AI and robots used to enable faster detection of UTIs

Care home residents in Scotland could be among the first to benefit from a project that aims to use artificial intelligence (AI) and robots to detect urinary tract infections (UTIs) earlier.

Researchers from the University of Edinburgh and the city’s Heriot-Watt University are working together on the Feather initiative, which seeks to reduce some of the negative consequences of late diagnosis of UTIs.

The expert leading the programme, Professor Kia Nazarpour of the University of Edinburgh, said it could eventually reduce the number of people dealing with accidents and emergencies with infections, as well as help tackle antibiotic overprescribing.

Around 150 million people a year worldwide may suffer from UTIs, making them one of the most common types of infection.

If caught early, UTIs can be treated with antibiotics, but if left undiagnosed, they can lead to sepsis, kidney damage, and even death.

Early signs of a UTI can be difficult to spot because symptoms vary with age and existing health conditions.

There is not a single sign of infection but a collection of symptoms which could include pain, increased temperature, urination frequency, sleep disturbances and tremors.

The new research involves installing sensors to detect changes in behavior that could indicate someone has such an infection – such as increased use of the kettle or a change in walking pace – before the individual or their carers are aware of the problem.

These would then trigger an interaction with the ‘socially assistive robot’, with the technology for this under development at the new Assisted Living Lab at Heriot-Watt University’s National Robotarium.

The work has already received £1.1 million in UK government funding from the Engineering and Physical Sciences Research Council – which is part of UK Research and Innovation – and the National Institute for Health and Care Research (NIHR).

Work is ongoing with two industry partners from the care sector – Scotland’s national respite centre, Leuchie House and Blackwood Homes and Care – with researchers seeking to develop machine learning methods and interactions for socially assisted robots that could support early detection of a potential infection and raise an alert for investigation by a physician.

The Scottish Office minister, Lord Offord, said the research could ‘make a big difference in detecting UTIs as quickly as possible’ (Aaron Chown/PA)

Kitty Walker, who is a regular guest at Leuchie House, said UTIs could be affecting her speech, making communication difficult.

“The impact of having a UTI can be much more serious than many people realize,” she said.

“I have been hospitalized in the past after a late diagnosis of a urinary tract infection led me to have a seizure and required mouth-to-mouth resuscitation.

“It can often take a long time to receive a full diagnosis and be given the right antibiotics to address the infection.

“Being able to spot early indicators that I have a UTI would spare any anxiety I might feel when I know there is a problem and help cut down on the number of different antibiotics I have to take.”

The professor. Nazarpour, project leader and professor of digital health at the University of Edinburgh’s School of Informatics, said working with the Feather project “would help people, healthcare professionals and doctors recognize the signs of potential urinary tract infections much earlier, helping to solicit the necessary medical checks and tests”.

He added: “Early detection makes early treatment possible, improving patient outcomes, reducing the number of people presenting to the emergency room and reducing costs for the NHS.

“We also believe it will help minimize the amount of antibiotics that are necessarily prescribed as cover pending lab results.

“As the second most common reason for prescribing antibiotics, infection contributes significantly to the increasingly worrying problem of drug-resistant bacteria, and there is a widespread societal benefit to implementing better diagnosis.”

Scottish Office Minister Lord Offord said: “Data and artificial intelligence have the potential to transform the diagnosis and treatment of so many conditions and improve patient outcomes.

“This research will make a huge difference in detecting urinary tract infections as quickly as possible and I am delighted that care sector residents in Scotland will be among the first to benefit.

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

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