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Measuring joint moments at high speed is integral for sports-related research, but substantial artefacts can arise with certain computational methods. This is relevant for BJSM readers as measurement errors can lead to flawed conclusions. Potential settings where errors have the potential to creep in include anterior cruciate ligament (ACL) risk factor studies, running biomechanics analysis and other fields where biomechanists study fast movements. Our recent paper in Journal of Biomechanics demonstrated the effect of different filtering of force and marker data in joint moment calculations.1 This paper explains those findings for the clinical readership of BJSM and highlights the areas where it may be wise to ‘proceed with caution’ when interpreting previous studies that aim to identify key risk factors for injury.
What is a joint moment and why should I care?
Estimates of joint moments are fundamental in the study of sporting motion. Joint moments calculated in standard motion analysis are net joint moments, the total effect of all structures that produce forces that work across the joint. Joint moments stem from muscle forces, articular contact and ligaments. We are interested in joint moments because, unlike these separate forces, they can be measured. A correct interpretation of joint moments may help us understand which muscles and ligaments are at risk of injury in certain settings.
What is all this noise about?
If biomechanics is not your thing, feel free to skip down to ‘Implications’ below. Joint moments are normally calculated through the process of inverse dynamics, where ground reaction forces (force plate data) and segment accelerations (marker data—the reflective markers attached to the participant) are combined.
In all high-impact movements, such as running and sidestep cutting, it is normal to see an impact peak in ground reaction force that will result in high acceleration of body segments. Unfortunately, due to random noise in the measurement of marker positions, current motion analysis systems cannot reliably …