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The University of Southampton
Interdisciplinary Research Excellence

High-tech healthcare: health and wellbeing in the future

Published: 15 May 2013

Professor Ann Ashburn is part of the interdisciplinary research collaboration between the Universities of Southampton, Reading and Bristol, which has been awarded an EPSRC grant of £12 million. They will work in partnership with Bristol City Council, IBM, Toshiba and Knowle West Media Centre (KWMC).

Our healthcare system faces unprecedented challenges. Britain is the most obese nation in Europe and the country's ageing population is especially at risk from isolation, depression, strokes and fractures.
Known as SPHERE (Sensor Platform for HEalthcare in a Residential Environment), this collaboration will address these issues by developing 24/7 home sensor systems to monitor the health and wellbeing of people living at home.

The collaboration's vision is to impact all these healthcare needs simultaneously through data-fusion and pattern-recognition from a common platform of non-medical/environmental sensors at home. This will include ubiquitous and unobtrusive 'passive sensors' embedded in clothing or jewellery, or even implanted, possibly in association with remedial surgery.

The University of Southampton has UK-leading expertise and lab facilities for studying movement in stroke and Parkinson's disease rehabilitation, and also conducts research into falls and impaired balance.

Professor Ann Ashburn, Professor of Rehabilitation at the University of Southampton, says: "We have limited knowledge of the ways in which individuals move about, negotiate obstacles and on some occasions become unsteady and fall over in their homes. This exciting research opportunity will allow us to detect these situations and make major contributions to fall prevention among the older population."

The system will be general-purpose, low-cost and accessible. Sensors will be passive and suitable for all patients, including the most vulnerable. An example of SPHERE in action could be the way it will be able to identify an overnight stroke or mini-stroke on tthe patient's waking, by detecting small changes in behaviour, expression and gait. It could also monitor a patient's compliance with their prescribed drugs.

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