Biomechanical and Biophysical Biomarkers of Musculoskeletal Injury: A Machine Learning Approach to Injury Prediction and Performance Enhancement
Abstract
Both researchers and practitioners regularly try to quantify load in the context of exposure to stressors that can have both positive andnegative consequences on individuals. Put simply, if the load experienced is sufficient enough to create a stimulus for adaptation, and an appropriaterecovery environment is provided, then the individual will respond is a positive way. However, if the load is too great and/or adequate recovery is notprovided then there will be deleterious consequences leading to injuries and/or decrements in performance. However, what determines load and howbest to measure it has yet to be adequately defined and researched; additionally, how males and females respond, whether it be differently or the same,is unknown. Much of what is available for measuring and quantifying this load has been learnt from the sporting environment, as such it is necessary toundertake a thorough investigation within a military setting to understand the physical and physiological load placed on military personnel in order todevelop a predictive algorithm that will inform about physical performance and musculoskeletal injury, and how males and females differ in theirresponses.Using current technologies, the quantification of load has largely been performed by measuring velocity and displacement of athletes usingGPS. In this sense external load has been defined as the velocity and displacement of the athlete, not by internal measures (Wallace, Slattery, andCoutts 2009). In a sporting setting external load can be influenced by coaching staff through the manipulation of training variables such as frequency,intensity, time, and type of training (Borresen and Lambert 2009; Halson 2014). However, these are gross measures of load and movement, that may ormay not be related to the biomechanics and physiology of a human. Additionally, since GPS in sports first became common, technologies have rapidlyadvanced that allow for more sophisticated measures that may more directly relate to mechanical and physiological load than GPS alone.Over the last number of years there has been a rapid advancement of IMU technology that may now allow for measurement of surrogateexternal mechanical loads experienced by the lower limb using easily deployable IMUs. Researchers have demonstrated that is possible to calculatevariables such as peak accelerations, impact attenuation, and loading rates while running, which can be used to predict risk of running injuries (Crowelland Davis 2011; Lucas-Cuevas et al. 2017; Milner et al. 2006); a similar approach may be possible during military activities. Gold standard measures ofexternal mechanical load at the lower limb are typically taken using laboratory techniques using force plates, instrumented treadmills, and threedimensionalkinematics (Beckham, Suchomel, and Mizuguchi 2014; Lakomy 1987).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2021
- Source ID
- N629092112015
Entities
People
- Timothy Doyle
Organizations
- Macquarie University
- Office of Naval Research
- United States Navy