The work on this project could involve:
- User modelling and personalization
- Devising and evaluating an objective measure and early warning scores for ill health
- Design of simple tool for self-monitoring of at-risk individuals as proof of concept
The project will propose a simple, accurate and reliable measure, with a view to integrate this with a number of personal monitoring devices.
Many, preventable, chronic health issues (such as cardiovascular diseases, musculoskeletal disorders, diabetes and some cancers) are related to excess weight, and in 2014/15 obesity cost the National Health Service some £6bn and society as a whole an estimated £27bn (PHE, 2017). One could say obesity is a huge problem. However, underweight is also undesirable, leading to problems with immune systems and bone density, to name but a few.
The main indicator available to the population is the Body Mass Index (BMI) and although this is a good method for measuring a population’s weight, as a measure of someone’s individual health it is poor, because it does not take into account the make-up of an individual’s weight, that is, the amounts of muscle or unhealthy fat. The limitations of the BMI are well known but no simple, improved measure is widely available for people to easily and accurately monitor whether they may be at risk of developing weight-related disorders. This project aims to remedy this.
We will engage with the Primary Care Research Lead for the region and build upon the strategic partnership we have with Queen Alexandra Hospital in Portsmouth.
This proposal addresses a number of Grand Challenges (such as the EPSRC’s Transforming Community and Health Care and the Industrial Strategy’s AI and Data), as well as the BBSRC’s
Healthy Ageing Across the Life Course programme, the Data Enabled Decision Making Cross-ICT Priority (EPSRC) and both the Health and Wellbeing and Future and Emerging Technologies research themes at the University.
Health Matters: Obesity and the Food Environment (2017). Retrieved from Public Health England
5 Accordian entry requirements
You'll need a good first degree from an internationally recognized university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
- Knowledge of Human-Computer Interaction, User Modelling and Personalization
We’d encourage you to contact Dr Tineke Fitch at firstname.lastname@example.org to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form and select ‘Computing’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
If you want to be considered for this self-funded PhD opportunity you must quote project code COMP4510220 when applying.