Abstract

The behavioral analysis of individuals is an important science, especially if it is conducted on the elderly population, aiming to prevent Mild Cognitive Impairment (MCI) and frailty problems. A fundamental aspect in this context is to explore the use of innovative technologies enabling the Internet of Things (IoT), above all sensors, to unobtrusively capture personal data for automatically recognizing behavioral changes in elderly people. This is done with the aim to timely identify risks of MCI and frailty before they escalate into more serious conditions such as Alzheimer Disease. This paper aims to briefly describe the overall goal of the City4Age project, funded by the Horizon 2020 Programme of the European Commission, in particular focusing on the IoT-based personal data capturing system.

Autore Pugliese

• Patrono Luigi , Mainetti Luca

Tutti gli autori

• Mainetti L. , Patrono L. , Rametta P.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2016

ISSN

Non Disponibile

ISBN

Non Disponibile

Numero di citazioni Wos

1

Ultimo Aggiornamento Citazioni

28/04/2018

Numero di citazioni Scopus

15

Ultimo Aggiornamento Citazioni

28/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile