It is estimated that over two-thirds of women experience Pregnancy-Related Low Back Pain (P-RLBP) and the pain may be severe enough to interfere with work, daily activities and sleep. Furthermore, women who experience P-RLBP in one pregnancy may continue to experience problems post-delivery and/or with subsequent pregnancies.
Preliminary findings from a cohort study by Dr Dianne Liddle, that attained insight from 200 pregnant women, suggest that many women are choosing to self-medicate with over-the-counter painkillers, with little input from health care professionals. There is a growing concern of such behaviours, as the effect of these medications on the unborn foetus is one of critical importance and little is known about the long-term impact. Furthermore, pressures on the health service are steadily increasing.
Therefore, a more effective method is needed to identify the most suitable form of invention in a timely fashion.
ICT is projected to be a key facilitator in enhancing how we operate our health services. As such, the PhD project will build upon the survey findings from Dr Liddle’s work, and, through her expertise in this field, it will involve the development of an intelligent system for gathering information about women’s on-going experiences and management of P-RLBP as it occurs.
This PhD would go beyond current state-of-the-art by using artificial intelligence (AI) on the data to allow for better targeted information to the patient as their condition changes before, during and after pregnancy.
This could lead to patient centred condition control via a dedicated App that would suggest exercise, appropriately tailored to the stage of pregnancy, to significantly reduce P-RLBP more than usual care alone. Stratifying women into different levels of need would help alert health care professionals that an intervention is needed and therefore provide an individually tailored programme to better meet their needs. The project will have these main overarching objectives:
1. To discover key requirements and scientific underpinnings from the existing datasets, combined with Dr Liddle’s guidance/expertise and literature. Methods such as AI, statistical analysis, and logistic regression analysis will be employed.
2. From these requirements and review of the state-of-the-art in the domain of P-RLBP, and relevant health tools/devices, a prototype tool will be developed tailored to pregnancy. Whereby the existing data collection occurred a maximum of 4 times for the participant, this tool will enable a much higher frequency of reporting, (i.e. pain levels/location, quality of life, function) enabling a comprehensive and enriched overview of the history and occurrence to be achieved.
3. The prototype will be deployed to enable data collection. A dashboard for Dr Liddle will show the current state of the user to assist decision making and further refine intervention strategies for the health personnel, and provide insight to refine the system further.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided). For Non EU nationals the candidate must be "settled" in the UK.
As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day
Adrian Johnston - PhD in InformaticsWatch Video
Monday 18 February 2019
25 to 29 March 2019
The largest of Ulster's campuses
When applying for this PhD opportunity please quote reference number: