Early detection of UTI’s possible with IoT and AI collaboration

The Alzheimers’s Society tells us that urinary tract infections are one of the main reasons why patients with Alzheimer’s are hospitalised. To alleviate the extra stress this does, and will in the future put on hospitals, scientists at the University of Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP) have developed a new system that allows data to be harvested from smart home devices like activity monitoring and vital signs monitoring devices, so clinicians can remotely monitor the health of patients and detect UTIs earlier. This data is plugged into an artificial intelligence, enabling machine learning algorithms to apply a technique called Non-negative Matrix Factorisation to find undetected signs of possible UTI cases.
Professor Helen Rostill, director of Innovation and Development at Surrey and Borders Partnership NHS Foundation Trust, said: “The TIHM for dementia study is a collaborative project that has brought together the NHS, academia and industry to transform support for people with dementia living at home and their carers. Our aim has been to create an Internet of Things led system that uses machine learning to alert our clinicians to potential health problems that we can step in and treat early. The system helps to improve the lives of people with dementia and their carers and could also reduce pressure on the NHS.”
Payam Barnaghi, Professor of Machine Intelligence at CVSSP, said: “Urinary tract infections are one of the most common reasons why people living with dementia go into hospital. We have developed a tool that is able to identify the risk of UTIs so it is then possible to treat them early. We are confident our algorithm will be a valuable tool for healthcare professionals, allowing them to produce more effective and personalised plans for patients.”