Introduction
Managing daily Neuromuscular fatigue in strength and conditioning can be paramount to the success of any program targeted at maximizing athletic performance and overall adaptation. As a human performance professional, there are a great deal of variables to consider and account for when aiming to optimize an athlete’s overall performance. Those variables tend to provide a delicate and ever-changing balance between the athlete participating in the sport, sport specific skill practice, strength and conditioning work, all in addition to daily life stressors. Not only this, but each athlete has a unique response to every stressor, thus making fatigue monitoring a relative necessity. With that, there are many methods that can be utilized to assess and monitor an athlete’s readiness and fatigue. While there are a vast number of ways to monitor athlete fatigue, a few that are very common within sports science are, but not limited to: neuromuscular fatigue monitoring (NMFM) thought force plate assessments, central nervous system readiness via direct current potential (DC Potential), as well as monitoring and tracking heart rate variability (HRV), resting heart rate (RHR), and recovery or readiness scores from various pieces of wearable technology (Casey et al., 2017; Coyne et al., 2020; Heishman et al., 2018, 2020; Merrigan et al., 2020). While each of these techniques have their respective place in sports science and athlete monitoring, the primary focus going forward will be on neuromuscular fatigue, what it means, how it can inform decision making, as well as how it can be applied by sports scientists and strength and conditioning professionals alike.
Background
Neuromuscular System
For a brief and extremely oversimplified review, while staying relevant to the topic at hand, the neuromuscular system is an intricate system within the human body, in which provides the connection of the brain and spinal cord (central nervous system, CNS) to both muscles, as well as the nerves that innervate them (peripheral nervous system, PNS) (Faude and Donath, 2019). Within the human performance realm, the neuromuscular system can be seen having an overabundance of functions, such as driving and controlling overall movement, coordinating central motor drive, reflex activity, excitation-contraction coupling within skeletal muscle, as well as providing both the coordination and integration of sensory feedback in the generation of movement (Faude & Donath, 2019). More specifically, a highly functioning neuromuscular system can facilitate adequate or enhanced levels of force production within a respective task, coordinate movements to protect bodily structures, as well as allow for the maintenance of stability by way of allowing for the human organism to maintain a stable posture in the presence of potential change (Faude & Donath, 2019). For the sake of brevity, understand that there are considerable layers of complexity and intricacy of the neuromuscular system, the likes of which this paper will not cover in its entirety.
Readiness and Fatigue
Continuing to delve deeper, understanding the meaning of both readiness and fatigue are vital to the application of NMFM. In this context, fatigue can be loosely defined as the reduction of an individual’s ability to produce force, and or perform work, thus resulting in a decrease in
performance (Heishman et al., 2018). To further expand the meaning of fatigue within human performance, low-frequency fatigue activities take center stage. When an athlete partakes in activities that involve high-intensity movements, repetitive eccentric movements of moderate-to high force, or motions that involve a repeated stretch-shortening cycle, there has been a reported potential decline in performance over time if fatigue is not identified, quantified, and addressed correctly (Heishman et al., 2018). If programmed incorrectly, these movements can accumulate throughout a day, week, or month, and the athlete will begin to show clear signs of fatigue, as higher intensity movements will drive high amounts of fatigue. The importance of this, as it relates to readiness and fatigue, is that within this context it provides a basic framework to understanding fatigue, and ultimately will provide insight as to how to establish athlete readiness within human performance.
As with every strength and conditioning program, the main goal is to provide a stimulus, then allow for adequate recovery, all in efforts to elicit adaptation, and a subsequent increase in performance (Gabbet, 2015; Heishman et al., 2018; McFarlane, 1985; Mooney et al., 2013). With this as the main goal, it is important to ensure that the athlete maintains the highest respective level of readiness to continue to participate in the daily training (Heishman et al., 2018; Watkins et al., 2017). Readiness has enumerable ways of being calculated, however, remaining with the topic of NMFM and readiness, one of the most common methods is through the counter movement jump (CMJ), which has been found to be both a valid and a reliable measure of neuromuscular fatigue, and overall athlete readiness (Alba-Jimenez et al., 2022; Claudino et al., 2016; Heishman et al., 2018, 2020; Merrigan et al., 2020; Watkins et al., 2017). In application with NMFM, through the CMJ, the human performance professional can gain insight into a quantitative analysis of both the readiness and recovery of the athlete, in addition to showcasing potential quantitative adaptations to the program (Heishman et al., 2018; Merrigan et al., 2020; Wu et al., 2019). Moreover, predictive models can be established with the CMJ, which can ultimately offer prospective insight into central and metabolic fatigue (Wu et al., 2019).
