Socially assistive robot Pepper

Artificial Intelligence and Robotics to Help Early Detection of Urinary Tract Infections – Heriot-Watt University

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Socially assistive robots like Pepper will be developed to detect UTI symptoms

A team of researchers from the University of Edinburgh and Heriot-Watt University is developing artificial intelligence (AI) and socially assisted robots to detect urinary tract infections (UTIs) earlier.

Project FEATHER aims to reduce the number of serious adverse outcomes that can result from late or misdiagnosis and reduce the amount of antibiotics prescribed while doctors wait for lab results.

This groundbreaking research has been awarded £1.1 million from the UK Government by the Engineering and Physical Sciences Research Council, part of UK Research and Innovation, the National Institute for Health and Care Research (NIHR).

Urinary tract infections affect 150 million people worldwide annually, making it one of the most common infections. When diagnosed early, it can be treated with antibiotics. If left untreated, UTIs can lead to sepsis, kidney damage, and even loss of life.

However, diagnosis can be difficult with laboratory analysis, a process that takes up to 48 hours and provides the only final result. It can also be difficult to recognize early signs of a UTI because symptoms vary according to age and existing health conditions. There is no single sign of infection but a range of symptoms that may include pain, temperature, frequency of urination, changes in sleep patterns, and tremors.

Urinary tract infections are particularly difficult to diagnose in people receiving formal care, and there is overtreatment with antibiotics in this group as doctors wait for lab results to come back.

To address these concerns, researchers from the University of Edinburgh and Heriot-Watt University are working with two industry partners from the care sector. Scotland’s National Comfort Center, Leuchie House, and Blackwood Homes and Care provide user insights to help researchers develop machine learning methods and interactions for socially assisted robots to support early detection of potential infections and raise an alert for investigation by a clinician.

The project will collect continuous data about the daily activities of individuals in their homes via sensors that can help identify changes in behavior or activity levels and trigger interaction with a socially assistive robot. The FEATHER platform will collect and analyze these data points to flag potential signs of infection before an individual or caregiver realizes there is a problem. Behavioral changes could include using the kettle, changing walking speed, and cognitive function through interaction with a socially assisted robot or changing sleep patterns.

The implementation and AI aspects of the project will be led by Professor Kia Nazarpour, Dr Nigel Goddard and Dr Linda Webb from the University of Edinburgh. Professor Lynn Bailey will lead the robot interaction aspects, assisted by Dr. Mauro Dragon, of Heriot-Watt University.

Professor Kia Nazarpour, Project Leader and Professor of Digital Health at the University of Edinburgh’s School of Informatics, said: “This unique data platform will help individuals, carers and clinicians recognize signs of potential UTIs very early, helping to prompt necessary medical examinations and investigations. It makes the discovery.” Early and timely treatment is possible, improving outcomes for patients, reducing the number of people on A&E, and reducing costs to the NHS.

We also think it will help reduce the amount of antibiotics that are necessarily prescribed as a cover-up while waiting for lab results. As the second most common reason for prescribing antibiotics, infections contribute significantly to the growing problem of drug-resistant bacteria, and there is a broad advantage for society in implementing better diagnostics.”

Professor Lyn Bailey, National Robotarium Chair on Human-Robot Interaction, Assisted Living and Health, said: “We hope that this work will create an additional structured support mechanism for people living independently. Studies show that there is a significant association between delirium and UTI when Older adults, and while caregivers can likely pick up on these signs, we shouldn’t rely on observations alone.We are working with stakeholders to co-design robot interaction and data collection for machine learning methods to support longer, healthier independent lives.

“Working with sensitivity and support with this vulnerable social group is of the utmost importance. By developing technology in the new Assisted Living Lab at the National Robotarium, we can test it in a realistic social care setting.”

Kitty Walker, a care recipient and regular guest at Leuchie House, said: “The impact of a urinary tract infection can be more serious than many people may realize. In general, my speech is affected which can make it difficult to communicate with people as I normally do. Even more seriously, I have been hospitalized in the past after a late diagnosis of a UTI caused me to have a seizure and required mouth-to-mouth resuscitation.

“It often takes a long time to receive a complete diagnosis and be given the appropriate antibiotics to treat the infection. In the meantime, I’ll usually prescribe a general antibiotic until the results come back. Being able to spot early indications that I have a UTI will save any anxiety I may have when I know That there is a problem and it helps reduce the number of different antibiotics that I need to take.”

UK Government Minister for Scotland, Malcolm Offord, said: “Data and artificial intelligence have the potential to transform diagnosis and treatment for many conditions and improve outcomes for patients.

“This research will make a huge difference in finding UTIs as quickly as possible and I am delighted that those in Care Scotland will be among the first to benefit.

“The UK Government is providing £1.1 million in research funding for this project, and through the City Deal we are investing £21 million in the new National Robotorium facilities at Heriot-Watt University.”

The Scottish Government’s Business Secretary, Evan Mackey, said: “I am delighted to see this pioneering and innovative work being carried out in Scotland. By allowing early diagnosis and treatment of urinary tract infections, AI and robotics research can make a key contribution to improving health and social care in Scotland, with Ensure the protection of the dignity of individuals.

“The National Robotarium Museum and its Ambient Assisted Living Laboratory will be a major asset for Scotland and the UK, in supporting people to live well and independently in their communities as they age.”

Colin Foskett, Head of Innovation and Research, Blackwood Homes and Care, said: “Understanding how to use socially assisted AI to better detect UTIs has the potential to improve the health and well-being of our customers. Early detection of UTIs can prevent hospitalization, and associated degradation and ensures that people can continue to live independently for longer.

Mark Bevan, CEO of Leuchie House, said: “Leuchie House is uniquely positioned as a national hub with unparalleled access for guests who trust us to manage the sharing of their health data and expertise.

“This pioneering partnership with guests, the University of Edinburgh and Heriot-Watt University, is just one example of how we are reaching from our base in East Lothian to improve the lives of people across Scotland and beyond, developing important new knowledge through the practice experience and research expertise of partners.”

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