Assessment of the Feasibility of Markerless Biomechanical Assessment to be Established as Tool for Profiling Injury Risk in Professional Football
Aim
Understand the validity, reliability, sensitivity and feasibility of a biomechanical injury risk screening protocol using markerless technology for use in professional football
Background
In developing any model to establish prediction of musculoskeletal injury risk, the way an individual moves and the internal forces which are applied to their anatomical structures because of these movements are likely to be a significant factor in understanding predisposition to injury. To accurately represent these biomechanical factors in any model these measurements must have scientific rigor, so that the level of systematic noise that is measurement error, can be distinguished real changes in the data, which might have significance in changing predisposition to injury. To understand both noise and real change in the data the validity, reliability and sensitivity of the testing protocol and tools needs to be established. Currently most biomechanical data collection is undertaken in laboratories and is reliant on very expensive, time consuming and fixed 3D motion capture system. MLA (icase PhD industrial partners) wish to work with partners in the football industry to move towards the use of the emergent markerless based technology, which allows for rapid high volume data collection. Prior to being able to introduce this technology the validity (against 3D motion capture) and reliability needs to be established. The icase project aims to establish the validity of markerless technology against 3D motion capture and its reliability when collecting biomechanical variables used by MLA in their footballer biomechanical assessment protocol.
Funding:
The project is an icase PhD funded by Machine Learning in Athletics (MLA)
Team
Dr Matias Yoma