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Examinando por Autor "Rametta, Piercosimo"

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    A critical analysis of an IoT—aware AAL system for elderly monitoring
    (Elsevier B.V., 2019-08) Almeida, Aitor; Mulero, Rubén; Rametta, Piercosimo; Urošević, Vladimir; Andrić, Marina; Patrono, Luigi
    A growing number of elderly people (65+ years old) are affected by particular conditions, such as Mild Cognitive Impairment (MCI) and frailty, which are characterized by a gradual cognitive and physical decline. Early symptoms may spread across years and often they are noticed only at late stages, when the outcomes remain irrevocable and require costly intervention plans. Therefore, the clinical utility of early detecting these conditions is of substantial importance in order to avoid hospitalization and lessen the socio-economic costs of caring, while it may also significantly improve elderly people's quality of life. This work deals with a critical performance analysis of an Internet of Things aware Ambient Assisted Living (AAL) system for elderly monitoring. The analysis is focused on three main system components: (i) the City-wide data capturing layer, (ii) the Cloud-based centralized data management repository, and (iii) the risk analysis and prediction module. Each module can provide different operating modes, therefore the critical analysis aims at defining which are the best solutions according to context's needs. The proposed system architecture is used by the H2020 City4Age project to support geriatricians for the early detection of MCI and frailty conditions
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    An IoT-aware architecture for collecting and managing data related to elderly behavior
    (Hindawi Limited, 2017-12-28) Almeida, Aitor ; Fiore, Alessandro; Mainetti, Luca; Mulero, Rubén ; Patrono, Luigi; Rametta, Piercosimo
    The world population will be made up of a growing number of elderly people in the near future. Aged people are characterized by some physical and cognitive diseases, like mild cognitive impairment (MCI) and frailty, that, if not timely diagnosed, could turn into more severe diseases, like Alzheimer disease, thus implying high costs for treatments and cares. Information and Communication Technologies (ICTs) enabling the Internet of Tings (IoT) can be adopted to create frameworks for monitoring elderly behavior which, alongside normal clinical procedures, can help geriatricians to early detect behavioral changes related to such pathologies and to provide customized interventions. As part of the City4Age project, this work describes a novel approach for collecting and managing data about elderly behavior during their normal activities. The data capturing layer is an unobtrusive and low-cost sensing infrastructure abstracting the heterogeneity of physical devices, while the data management layer easily manages the huge quantity of sensed data, giving them semantic meaning and fostering data shareability. This work provides a functional validation of the proposed architecture and introduces how the data it manages can be used by the whole City4Age platform to early identify risks related to MCI/frailty and promptly intervene.
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