Dementia patients could remain at home longer thanks to ground breaking technology

Innovative new technology will enable people with dementia to receive round the clock observation and live independently in their own homes, a new study in the journal PL0S One reports.

sabinevanerp, Pixabay CC0

By Natasha Meredith, University of Surrey 04 June 2018

During this unique study, researchers from the University of Surrey in partnership with Surrey and Borders Partnership NHS Foundation Trust have developed state of the art AI technologies, powered by machine learning algorithms, to monitor the wellbeing of people with dementia.

The study known as Technology Integrated Health Management (TIHM) for dementia, uses the ‘Internet of Things,’ a network of internet enabled devices (sensors, monitors and trackers) installed in homes, which can detect an immediate crisis as well as changes in people’s health and daily routines. Any change could indicate a potential health issue and if identified early could prevent a person from becoming seriously unwell and requiring emergency hospital admission.

The well-being of people with dementia can also be monitored using this innovative technology which can detect agitation and irritability.

Dr Payam Barnaghi, Reader in Machine Intelligence at the University of Surrey, said: “The impact of a simple algorithm on the life of people with dementia is staggering. Our algorithms and the unique technology it powers means that round the clock observation of people is possible and this not only helps inform clinical decision making but enhances the care and support given to people with dementia and their carers.

From digital assistants to ‘smart’ medicine bottles, a new wave of connected devices could help people live independently for longer. Patient Gerald Hicks trying out some of the technology involved in Surrey and Borders NHS Trust’s trial. Surrey and Borders Partnership NHS Foundation Trust photo. The Guardian

“Technology plays a growing role in our healthcare system and it is crucial we capitalise on this to improve the care people receive.”

Dr Helen Rostill, Director of Innovation and Development at Surrey and Borders Partnership NHS Foundation Trust, said: “We are delighted to be working with the University of Surrey on this ground-breaking study which we believe has the potential to not only transform support for people with dementia and their carers but also people with other long term and complex health conditions.”

Figures from the Alzheimer’s Society indicate that there are 930,000-people with dementia in the UK, with numbers set to rise to over 1 million by 2025. Currently there is no cure for this very challenging illness, placing financial strain on the NHS as the cost of care continues to soar. Innovative technology like this will help slow the decline and maintain independent living for people with dementia.

Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques, Shirin Enshaeifar, Ahmed Zoha, Andreas Markides, Severin Skillman, Sahr Thomas Acton, Tarek Elsaleh, Masoud Hassanpour, Alireza Ahrabian, Mark Kenny, Stuart Klein, Helen Rostill, Ramin Nilforooshan, Payam Barnaghi. May 3, 2018 PL0S One https://doi.org/10.1371/journal.pone.0195605

Machine-learning based identification of undiagnosed dementia in primary care: a feasibility study, Emmanuel A Jammeh, Camille, B Carroll, Stephen, W Pearson, Javier Escudero, Athanasios Anastasiou, Peng Zhao, Todd Chenore, John Zajicek and Emmanuel Ifeachor. BJGP Open 12 June 2018; bjgpopen18X101589. DOI: https://doi.org/10.3399/bjgpopen18X101589

Source University of Surrey
via EurekAlert! American Association for the Advancement of Science AAAS

Also see
Internet of things set to change the face of dementia care in The Guardian
Modular measurement wristband for personalized dementia therapy, The PYRAMID project: New care approach for greater patient security in Fraunhofer Institute for Reliability and Microintegration IZM
Dementia could be detected via routinely collected data, new research shows in University of Plymouth

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