In order to have a successful training program it is important to balance between training stress and subsequent fatigue and adaptations (Kellmann, 2010). Understanding and monitoring fatigue is a key part of an effective training program and is essential in identifying athletic status and readiness for individuals or teams (Twist & Highton, 2013). In fact, monitoring fatigue can help improve the coach’s understanding of how the athlete is responding to training stimulus and avoid injuries or illness leading to decrements in performance and overtraining (Brink et al., 2010; Meeusen et al., 2013). Therefore, having a validated and sensitive monitoring tool that coaches can use pre and post training sessions to track changes in fatigue and provide immediate feedback to their athletes would be extremely useful (Gathercole, Sporer, Stellingwerff, & Sleivert, 2015). It would also be ideal if this tool was noninvasive and did not take a great deal of time from the athlete’s training schedule (Twist & Highton, 2013). The aim of this study is to develop a tool, based on the existing literature on the subject, that can be easily used by coaches to monitor fatigue, more specifically centrally driven fatigue.
Fatigue and The Peripheral and Central Nervous Systems
Human muscle fatigue is an integrated phenomenon with complex interactions controlled by two mechanisms: peripheral and central. Any of both can lead to a decrease in the maximum force generating capacity of the muscles, thus hindering athletic performance (Meeusen & Roelands, 2010; Kent-Braun, 1999). The type of exercise performed influences the development of and recovery from fatigue, with peripheral factors influencing early fatigue and central factors influencing nearer to the end of exercise fatigue and activity failure (Decorte, Lafaix, Millet, Wuyam, & Verges, 2012).
Peripheral muscle fatigue can be further defined as a transient decrease in the capacity of a muscle group for exercise, that occurs at or distal to the neuromuscular junction (Fernandez-Del-Olmo et al., 2013; Nicol, Avela, & Komi, 2012). Peripheral fatigue occurs within the motor units and is also described as local fatigue (Kent-Braun, 1999).
Central muscle fatigue is linked with changes to functions of the central nervous system (CNS) that may influence mood, perception of effort and tolerance to discomfort or pain (Meeusen, Watson, Hasegawa, Roelands, & Piacentini, 2006). Central fatigue refers to more proximal processes and is defined as the loss of neural drive from the brain and the impaired function of the CNS (Fernandez-Del-Olmo et al., 2013; Meeusen, Watson, Hasegawa, Roelands, & Piacentini, 2006). In central fatigue, there is a progressive exercise induced decline in muscle activation leading to deficit and failure of voluntarily activation of the muscle. This has been attributed to metabolic changes in the muscle that initiate afferent inputs and central drive impairment (Girard, Racinais, Micallef, & Millet, 2011; Decorte et al., 2012).
Central fatigue has been found to have a more profound impact on performance and it has been associated with overreaching and overtraining (Budgett, 1998). Overreaching and overtraining pose a significant problem for coaches and athletes because there are no clear guidelines for monitoring and detecting if the athlete is approaching levels of fatigue that may lead to any of both conditions (Coutts, Wallace, & Slattery, 2007). Overreaching is the accumulation of training and non-training stress that can result in a short-term decrement in performance. It can lead to changes in the physiological and psychological states of the athlete and normally requires a recovery period of several days or weeks (Coutts et al., 2007). Overtraining is a fatigue condition that causes decrements in performance and is linked to frequent infections and mood disturbances such as depression (Budgett, 1998). The symptoms usually occur during vigorous training or post competition despite adequate rest for up to two weeks (Budgett, 1998). To avoid overtraining and optimise performance in sports, it is important to understand stress and fatigue to effectively manage physical recovery (Kellmann & Klaus-Dietrich, 2000). A major aim of research on overtraining is to develop tools that can be used to monitor the athlete continuously during training, based on identified markers that sensitively predict symptoms of overtraining, so that coaches can modify volume if persistent negative symptoms occur (Kellmann & Klaus-Dietrich, 2000).
Coaches and researchers also have great interest in the effect of long-term centrally driven fatigue on athletic performance and on having tools to assess and monitor it before overreaching or, even worse, overtraining may occur (Mooney, Cormack, O’Brien, Morgan, & McGuigan, 2013). The ability to monitor fatigue is critical in understanding the relationship between training and performance and can provide coaches with important information when planning their athletes periodisation scheme and for quantifying their training load (Hellard et al., 2006; Foster et al., 2001).
There exist different ways of monitoring fatigue, including self-reported questionnaires, blood biochemical markers and neuromuscular performance tests (Twist & Highton, 2013). Self-reported questionnaires are one of the easiest and most commonly used methods by coaches (Taylor, Chapman, Cronin, Newton, & Gill, 2012). These have been shown to be sensitive to changes in load, but they are also prone to inaccuracies due to athletes over or under reporting their status (Kellmann, 2010). The advantage of self-reported questionnaires is rapid data collection that is available for analysis within short periods of time when compared to common physiological monitoring tools that may take hours to several days for feedback (Kellmann, 2010). Having said that, the subjective nature of these questionnaires casts a doubt on their accuracy since the athlete can miss-report their status due not only to physical fatigue but also to psychological factors (Twist & Highton, 2013).
Another method that can be used by coaches is based on blood markers (Coutts et al., 2007). These tests can provide a good understanding of the mechanisms of fatigue but are not a popular form of collecting data because they are costly, invasive and require long periods of time to process and obtain the results (Taylor et al., 2012). In fact, Coutts et al. (2007) found that changes in biochemical measures such as given by blood markers did not relate to the onset of overreaching or recovery, quite possibly due to infrequent testing. When there is not high enough sampling frequency, then it is not possible to provide a clear understating on how the athletes are reacting to stress and how they are adapting to training and competition (Coutts et al., 2007).
By monitoring the athlete regularly and having a higher frequency of data collection it would be easier for the coach to detect the changes the athlete is experiencing (Newton & Dugan, 2002). Monitoring and collecting data daily can help identify key data points to determine when an athlete status changes and the nature of the change. This is important and using tests such as blood markers does not meet such requirement (Brink, Nederhof, Visscher, Schmikli, & Lemmink, 2010).
Coaches can also use performance tests to monitor fatigue (Twist & Highton, 2013). Performance tests looking at heart rate or running velocity, for example, are great at assessing task specific fatigue and can be used in conjunction with blood markers to assess fatigue or when the athlete is returning from injury (Twist & Highton, 2013). The main drawback of using these tests is they are time consuming, can cause further fatigue and disrupt the athlete’s training program (Fry et al., 1993).
Finally, coaches can use neuromuscular performance tests such as counter movement jump (CMJ) or depth jump (DJ) to assess neuromuscular performance (Twist & Highton, 2013). These are simple measures of simulated performance or muscle function that are very practical and can actually be ideal monitoring tools (Gathercole et al., 2015). When compared to other indirect markers, measures of neuromuscular function involving jump tests and isokinetic dynamometry can monitor low frequency fatigue more effectively (Cormack, Newton, McGuigan, & Cormie, 2008).
Neuromuscular Performance Tests
Neural control components including peripheral and central, have an important role in muscle activation during jump tests (Nicol et al., 2012). Stretch shortening cycle (SSC) muscle action is vital to various forms of exercise since the neuromuscular system is loaded in a more complex way during SSC when compared to any isolated forms of muscle action (Lloyd, Oliver, Hughes, & Williams, 2011; Flanagan & Comyns, 2008). During the active braking phase of SSC, central neural pathways play a crucial role in controlling the impact of loads and type of stretch (Nicol et al., 2012). According to Cormack, Newton and McGuigan (2008), the SSC is useful in detecting neuromuscular fatigue due to the fact that, along with disturbances to the stretch reflex activation, the mechanical, metabolic and neural components are also taxed. Nicol et al. (2012) state that whenever there is reduction in neural drive, central fatigue exists regardless of what mechanism.
Importantly, SSC has been strongly linked to exercise fatigue and therefore, since the SSC is involved in the CMJ and DJ, these tests may provide a sensitive tool to detect changes in fatigue (Coutts et al., 2007). Moreover, jump tests such as CMJ and DJ are easy to use tools and cause minimal fatigue, in addition to being able to assess SSC capability of the muscles of lower limps (Newton & Dugan, 2002).
Contact mats can be used to assess jump performance and provide flight time, contact time and predicted jump height based on vertical displacement (Patterson & Caulfield, 2010). Contact mats are cost effective, have good interday reliability and can be easily incorporated into training practice as effective tools of muscle function. They are also easier to administer than force plates and can be used to measure reactive strength index (RSI) (Patterson & Caulfield, 2010). RSI, calculated by dividing vertical jump height by ground contact time during the rebound phase, (Flanagan, Ebben, & Jensen, 2008) can be used as a reliable measure of SSC function and the athletes ability to utilise the SSC to generate force (Lloyd et al., 2011; Ball & Zanetti, 2012). According to Feldmann, Weiss, Ferreira, Schilling and Hammond (2011), RSI measurement during DJ can be employed to monitor changes in both the acute and or chronic training status of athletes. It can also be used in performance assessment to monitor power development and predisposition to injury (Ball & Zanetti, 2012).
Additional Performance Tests
According to Johnston et al. (2013), when monitoring fatigue and recovery it is also important to assess upper body neuromuscular function. Measurements of upper body neuromuscular function are important for many sports as fatigue can be caused due to upper movements that involve throwing, pushing, pulling and grabbing actions (Twist & Highton, 2013).
Grip strength is used as a measure of the ability of the hand and fingers to generate muscle force (Mathiowetz et al., 1985). Grip strength is vital for many sports such as climbing, judo and racquet sports (Chang, Chou, Lin, Lin, & Wang, 2010). Grip strength is also widely used to assess the function of the arm and hand in rehabilitation settings and has been linked to isokinetic dynamometry strength levels of the shoulder stabilisers, so it may be reliably used to evaluate muscle fatigue (Twist & Highton, 2013).
According to Cormack, Newton, McGuigan, et al. (2008) it may be more advantageous for coaches to monitor performance using ratios rather than single measures. The authors found that during CMJ the [flight time] / [contact time] ratio proved more effective than flight time or contact time as measures of their own.
Another ratio that can be used to monitor fatigue, which assesses the SSC and upper body neuromuscular function, is [RSI] / [grip strength] ratio. Potentially, this ratio may be employed to provide a better understanding of how the athlete is being stressed and use the feedback to assess fatigue. The ratio can help the coach determine if the athlete is experiencing peripheral or central fatigue based on the idea that if both measures decrease this will lead to a lower ratio. Note that if both decrease, fatigue is more likely to be centrally driven whereas if only one measurement decreases then fatigue is more likely to be locally driven.
The use of [RSI] / [grip strength] ratio as a tool may provide the practicality and low physiological strain required for repeated tests of multiple athletes in short spaces of time, to give coaches valuable and immediate feedback (Gathercole et al., 2015).
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