Graduate Teaching Assistant (A computer vision-based innovative rehabilitation system for stroke, Spinal Cord Injury (SCI) and Motor Neurone Disease (MND) patients for improving their care)

Fixed term for 3 years

University of the Year 2014/2015 – Times Higher Education Awards

Research proposals are invited in the areas below:

A computer vision-based innovative rehabilitation system for stroke, Spinal Cord Injury (SCI) and Motor Neurone Disease (MND) patients for improving their care

People affected by stroke, SCI and MND often experience mobility impairments. Rehabilitations for such people are very expensive, mainly due to the required volume of labour intensive therapies. It is well-known that repetitive practice such as Activity of Daily Living (ADL), is key to successful rehabilitation and the extent of recovery is directly linked to the amount of practice.

It is time-consuming and requires a high degree of consistency for a carer to observe an individual performing activities and is subject to the Hawthorne effect. This can have an adverse influence on therapies offered, with treatments focused on what the therapist might see as important instead of what is actually important for an individual to live independently.

The proposed research would look into the computer vision based automation of the ADL tasks. The aim is to analyse the video stream of individual performing ADL and develop algorithms, which could measure the deviations by comparing it to a perfect execution (face-to-face with carers) of the same ADL. This would provide an in-depth detail comparison of the task execution and visual aid to the carers/patients to provide more consistent feedback.

The ideal candidate should have a strong scientific interest, self-motivation and willingness to work as a team player within an interdisciplinary setup involving people from Computing, Psychology and Health professionals. You should have a strong programming skills (e.g. C/C++, MATLAB, Python) and knowledge in computer vision and activity recognition. Familiarity with tools such as OpenCV, Caffe, VLFeat, MatConvNet and Theano will be beneficial.

Informal enquiries may be addressed to Dr Ardhendu Behera (Department of Computing) at beheraa@edgehill.ac.uk

How to apply

Applicants must complete the online application form, attaching one document containing:

• A ‘Research Proposal’ which should not exceed 2,000 words


• A full academic curriculum vitae

Applicants should normally have/be about to obtain, a Masters qualification in a relevant subject.

Selection Criteria:

Selection will be based on the following:

• Your curriculum vitae


• The synergy between your qualifications, research experience and declared research interest


• The quality of the research proposal


• Performance at interview


• Supervisory capacity in the declared area of research


• Previous tutoring/teaching experience and related subject based qualifications


• The strategic and developmental needs of the faculty

The Recruitment Process

Shortlisted candidates will be invited to interview and asked to give a presentation related to their proposal. Successful candidates at interview will be put forward to a final selection panel which will make the decision on the award of the studentships. Candidates will not have to attend the final panel.

The closing date for all studentships is Sunday 10 April 2016

Interviews will be held between Tuesday 3 May and Wednesday 11 May 2016