Movement variability under fatigue, the heads of Easter Island, and our two tasks in life

📝 Weekly paper summary

Adaptation of lower limb movement patterns when maintaining performance in the presence of muscle fatigue (Mudie et al., 2016)

Category

Case report study (n=40)

Context

Movement variability is unavoidable due to the vast degrees of freedom available to performers. Although variability in outcomes is less desirable, variability between segments allows a performer to adapt their movement solutions to dynamic task, environment, and personal constraints.

There are currently conflicting findings in the literature regarding whether the magnitude of variability of segment coupling increases or decreases as fatigue progresses during repetitive tasks. The authors of this study proposed the following rationale for these conflicting findings (pg. 29):

"...the measure of variability being sensitive to either, differences in tasks between studies or changes in the performance output that would likely occur during a fatiguing task (Miller et al., 2008). Thus, performance output characteristics that modulate leg stiffness and were not reported in previous studies, such as stride length (Miller et al., 2008), force output (Samaan et al., 2015) or jump height (Dal Pupo et al., 2013), may have changed as fatigue increased and may have directly affected the measurement of coupling variability. Further, it is difficult to differentiate possible effects due to warm-up, motor learning during repetitive tasks or fatigue, when coupling variability was not measured regularly (Dal Pupo et al., 2013; Ferber & Pohl, 2011; Miller et al., 2008; Samaan et al., 2015) during a repetitive task."

Therefore, the main aim of this investigation was to delineate whether changes in movement variability may have been due to changes in task performance or due to other fatigue-related processes. The authors hypothesized that movement variability would increase as fatigue increased, presumably since they expected participants' to "tap into" more movement solutions when fatigued to maintain performance.

Correctness

One thing that stands out to me in this paper is that fatigue hasn't been operationalized very clearly in the introduction. More recently, authors have discussed the importance of clearly differentiating between perceived and objective fatiguability (e.g., Enoka et al., 2021; Skau et al., 2021). In this paper, the authors controlled for objective fatigability since they defined volitional exhaustion as the moment participants couldn't achieve the target single-leg hop height anymore. Therefore, this paper's operationalization of "volitional" failure may differ from that of other papers. This consideration will be necessary for interpreting the overarching literature when discussing how movement variability changes with different magnitudes of fatigue.

Another thing that's important to consider is that the filter cutoff frequencies selected in this investigation appear to be justified based on the decisions made from other papers rather than on the data the researchers collected themselves. Since the cutoff filter may impact measures of the magnitude of movement variability and the authors didn't justify the cutoff frequencies based on the data they collected, this may influence the interpretations drawn from the study.

Similar to the study I outlined in last week's newsletter, this work was published before the frequency artifacts from vector-coding variability measures were published. Therefore, we should also consider these findings in light of Stock et al.'s (2018) work.

Contributions

• During both the loading (landing - peak vGRF) and propulsive phase (peak vGRF - toe-off) of the hop, coupling variability significantly increased at the end of the trial relative to the beginning. In other words, people used more movement solutions, and thus presumably distributed the loading to muscles with relatively less fatigue, as muscular fatigue progresses to preserve performance output.
• Although I can't elaborate on all the papers here, it supports the general hypothesis that movement variability seems to initially increase with minor fatigue (i.e., up to, but not beyond, the point in which some global performance measure changes) as people "hunt" for more movement solutions. Once they become fatigued beyond this point, the pool of solutions decreases and movement variability reciprocally decreases. This potential general trend has potentially significant implications for the structure and implementation of training:

1. Perhaps inducing minor fatigue during training can potentiate increased movement variability and, thus, increase training transfer to novel contexts and constraints
2. Aiming to increase movement variability for (endurance) athletes or workers as an outcome from training may act as a "motor control" buffer (as opposed to typical physiological buffers) that prolongs performance during their activities
3. Pushing people "too far" (i.e., to the point in which some global performance measures decrease excessively) may narrow the solution pool too much such that transfer of training is impaired.

• task constraints (e.g., people performing repeated jumps submaximally versus maximally) will also likely dictate the response to movement variability following, and during, fatiguing tasks.

🧠 Fun fact of the week

The heads of easter island have torsos!

I find this hilarious for some reason and, by extension, a fun fact.

🎙 Podcast recommendation

Lex and Stephen's previous discussions were incredible, and I'm looking forward to this one!

🗣 Quote of the week

"You have two essential tasks in life: to be a good person and to puruse the occupation that you love. Everything else is a waste of energy and a squandering of your potential"

- Ryan Holiday, The Daily Stoic (pg. 324)