Recipient organisationNIHR HealthTech Research Centre in Paediatrics and Child Health
NIHR supportRecorded as supported by this research centre
PeriodFeb 2025 — Ongoing
In plain English
AI plain-English summary
A child’s oxygen level can drop dangerously low during a seizure or fever, but existing pulse oximeters often fail because the child cannot stay still long enough for a reliable reading. Current technology relies on detecting several heartbeats over multiple seconds to extract a signal. When a young patient moves, the data becomes corrupted by motion artefacts, forcing clinicians to repeat measurements and prolonging appointments. This is especially problematic in acute paediatric settings where patient compliance is low. The researchers have developed a new method that uses high-frequency modulation to shrink the measurement timescale to a fraction of a second—fast enough that patient motion is effectively frozen. If the prototype succeeds, clinicians in ambulatory care could obtain accurate oxygen saturation readings from a wriggling infant in seconds rather than minutes. This would reduce face-to-face time, speed up triage decisions, and cut appointment lengths. The project will produce a working prototype, a clinical needs report, and proof-of-concept measurements, laying the groundwork for a follow-on device that could transform point-of-care monitoring for children.
View original technical description
Clinicians in ambulatory care settings often require an oxygen saturation reading from a child to determine the severity of their illness and whether hospital assessment or admission is required. Unfortunately, existing technology is not fit for purpose, in particular the challenge of taking an accurate measurement if the patient does not remain still (which can lead to ‘motion artefacts’ in the data collected). This is particularly challenging in acute paediatric settings where patient compliance is low, greatly increasing appointment times. Motion artefact arises because the measurement timescales are dictated by the beating of the patient’s heart, requiring multiple seconds of stable measurement to acquire a series of heartbeats for signal extraction. We have proposed a new method that circumvents this limitation by employing a high frequency modulation to reduce measurement timescales by several orders of magnitude to a duration over which patient motion is effectively stationary. This new approach would offer advantages over existing point-of-care monitoring devices by reducing the face-to-face patient time required for a clinician to measure SpO2 successfully. Theoretical calculations have demonstrated the feasibility of our approach, and the aim of this project is to construct a functioning prototype, which will help start the translation of this new method into practice. The research project will take place over 5.5 months, conducted by a masters student with supervision from GOSH BRC Paediatric Excellence Initiative (PEI) and University of Oxford. Outputs include a knowledge exchange trip with other PEI sites, a Clinical Need and human factors report, a prototype device, proof-of-concept measurements, and a project report. This project is reprofiled from funding originally allocated to a PhD project in the same context. This project will inform and be complemented by a follow-on project (from the same reprofiled funding) based at University of Sheffield (expected 2025-2027).
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