Pre-planned Vs. Executed Real-Time Pacing Strategies during 3-km Race: Role of Rating Perceived Exertion

The interplay of fatigue dynamics and task achievement using optimal control predictive simulation

Predictive simulation of human motion could provide insight into optimal techniques. In repetitive or long-duration tasks, these simulations must predict fatigue-induced adaptation. However, most studies minimize cost function terms related to actuator activations, assuming it minimizes fatigue. An additional modeling layer is needed to consider the previous use of muscles to reveal adaptive strategies to the decreased force production capability. Here, we propose interfacing Xia's three-compartment fatigue dynamics model with rigid-body dynamics. A stabilization invariant was added to Xia's model. We simulated the maximum repetition of dumbbell biceps curls as an optimal control problem (OCP) using direct multiple shooting. We explored three cost functions (minimizing torque, fatigue, or both) and two OCP formulations (full-horizon and sliding-horizon approaches). We adapted Xia's model by adding a stabilization invariant coefficients S=105 for direct multiple shooting. Sliding-horizon OCPs achieved 20 to 21 repetitions. The kinematic strategy slowly deviated from a plausible dumbbell lifting task to a swinging strategy as fatigue onset increasingly compromised the humerus to remain vertical. In full-horizon OCPs, the latter kinematic strategy was used over the whole motion, resulting in 32 repetitions. We showed that sliding-horizon OCPs revealed a reactive strategy to fatigue when only torque was included in the cost function, whereas an anticipatory strategy was revealed when the fatigue term was included in the cost function. Overall, the proposed approach has the potential to be a valuable tool in optimizing performance and helping reduce fatigue-related injuries in a variety of fields.

Pacing Behaviour Development and Acquisition: A Systematic Review

BACKGROUND

The goal-directed decision-making process of effort distribution (i.e. pacing) allows individuals to efficiently use energy resources as well as to manage the impact of fatigue on performance during exercise. Given the shared characteristics between pacing behaviour and other skilled behaviour, it was hypothesized that pacing behaviour would adhere to the same processes associated with skill acquisition and development.

METHODS

PubMed, Web of Science and PsycINFO databases between January 1995 and January 2022 were searched for articles relating to the pacing behaviour of individuals (1) younger than 18 years of age, or (2) repeatedly performing the same exercise task, or (3) with different levels of experience.

RESULTS

The search resulted in 64 articles reporting on the effect of age (n = 33), repeated task exposure (n = 29) or differing levels of experience (n = 13) on pacing behaviour. Empirical evidence identifies the development of pacing behaviour starts during childhood (~ 10 years old) and continues throughout adolescence. This development is characterized by an increasingly better fit to the task demands, encompassing the task characteristics (e.g. duration) and environment factors (e.g. opponents). Gaining task experience leads to an increased capability to attain a predetermined pace and results in pacing behaviour that better fits task demands.

CONCLUSIONS

Similar to skilled behaviour, physical maturation and cognitive development likely drive the development of pacing behaviour. Pacing behaviour follows established processes of skill acquisition, as repeated task execution improves the match between stimuli (e.g. task demands and afferent signals) and actions (i.e. continuing, increasing or decreasing the exerted effort) with the resulting exercise task performance. Furthermore, with increased task experience attentional capacity is freed for secondary tasks (e.g. incorporating opponents) and the goal selection is changed from achieving task completion to optimizing task performance. As the development and acquisition of pacing resemble that of other skills, established concepts in the literature (e.g. intervention-induced variability and augmented feedback) could enrich pacing research and be the basis for practical applications in physical education, healthcare, and sports.

Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels

The purpose of this study was to investigate the multivariate profile of different types of Brazilian runners and to identify the discriminant pattern of the distinct types of runners, as a runners' ability to self-classify well. The sample comprised 1235 Brazilian runners of both sexes (492 women; 743 men), with a mean age of 37.94 ± 9.46 years. Individual characteristics were obtained through an online questionnaire: Sex, age, body height (m) and body mass (kg), socioeconomic status, and training information (i.e., self-classification, practice time, practice motivation, running pace, frequency and training volume/week). Multivariate analysis of variance was conducted by sex and the discriminant analysis was used to identify which among running pace, practice time, body mass index and volume/training could differentiate groups such as "professional athletes", "amateur athletes" and "recreational athletes". For both sexes, running pace was the variable that better discriminated the groups, followed by BMI and volume/week. The practice time is not a good indicator to differentiate runner's types. In both sexes, semi-professional runners were those that better self-classify themselves, with amateur runners presenting the highest classification error. This information can be used to guide the long-term training, athlete's selection programs, and to identify the strengths and weaknesses of athletes.