Stroke is the leading cause of severe disability in adults, with over two-thirds leaving hospital with a disability. According to the Scottish Government’s Progressive Stroke Pathway, people should have access to high quality stroke rehabilitation with the aim of optimising function and promoting independence. Rehabilitation should be person-centred, and consider the person’s capacity, needs and preferences. As the average age of people who have a stroke is getting younger, improving the function of their affected arm could be an important goal for an increasing number of people. To understand whether the stroke rehabilitation pathway helps people achieve their desired arm use, we need to know how much people involve their affected arm in their preferred activities.
In this exciting interdisciplinary project, we are proposing to use wearable sensors to investigate people’s arm use in everyday activities, after a stroke. The project will have three aspects: technology development, to improve the information derived from sensors using biomechanical modelling and machine learning; data collection from people after a stroke in the lab and in the community; and engagement with clinicians and patients to understand their views on the stroke rehabilitation pathway. Within these three aspects there is considerable leeway for the right candidate to tailor to their interests, skills, and career aspirations.
The student will be based in the Aberdeen Centre for Health Data Science, a dynamic and multi-disciplinary group of engineers, scientists and clinicians who aim to improve health and care with data. We work closely with the Bioengineering group in the School of Engineering, which houses a modern biomechanics laboratory with a range of equipment for the measurement of arm movement.
The supervisory team includes Dr Dimitra Blana, Lecturer in Health Data Science with expertise in movement analysis and biomechanical modelling; Dr Edward Chadwick, Reader in Biomedical Engineering, an expert in the use of medical devices for measuring movement; and Dr Kathryn Martin, Senior Lecturer in Epidemiology, with extensive experience in the study of physical activity, and stakeholder involvement/engagement in research. We have close links with the Stroke Rehabilitation Unit in Woodend Hospital, Aberdeen, as well as clinical movement analysis laboratories across the UK. This project will give the student invaluable skills for a career in the medical technology sector, NHS, or academia.
Informal enquiries are welcome. Please contact Dr Dimitra Blana ([Email Address Removed]) for more information.
Essential Background of student:
Candidates should have (or expect to achieve) a minimum of a First Class Honours degree in Health Data Science, Biomedical Engineering or a related subject. Applicants with a minimum of a 2.1 Honours degree may be considered provided they have a Distinction at Master's level.
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APPLICATION PROCEDURE:
We encourage students to apply early, as applications will close when a suitable candidate is found.
International applicants are eligible to apply for this studentship but will have to find additional funding to cover the difference between overseas and home fees (approximately £14,000 per annum)
- Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php
- You should apply for Applied Health Science (PhD) to ensure your application is passed to the correct team for processing.
- Please clearly note the name of the supervisor and exact project title on the application form. If you do not mention the project title and the supervisor on your application it will not be considered for the studentship.
- Candidates should have (or expect to achieve) a minimum of a 1st Honours degree at undergraduate level. Applicants with a 2.1 Honours degree may be considered provided they have a Distinction at Masters level.
- Please note: you DO NOT need to provide a research proposal with this application
- General application enquiries can be made to [Email Address Removed]