Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.


Professor Antoniya Georgieva

Description of project 

Across the globe, each day, we continue to have term babies arrive at delivery wards in good condition in utero, only to be born hours later with neurological injuries (1). The consequences are profound and life-long for the babies, parents, siblings, and their wider family (2). Clinical staff involved in the obstetric management are severely impacted in multiple ways. On the other hand, Cesarean section to avoid oxygen deprivation during labor carries multiple risks for mother, fetus, future pregnancies; as well as costs. But achieving safe spontaneous delivery is sometimes challenging due to poorly understood and complex fetal physiology, and often, conflicting healthcare needs for mother and baby.

Oxford 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, the deaths of babies during labour or after birth and unnecessary medical interventions in childbirth.

Our multidisciplinary team is focused on developing and implementing novel technologies for continuous monitoring and risk assessment of the fetus in-utero at the onset of and during labour. We employ a range of data-science methods to provide automated and data-driven analysis of physiological signals alongside clinical risk factors (for example, fetal or maternal age, co-morbidities, maternal temperature, etc).

We are based at the John Radcliffe Hospital and at the Big Data Institute and collaborate with Computer Science Department. A DPhil project with our team could center on data analysis and risk-assessment using continuous pre- and in-labour fetal heart rate monitoring datasets and/or imaging of in-utero dynamics with novel wearables under development in our team.

1. Gale DC, Stanikov ME, Jawad S, Uthaya DS, Modi PN. Brain Injury Occurring During or Soon After Birth: A Report for the National Maternity Ambition Commissioned by the Department of Health. Imperial College London, UK (2018).

2. Lee BL, Glass HC. Cognitive outcomes in late childhood and adolescence of neonatal hypoxic-ischemic encephalopathy. Clin Exp Pediatr. (2021) 64:608–18.



Students will have access to a wide-range of seminars and training opportunities through the many research institutes and centers based in Oxford, for example training scientific presentation giving; writing a thesis and scientific publications; medical statistics; quantitative analysis; communication and assertiveness, etc.

In addition, we will support student training as per their specific needs and interests such as short courses statistical methods, machine learning, fetal monitoring, etc.



No available funding.