Oxford Centre for Labour Monitoring
The Oxford Centre for Labour Monitoring is committed to preventing injury of babies during labour and delivery, caused by lack of oxygen in utero - rare but devastating events. Our work will potentially benefit families, clinicians and healthcare systems by reducing brain injuries, perinatal deaths and unnecessary interventions.
Our specialist team develops data-driven cardiotocography (CTG) systems/software to continuously assess fetal wellbeing at the onset of and during term labour. We are based at the John Radcliffe Hospital and at the Big Data Institute.
Expert Advisor and Patient Public Voice, co-founder of the Campaign for Safer Births
Oxford University Hospitals NHS Foundation Trust
St George's University Hospitals NHS Foundation Trust
MONITORING DURING LABOUR
Photo caption: Daily fetal monitoring in labour at the Oxford's Hospital. The Cardiotocogram (CTG) consists of two graphs: fetal heart rate and uterine contractions. A typical delivery unit generates 20-25km/year of paper CTGs.
We can listen to the fetal heart rate through a stethoscope, a Doppler hand-held device or a continuous electronic monitor. Electronic monitoring produces a paper strip, showing graphs of the fetal heart rate and of uterine contractions, which change with time.
During birth, the stress of contractions and descent through the birth canal can reduce a baby’s oxygen supply. We use advanced signal processing and data analytics to interrogate our large database of nearly 100,000 labours at term, with digital CTGs linked to perinatal outcomes. We are also researching which clinical factors, markers or symptoms can make fetal monitoring in labour more individualised and precise.
Our goal is to translate the new findings into a software for risk assessment at the bedside during labour, similarly to the Dawes-Redman pre-labour CTG monitoring decision-support.
Parent, Patient and Public Involvement (PPPI)
The Oxford Centre for Labour Monitoring is committed to engaging the public in our work, by communicating what we do clearly and by putting women and families at the centre of our research.
Because of the unique nature of our work, we call this Parent, Patient and Pubic Involvement (PPPI).
We have further representation from women with lived experience of labour monitoring and experience of different outcomes on our PPPI panel.
DECIDE: DECision-support for Intrapartum Data-driven Evaluation
i4i NIHR Product Development Award
1 May 2021 – 30 April 2024
More information coming soon....
SIGNAL PROCESSING & MONITORING IN LABOUR WORKSHOPS (SPAM)
The Signal Processing and Monitoring (SPaM) in Labour workshop is a bi-annual event, held since 2015. The workshops provide a friendly forum for people with expertise across different fields, who are learning to speak the same multidisciplinary language and keep pushing forward the research in intrapartum monitoring. Anyone with interest in intrapartum fetal monitoring and/or passion for healthy labour outcomes is welcome, including medical doctors, midwives or other health care professionals, mathematicians, engineers, PhD Students or industry representatives. It is an exciting initiative to bring together experts in labour monitoring and fetal heart rate analysis to critically review and discuss current issues such as: new technology; comprehensive digital databases; statistical analysis; classification; clinical practice, fetal physiology and challenges. There are talks on the clinical aspects of labour monitoring and fetal physiology as well as computerised CTG and heart rate variability, and we are providing a truly multidisciplinary forum and spirit.
Watch SPAM In Labour Workshop Talks
Tentative dates for next Signal Processing and Monitoring in Labour Workshop: 1-4 June 2022; Location to be confirmed
No currently open positions are available but if you wish to join the team, keep in contact please!
Georgieva A. et al, (2021), BJOG: An International Journal of Obstetrics & Gynaecology
Georgieva A. et al, (2019), Acta Obstetricia et Gynecologica Scandinavica, 98, 1207 - 1217
Petrozziello A. et al, (2019), IEEE Access, 7, 112026 - 112036
Lear CA. et al, (2018), Seminars in Pediatric Neurology, 28, 3 - 16