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I have developed my career in biomedical research, building on my expertise in signal processing, computing and mathematics, but specialising in intrapartum (in labour) fetal monitoring. I am now leading an ambitious programme to develop evidence-based diagnostics in this clinical field. I am uniquely positioned to achieve this by working with the world’s largest and most complete birth cohort of routine labour data (>59,000 deliveries).
I obtained a BSc(Hons) in Applied Mathematics from the Technical University of Sofia (Bulgaria) and a PhD in Computer Science from Portsmouth University. I joined the Nuffield Department of Obstetrics and Gynaecology and the Institute of Biomedical Engineering at Oxford for a post-doctoral position in 2007. In 2012, I founded the Oxford Centre for Fetal Monitoring Technologies, of which I am the Scientific Director. In 2016 I was awarded a NIHR Career Development Fellowship to grow my independent research group. In the same year I also joined the newly formed Big Data Institute at Oxford.
BSc (Hons) PhD
Scientific Director, Oxford Centre for Fetal Monitoring Technologies
- NIHR Career Development Fellow
- Wolfson College Research Fellow
- Visiting Fellow, Department of Engineering Science
- Group Leader
Based jointly at the Big Data Institute and the Nuffield Department of Women's and Reproductive Health
I am leading a research team to develop a data-driven cardiotocography (CTG) system to continuously assess fetal wellbeing during term labour. CTG is the gold standard worldwide to detect if a fetus may benefit from an emergency delivery. Unreliable, empirical CTG interpretation will be replaced with quantified computer- and data-based individualised risk assessment.
We already have a prototype system (OxSys), as the starting point. It is derived from a large birth cohort (59,279 term deliveries) by systematic analysis of computer-based CTG features and clinical risk factors in relation to perinatal outcomes. In tests 'off-line' with the data, the current prototype has shown to perform similarly or better than clinicians in clinical practice. We have developed a tablet app that runs OxSys in real time data at the John Radcliffe Hospital, analysing all CTGs as they are being taken (maternity admission unit, delivery suite or Level 6). We are continuously improving the app's interface in collaboration with the clinicians. The app takes in information from the user about any risk factors if present and modifies the analysis accordingly.
In the coming years, we will continue to use 'big data' to derive new understanding and improved methods for CTG interpretation in the patient-specific clinical context. Beyond this, we will ensure refined optimal performance of OxSys on the birth cohort; validate OxSys on additional data (approx. 48,000 births). We will then take the first steps towards translation to the bedside.
Our work will potentially benefit families, clinicians and the NHS by reducing brain injuries, perinatal deaths and unnecessary interventions
National Institute for Health Research (NIHR)
Action Medical Research
I am keen to hear from interested students or post-doctoral researchers, especially as our team is currently growing.
For more information, including recent publications and up-coming international Workshop, please look at our group's website: Oxford Centre for Fetal Monitoring Technologies
You may also want to have a look at this page for an overview of our research and it's importance.
We are an organiser of the international Workshop on Signal Processing and Monitoring (SPaM) in Labour, with its 3rd Workshop to be held 28-30 Oct 2019 in Porto, Portugal - see webpage.
Petrozziello A. et al, (2019), IEEE Access, 7, 112026 - 112036
Lear CA. et al, (2018), Seminars in Pediatric Neurology, 28, 3 - 16
Stroux L. et al, (2017), Acta Obstetricia et Gynecologica Scandinavica, 96, 1322 - 1329
Georgieva A. et al, (2017), Acta Obstetricia et Gynecologica Scandinavica, 96, 883 - 891
Hoyer D. et al, (2017), Physiological Measurement, 38, R61 - R88