Available
Project number:
2025_50
Start date:
October 2025
Project themes:
Main supervisor:
Reader in Engineering
Co-supervisor:
Irene Di Giulio, Senior Lecturer in Anatomy and Biomechanics
Additional Information:
Exploiting Fabric-Based Sensor Technology for Human Activity Recognition in Healthcare
Human activity recognition (HAR) has become increasingly important in healthcare, with applications ranging from rehabilitation to prosthetic control and health monitoring. Traditional rigid-attached sensors have proven accurate, but often lack comfort for long-term use. Recent research shows that textile-based sensors, embedded into garments, not only offer comfort but can also outperform rigid sensors in terms of accuracy, especially in short time windows. This project builds on these findings to develop wearable solutions that monitor patient movement more effectively.
The key novelty of this project is its focus on fabric-attached sensors, which have demonstrated a surprising ability to achieve higher accuracy than rigid sensors due to their increased responsiveness. By integrating these sensors into clothing, healthcare applications can benefit from precise, long-term movement tracking without compromising comfort. This advancement has the potential to revolutionise healthcare monitoring, particularly in rehabilitation, prosthetics, and movement disorder treatment, where accurate real-time data is essential for personalised care, an especially important driver of inclusivity for those with body difference.
The project aims to design wearable garments with embedded textile-based sensors for healthcare use. It seeks to develop advanced machine learning models that leverage the enhanced accuracy of fabric sensors for activity recognition. The system will be tested in real-world healthcare settings, including rehabilitation centres, to assess its effectiveness. Ultimately, the goal is to create a wearable solution that improves patient outcomes by providing more precise, comfortable, and long-term monitoring of movement and physical activity.
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
