Informing treatment of shoulder pain through upper extremity movement analysis

Motion capture experiments and analysis of their output will be used to provide insight into shoulder pain and its treatment.

Start date
1 January 2021
Duration
3 years
Application deadline
Funding information

The funding covers a full UK/EU tuition fee waiver. A stipend at UKRI rates is also included. The stipend is currently £15,285, tax free and does not need to be paid back.

Funding source
NIHR Applied Research Collaboration [Kent, Surrey and Sussex] through the University of Surrey
Supervised by

About

This funded project will investigate possible links between clinical shoulder pain and movements of the arm obtained during experiments. The aim is to identify patterns in movement that could indicate the best approach to treatment for the joint pain.

Shoulder pain impacts the sufferer’s ability to work, sleep and carry out even basic daily activities. It has an estimated prevalence in the general population of up to 15% and even greater in participants of overhead sports. Despite the prevalence and impact, the long-term outcomes can be poor.

The project will be conducted at the University of Surrey with experiments making use of the motion-capture facilities in the Human Movement Laboratory. Application of novel approaches to analysing the experimental data will be an important part of the project. The analysis techniques will include conventional statistical approaches as well as artificial intelligence techniques.

Collaboration has been established with the physiotherapy unit at the Royal Surrey County Hospital. The supervisory team includes biomedical engineers from the University of Surrey and Brunel University, and a clinical physiotherapist from the Hospital.

Consequently, the project will integrate analytical approaches seen in engineering with the clinical approaches used in treating individuals suffering from shoulder pain.

This project would be suited to an individual with an interest in experimental biomechanics, computational modelling and/or statistical analysis. It is expected that applicants will have a background in physics, engineering, computer science, sport science or another related discipline.

Related links
NIHR Applied Research Collaboration

Eligibility criteria

Applicants are expected to hold a first or upper-second class degree in a relevant discipline (or equivalent overseas qualification), or a lower second plus a good Masters degree (distinction normally required).

Available for UK and EU students.

IELTS Academic: 6.5 or above (or equivalent) with 6.0 in each individual category.

How to apply

Applicants should apply online through the Biomedical Engineering PhD programme page.

Please disregard the application deadline of the 5th of November as that refers only to open calls for PhD applicants rather than this specific project.

Enquiries about the project, role and application process will be welcomed by Dr Matthew Oldfield.


Application deadline

Contact details

Matthew Oldfield
11 AA 02
Telephone: +44 (0)1483 684402
E-mail: m.oldfield@surrey.ac.uk

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