Technological Solutions for Social Isolation Monitoring of the Elderly: A Survey of Selected Projects from Academia and Industry.

Social isolation is likely to be one of the most serious health outcomes for the elderly due to the COVID-19 pandemic, especially for seniors living alone at home. In fact, two approaches have been used to assess social isolation. The first is a self-reported survey designed for research purposes.

A Smart Shoe Insole to Monitor Frail Older Adults' Walking Speed: Results of Two Evaluation Phases Completed in a Living Lab and Through a 12-Week Pilot Study.

Background: Recent World Health Organization reports propose wearable devices to collect information on activity and walking speed as innovative health indicators. However, mainstream consumer-grade tracking devices and smartphone apps are often inaccurate and require long-term acceptability assessment.

Objective: Our aim is to assess the user acceptability of an instrumented shoe insole in frail older adults.

A Smart Insole to Promote Healthy Aging for Frail Elderly Individuals: Specifications, Design, and Preliminary Results.

Background: Older individuals frequently experience reversible "frailty syndrome,", increasing incidence of disability. Although physical exercise interventions may delay functional decline, there are difficulties in implementing them and performing seamless follow-up at home. Very few technological solutions attempt to address this challenge and improve individual participation.

A telemetry system embedded in clothes for indoor localization and elderly health monitoring.

This paper presents a telemetry system used in a combined trilateration method for the precise indoor localization of the elderly who need health monitoring. The system is based on the association of two wireless technologies: ultrasonic and 802.15.

Smart wearable systems: current status and future challenges.

Objective: Extensive efforts have been made in both academia and industry in the research and development of smart wearable systems (SWS) for health monitoring (HM). Primarily influenced by skyrocketing healthcare costs and supported by recent technological advances in micro- and nanotechnologies, miniaturisation of sensors, and smart fabrics, the continuous advances in SWS will progressively change the landscape of healthcare by allowing individual management and continuous monitoring of a patient's health status. Consisting of various components and devices, ranging from sensors and actuators to multimedia devices, these systems support complex healthcare applications and enable low-cost wearable, non-invasive alternatives for continuous 24-h monitoring of health, activity, mobility, and mental status, both indoors and outdoors.

Behaviour monitoring of the elderly by trajectories analysis.

This paper presents a way to keep the elderly autonomous in their daily activities. The principle is to monitor their behaviour and more specifically their trajectories of movement in the living area. Two methods have been developed and compared: supervised and unsupervised classification.

Smart homes - current features and future perspectives.

In an ageing world, maintaining good health and independence for as long as possible is essential. Instead of hospitalization or institutionalization, the elderly and disabled can be assisted in their own environment 24h a day with numerous 'smart' devices. The concept of the smart home is a promising and cost-effective way of improving home care for the elderly and the disabled in a non-obtrusive way, allowing greater independence, maintaining good health and preventing social isolation.

Wireless fall sensor with GPS location for monitoring the elderly.

Falls of the elderly has become a major public health problem in our modern society. It is both the first cause of accidental death, but also the beginning of the loss of autonomy from these people. In this context, the paper describes a solution based on an energy-efficient embedded device capable of detecting the fall, to send a warning to a control and monitoring processing station and to locate the person in a close external environment.

PROSAFE-extended, a telemedicine platform to contribute to medical diagnosis.

A single elderly, dependent subject was monitored for a period of three months. Data were collected from 12 sensors in his apartment. We investigated new criteria for diagnosing abnormal events with more reliability.

A review of smart homes- present state and future challenges.

In the era of information technology, the elderly and disabled can be monitored with numerous intelligent devices. Sensors can be implanted into their home for continuous mobility assistance and non-obtrusive disease prevention. Modern sensor-embedded houses, or smart houses, cannot only assist people with reduced physical functions but help resolve the social isolation they face.

An extended PROSAFE platform for elderly monitoring at home.

In 1995, the first principles of a monitoring system based on a study of behavioural differences compared to normal living habits were put forward. These gave rise to the launch of a PROSAFE programme involving the use of distributed presence sensors and diagnostic components based on movement criteria. The approach was validated in a hospital and institutional environment, in a room being monitored at night.

Assessment of activity of elderly people using a home monitoring system.

A multisensor home monitoring system has been developed within a telecare project to help elderly people by observing mobility changes indicative of abnormal events. This paper assesses the motor activity and the relationships between activity measures using the system. The motor activity data (in bed, getting up, getting out, visiting the toilets) are analysed from a statistical perspective to assess changes in occurrence, time and duration.

Validation of a remote monitoring system for the elderly: application to mobility measurements.

The aim of this paper is to introduce a smart tool for the assessment of the mobility of patient with motor disorders and to evaluate its performance through some initial experiments. These experiments are based on a system which is composed of sensors connected to a Personal Computer (PC) using data acquisition cards and a communication network. The PC includes a data acquisition and processing software.