<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/26D10B3E-1C6B-4C08-B554-7EFCEE030E5F" ns1:id="26D10B3E-1C6B-4C08-B554-7EFCEE030E5F"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/F8D19C06-8ACF-4F4F-988B-B58137CDE5C1" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E76F0E03-2B44-4359-89F8-A79D45D371C6" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E76F0E03-2B44-4359-89F8-A79D45D371C6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/A304A426-43D1-4722-9559-4A8A06859815" ns1:rel="FUND" ns1:start="2024-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10134159</ns2:identifier></ns2:identifiers><ns2:title>Novel Biosensor for the Diagnosis of Childhood Sleep Apnoea</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Paediatric obstructive sleep apnoea (OSA) is a common condition which affects up to 6% of children, and up to 60% of obese children. If this is not treated, the child is at risk of serious, chronic health disorders, including heart, brain, hormonal, and mental health conditions. Unfortunately, OSA is very difficult to diagnose, meaning up to 80% of children never receive the care they need. This is primarily because children must currently attend specialist hospitals for a complex, overnight sleep study. This is not only uncomfortable for the child, but also expensive and requires extensive clinical resources. Consequently, this leads to long waiting lists and a lack of accessibility. At present, there is no way to accurately diagnose paediatric OSA in remote settings. This means children often do not receive the treatment they need.

At Seluna, we believe that every child deserves the right diagnosis and treatment to live a healthy life. So, it's our mission to combine our advanced machine-learning software with a novel wearable device to accurately diagnose paediatric sleep disorders in remote settings.

By promoting home testing, we aim to diagnose more children while reducing the strain on hospitals, reducing associated healthcare costs, reducing waiting list times, and easing the burden on the children. Our goal is to provide doctors with diagnostic decision support to prioritise treatment for children who need it most urgently.

We aim to do this using a combination of machine learning, signal processing, and an innovative wearable device concept. Our software will provide a user-friendly interface that will allow clinicians to get a complete snapshot of sleep study data, in such a way that will reduce the time required to diagnose sleep apnoea.

At Seluna, ensuring fairness and minimising bias in our software and hardware is paramount, which this grant will help facilitate. We aim to reduce healthcare inequalities, especially in remote regions.

Designed for pediatric sleep apnoea diagnosis, our hardware will work seamlessly with our software to monitor and analyse sleep patterns. The device will be tailored to be comfortable and non-intrusive for children and can be used outside of the hospital, allowing sleep apnoea diagnosis to happen from home.</ns2:abstractText></ns2:project>