Ballet Movement Detection Feasibility for Overuse Injury Modelling within Royal Ballet School Training Programmes
PI: Chris Steer, St Mary’s University, Twickenham.
CoI’s: Charles Pedlar, St Mary’s University; Matthew Lamarque, Royal Ballet School, White Lodge; Niall MacSweeney, St Mary’s University and Royal Ballet School, White Lodge; Karen Sheriff, Royal Ballet School, White Lodge.
Project Overview: The Royal Ballet School (RBS) aims to nurture, train and educate the exceptional young dancers for the Royal Ballet companies and other leading UK and international companies. Its strong charitable focus on the development and holistic support of young talented dancers includes both pilates, strength and conditioning alongside formal classical ballet training. With the young student dancer’s musculoskeletal development and the rigorous training duration and intensity, the risk of serious injuries, particularly of the lower leg, is significant. Sadly, injuries, particularly of the mid-sole, can be career-ending and may also be permanent. The RBS has invested significantly in its Healthy Dancer Programme, providing nutrition, physio, strength and conditioning, and healthcare support to the student dancers and rehabilitation when needed. St Mary’s University, Twickenham, is supporting the School by providing analytical support and, in this project, we seek to prototype a sensor system and analysis that allows early detection of overuse injuries in ballet students, within the context of their training. The approach taken is to develop a large dataset that captures the subjects’ variability and the method’s uncertainties, which is then ultimately used to inform preventative action.