Towards quick clinical adaption of Diagnostic Decision Support System (DDSS) for pregnancy monitoring in low-resource settings: deriving tocodynamometry-like (TOCO-like) waveform from electrohysterography (EHG)

Eligibility: UK/EU/International graduates with the required entry requirements

Funding details: Bursary plus tuition fees (UK/EU/International)

Duration: Full-time – between three and three and a half years fixed term

Application deadline: 14th May 2021

Interview dates: Will be confirmed to shortlisted candidates

Start date: September 2021

For queries please contact Dr Yuhang Xu.


Introduction

Coventry University is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship within the Centre for Intelligent Healthcare.

Project details

The strength and frequency of uterine contraction (UC) is important in monitoring dysfunction in pregnancy and labour, e.g., preterm birth and dystocia. External tocodynamometry (TOCO) is the only clinical device currently available for routine UC detection, which measures changes of the abdominal shape during UCs via a single pressure sensor. However, it suffers from several drawbacks, including restriction by belt, intolerance of movement and limited clinical information. Electrohysterography (EHG), measured by abdominal electrodes, is a potential alternative of TOCO for UC assessment, which avoids the drawbacks of TOCO. Nevertheless, EHG has not been adopted in clinical use due to the unfamiliarity of clinicians with the raw EHG signals. 

This project aims to develop advanced algorithms to convert EHG to TOCO-like waveforms to assist clinicians for fast adoption of EHG in clinical practice. Further, clinically useful features will be extracted from the derived waveforms to develop a Diagnostic Decision Support System (DDSS), which helps reducing the training requirements for clinicians, enabling wide pregnancy monitoring for low-resource settings.

This project builds on previously funded international collaborative research and brings together a supervisory team with interdisciplinary expertise in engineering, electrophysiology, maternity care and usability testing.

Funding 

This is a fully-funded studentship including full tuition fees (UK/EU/International) plus stipend (based upon the applicable UKRI rate at the point of the award) and additional allowances.

Benefits

Training and Development

The successful candidate will receive comprehensive research training including technical, personal and professional skills.

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities. 

Entry requirements

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average. 
    PLUS 
    the potential to engage in innovative research and to complete the PhD within a 3.5 years
  • a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

In addition

  • Degree in the relevant specialist subject area such as Electronic Engineering, Biomedical Engineering or Computer Science
  • Background in electrophysiology or similar
  • Coding/ programming (e.g. Matlab) skills in bio-signal processing
  • Knowledge of statistical analysis techniques
  • Knowledge of software development (desired)
  • Ability to think innovatively and critically analyse data and results
  • Good written and oral communication skills
  • A record of presenting papers at conferences and of publishing peer reviewed research papers (desired)
  • Ability to meet deadlines, sometimes under pressure
  • Ability to work independently and also as part of a local and international multidisciplinary team
  • Willingness to take on roles to enhance research team activities and profile

How to apply

To find out more about the project please contact Dr Yuhang Xu.

All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.

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