[Comp-neuro] PhD position at the University of Exeter
K.Tsaneva-Atanasova at exeter.ac.uk
Sat Dec 2 23:45:53 CET 2017
Developing Gaze Training for Skilled Upper-Limb Prosthetic Use - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2892
About the award
This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.
The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.
Please note that of the total number of projects within the competition, up to 15 studentships will be filled.
Professor Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298>
Dr Gavin Buckingham<http://sshs.exeter.ac.uk/staff/index.php?web_id=Gavin_Buckingham>
Dr Sam Vine<http://sshs.exeter.ac.uk/staff/index.php?web_id=Samuel_Vine>
Professor Mark Wilson<http://sshs.exeter.ac.uk/staff/index.php?web_id=Mark_Wilson>
Streatham Campus, Exeter
Learning to use a prosthetic limb is inherently difficult and requires a huge amount of concentration. Like learning how to wield a new tool for the first time, amputees need to acquire the confidence and dexterity required for skilled action. In order to produce accurate goal-directed movements the motor system requires accurate and timely visual information making the timing and location of the person’s gaze, with relation to the movement of their limbs, critical for skilled behaviour. There is, however, no structured training protocol for use with prosthetic hands. We aim to develop a novel gaze training regime to facilitate the use of a prosthetic hand to skilfully interact with objects.
In the first phase of the project, the student will undertake an observational study to determine what factors lead some individuals to become skilled with a prosthesis faster than others. We will test large numbers of intact (i.e., without amputation) participants learning to use a state-of-the-art myoelectric prosthetic arm simulator, which is controlled by muscle feedback but ergonomically designed to fit over the wrist of an intact hand. Participants will move objects of different of sizes and weights from one location to another with a range of precision requirements and in the presence of a range of obstacles. Over multiple sessions we will measure hand and object kinematics, fingertip forces, and eye path with a head-mounted eye tracker. We will then develop a data-driven mathematical model of the eye tracking and biomechanical performance data. Statistical analysis of the patterns of eye movement will provide new insights into the ‘signature’ of good performance using the prosthetic arm.
The second phase will use the data from Project 1 to develop a training protocol that will adopt the ‘expert signatures’ from Phase 1 as a prototype for a trainee to follow. We will focus predominantly on the signature of expertise derived from the gaze behaviour measures and implement a gaze training protocol. We will then test the efficacy of this novel training regime with new set of intact participants using the prosthetic simulator, tracking their performance in comparison to individuals who will receive a sham training protocol.
In the final phase of the project, the gaze training protocol will be used in a sample of upper-limb-amputees as they learn how to use their new prosthesis. As this stage of the project will not be limited to myoelectric prosthetic users, this will also allow us to test the generalizability of our training protocol.
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in applied mathematics, computer science, physics or engineering. Experience in biomedical engineering or robotics is desirable.
The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>.
Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options.
Application deadline: 10th January 2018
Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year.
Duration of award: per year
Contact: Doctoral College pgrenquiries at exeter.ac.uk<mailto:pgrenquiries at exeter.ac.uk>
How to apply
You will be required to upload the following documents:
• Letter of application outlining your academic interests, prior research experience and reasons for wishing to
undertake the project.
• Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim
transcript if you are still studying.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your current
proficiency in English. For further details of the University’s English language requirements please see
The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018.
If you have any general enquiries about the application process please email: pgrenquiries at exeter.ac.uk<mailto:pgrenquiries at exeter.ac.uk>.
Project-specific queries should be directed to the supervisor.
Professor of Mathematics for Healthcare
Department of Mathematics &
Living Systems Institute, T02.17
University of Exeter, Stocker Road, Exeter, EX4 4QD, UK
email: k.tsaneva-atanasova at exeter.ac.uk<mailto:k.tsaneva-atanasova at exeter.ac.uk>
tel: +44 (0) 1392 723615
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the Comp-neuro