Intelligent RF Sensing for Falls and Health Prediction - INSHEP

Lead Research Organisation: University of Glasgow
Department Name: School of Engineering


The proportion of elderly people is increasing worldwide. In the UK, the Office for National Statistics estimates that "The number of people aged 75 and over is projected to rise by 89.3%, to 9.9 million, by mid-2039; the number of people aged 85 and over is projected to more than double, to reach 3.6 million by mid-2039; and the number of centenarians is projected to rise nearly 6 fold, from 14,000 at mid-2014 to 83,000 at mid-2039". Consequently, conditions such as diabetes, obesity, dementia, Parkinson's disease are expected to increase their incidence, with more and more people affected by multiple conditions at the same time (multimorbidity).
Furthermore, statistics in the UK show that "falls and fractures in people aged 65+ account for over 4 million hospital bed days each year in England alone, and the healthcare cost associated with fragility fractures is estimated at £2bn a year". Physical consequences of fall events (fractures, contusions, open wounds, abrasions, strain, and concussions) often require treatment at A&E departments if not hospitalisation, but they also lead to anxiety and loss of independence. All these reduce the quality of life of the people affected and of their families, as well as generate public costs for healthcare provision.
Our project will investigate how radar technologies will help vulnerable individuals (older people and people with cognitive or physical impairments, or with multi-morbidity conditions) preserve their independence and quality of life, and provide caregivers and health professionals with individualised information on each patient. In practical terms, our system will monitor activity levels over longer periods of time to detect early signs of cognitive and functional decline, providing not only prompt detection of critical events (e.g. falls, strokes), but also predicting these events from indicators in the data that will enable individualised prompt treatment and intervention from health professionals.
Radar snsors transmit and receive electromagnetic waves similar to those used by common devices such as Wi-Fi routers, and the analysis of the received echoes can provide information on how and where a person moves. Radar offers the advantage of providing contactless and non-intrusive monitoring, with no need for the end-users to carry or interact with devices, or alter their behaviour, and no need to record direct optical images of them. This makes these sensors attractive as a potential alternative to wearable sensors and conventional video-cameras, or as a complementary sensor to those ones.
Our project will combine cutting-edge research in the field of electronic engineering and machine learning, with end-users engagement from the very early stages (older people, caregivers, health professionals, community members). We will take into account their inputs, requirements, issues, attitudes in relating with our technology, and inform the design and technical choices while developing our system. This will enable to address potential users' acceptance issues and barriers to the development and adoption of the technology, an element of strength to maximise the impact of our proposal.

Planned Impact

Our project aims to develop a system based on radar sensors to monitor activity levels of vulnerable people (older individuals and people with cognitive or physical impairments or with multimorbidity (two or more long-term conditions), detect critical events (e.g. falls), and predict the insurgence of these events by looking at deviations from normal behaviour that may be related to worsening health status.
This system will benefit older and vulnerable people, enabling them to live independently and for longer time in their homes, avoiding or postponing the need to move to specialised care facilities such as nursing homes, or hospitalization in case of acute treatment. This will also help families and caregivers, providing peace of mind and more accurate automatic monitoring of vulnerable patients, as well as support health professionals with more specific information on the patients. Degrading health conditions may cause subtle changes in the normal behaviour of the people affected, especially in the case of older individuals, but detecting these signs may be very challenging for health professionals and caregivers who can only visit each specific patient sporadically.
This can also have a significant economic and societal impact, contributing to a more cost-effective NHS that can provide better healthcare with reduced resources with the help of technological solutions. This is in line with the EPSRC delivery plan ambition to make the UK a "healthy nation", specifically the challenge of "transforming community health" (by promoting and supporting independent living of vulnerable people in their homes).
As one of the barriers to the adoption and use of ICT based solutions for activity monitoring and fall detection is the lack of confidence and awareness in both healthcare professionals and end-users [1], we will make sure to involve them from the very early stage of the design and testing of our technology. We will incorporate their inputs, requirements, and needs, as well as address any potential issues and concerns regarding the use and the interaction with our technology. We will involve a broad spectrum of end-users through engagement with members of the public and charities and community groups (e.g. Age Scotland, Glasgow Old People Welfare Association), as well as professional caregivers, health professionals in the NHS (NHS Greater Glasgow and Clyde Community Falls Prevention Programme, Greater Glasgow and Clyde or Lanarkshire Health Boards), and policy makers (Glasgow City Council). This engagement work will consist of a series of interviews/focus groups as well as actual testing and direct involvement feedback from the users on the technology, with the addition of two workshop events to bring together the different stakeholders and present the project's results and outputs. We will also leverage on existing support and multidisciplinary collaborations within the University to maximise the academic impact and reach of this work, for example liaising with colleagues at the Institute of Health and Wellbeing (Prof Frances Mair, professor of primary care, and Prof Neil Hawkins, professor of health assessment technologies). Part of these impact activities will also involve Chinese stakeholders (healthcare professionals and policy makers at the UESTC and Sichuan Provincials hospitals, and members of the China Britain Business Council), leveraging on the existing partnership of the University of Glasgow with the University of Electronic Science and Technology of China (UESTC) in Chengdu. The problem of aging populations and related challenges for effective healthcare provision are becoming more and more relevant in China, hence there is significant interest for research and market opportunities for assistive living solutions.

[1] "Report to Congress: Aging Services Technology Study", report by the US Department of Health and Human Services, Office for Disability, Aging and Long-Term Care Policy, June 2012.


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