Available
Project number:
2025_51
Start date:
October 2025
Project themes:
Main supervisor:
Senior Lecturer
Co-supervisor:
Dr Letizia Gionfrida
Additional Information:
Computer vision-based control system for a novel of myoelectric prosthetic to improve reliability and user experience
Myoelectric controlled hand prosthetics are artificial hands controlled by electrical signals generated naturally by the muscles in a residual limb. These prosthetics play a pivotal role for users in their life, enabling them to do daily activities, as well as feeling accepted as part of society. However, there is a significantly high abandoned rate which is as high as 44% in some countries [1]. This demonstrates that currently available commercial prosthetics are not meeting user needs or expectations, despite recent technologic advances.
One significant factor in myoelectric prosthetics abandonment is the control system. It is not seen to be reliable and the hand grip selection as being a slow and complicated process [2]. Therefore, implementing a novel robust control system for hand control, based on a computer vision approach can address this issue.
The aim of this project is to develop a computer vision-based control system for a novel low-cost myoelectric prosthetic to provide improved capability and reliability in gripping objects, together with hand dexterity. A user centred design approach will be taken, ensuring users needs are addressed to maximise acceptance by the community, and improvements to the quality of life for users. Specific objectives include;
O1: Development of computer vision algorithm featuring object detection and grip mode classification, capable of real-time performance.
O2: Integration into the myoelectric prosthetic and combining with EMG actuation.
O3: Engaging with end users through testing, discussion and feedback sessions.
The projects deliverable will be a myoelectric prosthetic with integrated computer vision control approach.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at
