Non-invasive motion analysis of swimmers

This project will develop a camera-based tool to automatically track whole-body movements in sport. The tool will measure the complex movement patterns used by elite swimmers, without requiring markers or manual digitisation. The student will work alongside researchers from Manchester Metropolitan University, Sheffield Hallam University and British Para-swimming.
Project Aims and Objectives
Increasing participation in sport and physical activity is a key priority to improve the health and well-being of the nation. The performance of Great Britain’s teams at the 2012, and 2016 Olympic and Paralympic Games help inspire the population to become more active. The teams’ successes were underpinned by world-class coaching and world-leading research programmes. In many sports, research focused on characterising and optimising the athletes’ movement patterns and maximising benefits gained from their equipment. As well as having impact at an elite level, introducing improved training programs and better-designed equipment can also make sport more accessible to a wider population; for example, by making the sport easier to learn and reducing injury risks.
Motion analysis usually involves attaching markers or sensors to the athlete or equipment; however, putting them into position is time-consuming and they can change how the athlete would normally move. Therefore, a marker-free system is particularly desirable, especially when monitoring swimmers, as any attachments alter the flow of water around the athlete and increase drag. Robust marker-free techniques often apply a Visual Hull, which uses silhouettes from a number of cameras to represent a volume of interest. Swimming presents a particular challenge for constructing a Visual Hull of an athlete, due to: i) movements transitioning between water and air, ii) restricted camera positions, iii) water movement and, iv) low light levels.
The aim of this PhD is to develop Visual Hull techniques, in order to produce a non-invasive tool for biomechanical analysis of swimmers, with the following objectives:
1. To review current literature on swimming biomechanics, non-invasive motion analysis, image processing and Visual Hull construction.
2. To develop a robust tool, which automatically measures athlete movements in a laboratory.
3. To develop a robust tool, which automatically measures athlete movements in the Para-swimming National Performance Centre at the Manchester Aquatics Centre.
4. To develop a whole-body model to enable biomechanical data extraction from the tool.
5. To assess how the tool can be used to improve the performance of Olympic and Paralympic swimmers.
In the first year, the student will conduct a literature review, and then develop and validate a tool for measuring athlete movement in the laboratory. The second year will focus on further development and validation of the tool for measuring swimmer movements in the pool, including the development of a whole-body model that extracts biomechanical measurements. The final year will include applying the tool and assessing its impact on improving swimming performance.

The supervisory team for this project will be Dr Carl Payton, Dr Thomas Allen, Dr Heather Driscoll, and Dr Moi Hoon Yap

The closing date for applications is 31st January 2017.
To apply, please use the form on our web page: http://www2.mmu.ac.uk/study/postgraduate/apply/postgraduate-research-course/ - please note, CVs alone will not be accepted.

For informal enquiries, please contact: [Email Address Removed]
Please quote the Project Reference in all correspondence.