The Problem: Early Detection of Age-Related Risk
The aging of the population presents a major challenge for social and health services. The late detection of frailty and Mild Cognitive Impairments (MCI) in older adults complicates their care and reduces their quality of life. It is therefore crucial to develop methods to identify these risks as early as possible.
Our Solution: City4Age, the Smart City Serving Seniors
The City4Age project, funded by the European Commission (Horizon 2020), aims to transform cities into smart assistance environments (“Ambient Assisted Cities”). We are developing an innovative framework of ICT tools and services that cities can deploy for the early detection of risks related to frailty and MCI. The goal is to offer personalized interventions to help seniors improve their daily lives and promote positive behavioral changes.
How It Works?
Unobtrusive Data Collection
The smart city collects data on individual behaviors in a non-intrusive way, through sensors and connected objects.
Risk Detection
The collected data allows for the identification of segments of the population potentially at risk, even before symptoms appear.
Personalized Monitoring
For individuals already identified, the system allows for close monitoring to detect negative behavioral changes and alert the relevant services.
Proactive Interventions
The early detection of a change triggers individualized interventions to support the person and prevent their condition from worsening.
Project Team
Bessam Abdulrazak
Professor, Department of Computer Science, Université de Sherbrooke
Director of the AMI-Lab
Publications
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