If you’re trying to track mechanical load, GPS systems won’t give you the whole picture
This article is a follow up to Why GPS systems may be miscalculating your athlete’s mechanical load – Part 1
GPS Limitations
Advances in Technology
This article is a follow up to Why GPS systems may be miscalculating your athlete’s mechanical load – Part 1
Training aims to induce physical adaptations for enhanced performance whilst reducing the risk of injury. However to increase endurance, speed, strength and/or power, a sufficient training stimulus is needed. But an excessive training load can put an individual at risk of injury. To prescribe adequate training loads for the desired adaptations, it is critical to have a thorough understanding of the relationship between the loads experienced by the body and the physical adaptations. GPS systems do not analyze this. Therefore, the physiological and biomechanical load-adaptation pathways could be evaluated separately [1]
Physiological loads can be defined as the biochemical stresses experienced by the cardiovascular system. Enough stimuli may lead to desired adaptations such as increased metabolic and/or cardiac efficiency, while an over or under load could cause energy depletion or cardiac atrophy. Examples of commonly used measures to assess the internal physiological loads include oxygen uptake (VO2), heart rate, blood lactate and/or self-reported ratings of perceived exertion (RPE). The external physiological loads, on the other hand, are commonly quantified by GPS-derived metrics such as the total distance covered or time at certain speed or acceleration thresholds. Although these variables may be used to quantify and evaluate the aerobic and metabolic demands of training, they do not describe the loads experienced by the musculoskeletal system [2].
Biomechanical loads can be defined as the forces and stresses (i.e. normalized, distributed force) acting on the various hard and soft tissues (e.g. muscles, tendons, bones, cartilage) of the body. The repetitive mechanical loading of subsequent training sessions causes tissue-damage, which is necessary for positive adaptations such as stiffer tendons or muscle hypertrophy. However, an accumulation of damage over time can progressively weaken the tissues and ultimately lead to failure of a particular structure (i.e. overuse injuries) [3]. In contrast to the physiological loads, the biomechanical demands of training have been historically difficult to measure in the field. This limits detailed descriptions of the biomechanical load-adaptation pathways. However, recent advances in technology such as small, synchronized inertial sensors are enabling scientists, practitioners, and coaches to accurately measure, and therefore manage, biomechanical load in the field. Scientists, once previously constrained to the lab, can now work alongside practitioners, coaches and athletes to measure, analyze, and action field-based insights. Performance, return to play programming and injury risk reduction can then be improved with this data. The tech is here but up until now, what’s been missing is aligning sensors, software, and science. We now have a way to directly link sensor data to known underlying biomechanical models, and then present it in a simple, actionable way to practitioners, coaches, and athletes.