...Show MoreMetadata
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.
Published in: 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI)
Date of Conference: 11-13 September 2017
Date Added to IEEE Xplore: 12 October 2017
ISBN Information: