Real-world evaluation of compensatory movements and prosthesis non-wear in people with upper-limb absence at University of Salford

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Real-world evaluation of compensatory movements and prosthesis non-wear in people with upper-limb absence at University of Salford

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[ad_1] Project Description: To co-develop with users, methods which use wearable sensors to evaluate the extent of compensatory moveme

Lecturer (Teaching) in Sports Medicine, Exercise and Health at UCL
PhD Studentship – Using Scientific Machine Learning to Investigate the Electromechanical and Energetic Changes of Genetic Mutation-induced Hypertrophic Cardiomyopathies: An Embodied AI Approach at Manchester Metropolitan University
Research Assistant (Fixed Term) at University of Cambridge

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Project Description:

  1. To co-develop with users, methods which use wearable sensors to evaluate the extent of compensatory movements performed by upper-limb prosthesis users during day-to-day life.
  2. To identify the most acceptable of the different methods 
  3. To use this method, combined with our previous techniques [based on upper-limb symmetry and prosthesis non-wear detection] to record patterns of prosthesis non-use, use and compensatory behaviours in a small number of prosthesis users

The outcomes would be that we would have a series of novel algorithms to allow the real-world assessment of a range of compensatory movement features performed by prosthesis users with and without their prosthesis. For example, these could include a measure of the extent of forearm rotation due to an absence of wrist rotation. This could then be further classified as forearm rotation caused by shoulder lift or forearm rotation caused by torso lean. We would also look for these techniques to be adopted within NHS centres alongside the rollout of multi-articulating hands. Although we understand that there may be other limitations on this including the NHS budgets. This aspect may form part of a wider project to evaluate upper-limb prostheses at scale in order to influence policy decisions. 

The student would need to have a technical background in engineering, computer science, maths, physics or equivalent. They will be required to undertake signal analysis and will need to have a baseline level of understanding of coding. 

Entry Requirements: Applicants are normally expected to achieve either:

  • a minimum of an upper-second class honours degree from an undergraduate course in an appropriate physical or biological science, science, mathematics or engineering

or

  • a clinical qualification related to prosthetics, orthotics and the other relevant allied health disciplines, with additional evidence of skills in engineering and physical sciences (e.g. biomechanics, human gait)

It will be run as part of the Centre for Doctoral Training in Prosthetics and Orthotics (https://www.salford.ac.uk/centre-for-doctoral-training-in-prosthetics-and-orthotics). The successful candidate will have access to unique training program and engage with students from multidisciplinary backgrounds. The student will also be supported by a supervisory team with multidisciplinary expertise in this field and well-equipped facilities.

How to apply: For further information on the CDT and how to apply please visit the CDT website: https://www.salford.ac.uk/centre-for-doctoral-training-in-prosthetics-and-orthotics

A selection of the current students and projects may be found at https://hub.salford.ac.uk/cdt-students/

Informal enquiries about how to apply may be directed to cdt@salford.ac.uk  

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.

For more information and to apply for this vacancy, please visit www.salford.ac.uk/centre-for-doctoral-training-in-prosthetics-and-orthotics

At the University of Salford we are committed to an inclusive approach to promoting equality and diversity.

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