Monitoring
Neuromuscular Fatigue Applied
With the background and reasoning established to NMFM, administering the CMJ with various pieces of technology is a clear next step. A frequently utilized piece of sports science technology are force platforms, otherwise known as force plates / force decks (Alba-Jimenez et al., 2022; Heishman et al., 2020; Merrigan et al., 2020). Although they may not always be feasible, force plates can offer an extensive insight into the force and time characteristics of the athlete’s movement. For some, other pieces of technology like jump-apps, contact mats, and so forth, may present to be more feasible methods of tracking this over time. However, this paper will now aim to provide the human performance professional with a few examples of what to look for from their respective force platform software, in addition to what can be done with the given information.
As with most things within sports science, there are enumerable methods to come to the same relative conclusions, and broadly speaking, no one method is particularly more correct than the
other, when used correctly. Despite this, there are a few methods that are valid and reliable, and utilized by much of the field of human performance professionals who are tracking readiness, NMF, and performance overtime. Within the CMJ, depending on the application, there are an abundance of tracking methods. Commonly, when looking into human performance, the following metrics are often analyzed over time for NMFM and readiness: Jump Height, Reactive Strength Index Modified, Flight Time:Contraction Time, Concentric Rate of Force Development, Eccentric Rate of Force Development, Eccentric Duration, Force at Zero Velocity, Peak Landing Force, Peak Landing Force Asymmetry, as well as various other relevant metrics (Alba-Jimenez et al., 2022; Heishman et al., 2018, 2020; Merrigan et al., 2020; Watkins et al., 2017). While there are many ways to track CMJ metrics and fatigue, finding one that works best for one’s respective population is key to establishing standardization and norms to compare against. Once the metric(s) in which to track have been determined, then deciphering what they mean, and what to do with them is of clear importance. Following a consistent test protocol, such as providing the CMJ test prior to activity, and requiring the athlete to do 3-5 jumps within the test, can provide the human performance professional an overabundance of foundational data of which will assist in making an informed decision (Heishman et al., 2020; Wu et al., 2019).
For a practical example, suppose a facility or team comes to agreement that they will monitor neuromuscular fatigue through the CMJ, with 3 jumps per test, with hands on hips, and they determine that they want to examine metrics from the peak jump within each testing bout. So, over the long term, the team determines that they would like to track Jump Height (impulse momentum, in.), Reactive Strength Index Modified (jump height/time to takeoff), and Eccentric Duration (ms). From these metrics, Jump Height provides a peak height of the jump, showing the outcome of the athlete’s ability to absorb, redirect, and generate and exert maximal force and power output in a jumping pattern. Moreover, Reactive Strength Index Modified (RSI-Mod.) showcases a ratio between the athlete’s jump height, and their time to take off (Bishop et al., 2022). In other words, RSI-Mod. would show how high the athlete got in the air, compared to how quickly they were able to leave the ground from the point where they went into the braking phase and propulsive phase, from their unweighting phase of the CMJ, which in translation showcases their elastic and explosive capabilities to both quickly absorb and develop force. Eccentric Duration is a measure of the amount of time in which the athlete applies the metaphorical “brakes”, or how quickly they can slow themselves down, ultimately to redirect the force concentrically within the propulsive phase to jump vertically. In conjunction with one another, these respective portions of analysis in that of, Jump Height, Reactive Strength Index Modified, and Eccentric Duration can provide plenty of information for the performance professional to make data-informed decisions with.
With these metrics in place, the team can track them over time, and in this case, compare the athletes’ outcomes against their previous test trials. From there, the team can establish a criteria in which to make decisions. For instance, if an athlete’s eccentric duration is >20% of what their normal eccentric duration is, or over what their previous session was, which would be a clear indicator of neuromuscular fatigue, what decisions should the human performance team make based upon that? Context is key within these situations, as some human performance teams may choose to cut training that day, whereas others may choose to cut volume or intensity by a
predetermined percentage. In the end, establishing and following a standardized protocol with sound reasoning based on the presented data is a potential way to safeguard the athlete from potential injury, or at a minimum, ensure that they are in the best possible position to execute the plan of the day within training (Alba-Jimenez et al., 2022; Merrigan et al., 2020; Wu et al., 2019).
Conclusion
The neuromuscular system is an intricate and integral part of human movement, the likes of which can be examined within readiness and neuromuscular fatigue measures, such as the Counter Movement Jump. Upon completion of the Counter Movement Jump, with the assistance of proper technology, human performance teams can track and measure interindividual neuromuscular fatigue and readiness for daily tasks or activities. Establishing valid and reliable metrics that can be examined over time, along with instituting what the team is to do with the data once it is gathered, is paramount to the athlete’s success when measuring fatigue and readiness. In the end, neuromuscular fatigue monitoring and readiness tracking, through movements like the Counter Movement Jump, can provide human performance teams with plenty of information to make data driven decisions on go- or no-go criteria, should they so choose, for their athlete to not only adapt at the most effective rate, but also potentially contribute to injury prevention.
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