Ageing-friendly cities for assessing older adults’ decline: IoT-based system for continuous monitoring of frailty risks using smart city infrastructure

Abstract

Background and aims Population ageing is a typical phenomenon of developed countries with a great influence in their economy and society, with an increment on age-related expenditures. Disruptive solutions are needed to deploy new costeffective and sustainable solutions for aging well and independent living of our seniors. In this sense, new technological paradigms as IoT technologies and smart cities have the potential to become main drivers for innovation uptake. The purpose of this study is to describe a longitudinal cohort study in smart cities for assessing early frailty symptoms deploying an unobtrusive IoT-based system in the Madrid city. Methods A system was deployed in the Madrid city with the participation of 45 elderly users for an average of 71 weeks. Metrics were assessed by the available sensors in combination with the open data infrastructure of Madrid. Metrics include activity of the user, weekly visits pattern and transport daily usage pattern. System engagement was also monitored. Participants are assessed bimonthly with health and functional questionnaires. Results 45 older adults with a mean age of 79.1 years. Participants activity patterns monitor detected changes during potentially risky situations that usually were not reported by traditional assessment tools. Analysis of data collected enabled to identify absence of frailty (robust or post-robust status) Discussion and conclusions The results demonstrate the feasibility of engaging older adults with an IoT-based system and the successful collection of their activity metrics. Variation in the activity patterns may be a first sign of functional decline and enables to identify potential areas of early intervention.

Information and Communication Technologies for Managing Frailty: A Systematic Literature Review

“…The design and implementation of evidence-based practice, such as the use of ICT for managing frailty depend on successful behavioral change interventions [49]. Surprisingly, only one study has explicitly used behavioral changes, which were measured using outdoor walking distances and weekly visiting patterns as outcome variables [40]; more importantly, none of the studies identified in this literature review used a theoretical approach regarding behavioral change. One of these frameworks is the well-known 'COM-B' system.…”

“…Most of the studies in this group were descriptive. As in the frailty detection group studies, some studies asserted that the ICT employed could be used for screening and preventing frailty; however, no quantitative data were provided [5,[36][37], whereas other studies were found to monitor the evolution of the monitored variables (e.g., subject activity and frailty status, [38][39][40][41][42]) effectively.…”

A Microservices e-Health System for Ecological Frailty Assessment Using Wearables

“…IoT health systems allow doctors to monitor patients constantly and to suggest corrective actions according to the analyzed data [29,37,38]. For example, one of the goals of City-4Age and ACTIVAGE H2020 projects is the assessment of frailty using IoT technology based on rules [39]. Furthermore, there are a few efforts to apply microservices in the health domain.…”

The Concept of Smart City in Terms of Improving the Quality and Accessibility of Urban Space for the Elderly; Literature Review

“…IoT services are used for early detection and prevention of cognitive performance decrease and in the cases of falling of the elderly [11]. It is becoming a new platform of assessment of the housing environment, It is important mainly for the personalization of health and care services as well as for prevention [1]. The basic indicators of daily activity, whose monitoring is used in IoT in the housing microenvironment are as follows: number of steps, distance covered, and walking average speed, type of POI (points of interest), number of visit per POI, visit duration, number of trips, used bus lines, distance, and time per trip [1].…”