Facilitating health and wellbeing by developing systems for early recognition of urinary tract infections - Feather

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Informatics


Urinary tract infections (UTI) are one of the most common types of infection, impacting more than 92 million people worldwide. When diagnosed early, UTI's can readily be resolved with antibiotics. However, left untreated, it can lead to urosepsis (>1.6 million deaths), kidney damage and ultimately death.

Identifying the early symptoms of a UTI can be challenging, symptoms are different in younger and older people and people with underlying health conditions. In addition, there is no one symptom but a collection of symptoms that indicate a person has a UTI. These include changes to urine: colour, smell, frequency; incontinence, pain, confusion, agitation delirium, temperature, shaking and changes in sleep. This concoction of symptoms is what makes identifying the signs of a UTI difficult for the person concerned and/or their carers.

This project will gather data about the activities of an individual in their home on a continuous basis. By having data on activities of daily living, it is possible to identify changes. The Feather platform will combine these data points to recognise the emergence of a UTI. This is in fact quite difficult for an individual themselves or a carer to see. Thus, the Feather project will be able to raise an alert for investigation of a UTI, before a person could do it themselves, enabling early intervention, to get appropriate treatment quickly. For example, the following can all be indicators of behaviours that are impacted by the symptoms of UTI's, patterns for activities of daily behaviour, e.g. kettle use, change in walking pace, cognitive function through interaction with an intelligent agent, e.g. an embodied robot.

The Feather project could enable a GP to have the time to wait for lab results to urine tests to ensure appropriate prescription of antibiotics, reducing the cost to the NHS of prescriptions and improving outcomes for the patient. Early diagnosis should reduce the number of patients presenting at A&E and reduce the number of cases developing to urosepsis, kidney failure and ultimately death.

Working with stakeholders, we will co-design, co-implement and co-evaluate the Feature project.


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