In search of sports biomechanics' holy grail: Can athlete-specific optimum sports techniques be identified?

Proficiency Barrier in Track and Field: Adaptation and Generalization Processes

The literature on motor development and training assumes a hierarchy for learning skills-learning the "fundamentals"-that has yet to be empirically demonstrated. The present study addressed this issue by verifying (1) whether this strong hierarchy (i.e., the proficiency barrier) holds between three fundamental skills and three sport skills and (2) considering different transfer processes (generalization/adaptation) that would occur as a result of the existence of this strong hierarchy. Twenty-seven children/adolescents participated in performing the countermovement jump, standing long jump, leap, high jump, long jump, and hurdle transposition. We identified the proficiency barrier in two pairs of tasks (between the countermovement jump and high jump and between the standing long jump and long jump). Nonetheless, the transfer processes were not related to the proficiency barrier. We conclude that the proposed learning hierarchy holds for some tasks. The underlying reason for this is still unknown.

AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets

BACKGROUND

Optimal sports performance requires a balance between intensive training and adequate rest. IMUs provide objective, quantifiable data to analyze performance dynamics, despite the challenges in quantifying athlete training loads. The ability of AI to analyze complex datasets brings innovation to the monitoring and optimization of athlete training cycles. Traditional techniques rely on subjective assessments to prevent overtraining, which can lead to injury and underperformance. IMUs provide objective, quantitative data on athletes' physical status during action. AI and machine learning can turn these data into useful insights, enabling data-driven athlete performance management. With IMU-generated multivariate time series data, this paper uses AI to construct a robust model for predicting fatigue and stamina.

MATERIALS AND METHODS

IMUs linked to 19 athletes recorded triaxial acceleration, angular velocity, and magnetic orientation throughout repeated sessions. Standardized training included steady-pace runs and fatigue-inducing techniques. The raw time series data were used to train a supervised ML model based on frequency and time-domain characteristics. The performances of Random Forest, Gradient Boosting Machines, and LSTM networks were compared. A feedback loop adjusted the model in real time based on prediction error and bias estimation.

RESULTS

The AI model demonstrated high predictive accuracy for fatigue, showing significant correlations between predicted fatigue levels and observed declines in performance. Stamina predictions enabled individualized training adjustments that were in sync with athletes' physiological thresholds. Bias correction mechanisms proved effective in minimizing systematic prediction errors. Moreover, real-time adaptations of the model led to enhanced training periodization strategies, reducing the risk of overtraining and improving overall athletic performance.

CONCLUSIONS

In sports performance analytics, the AI-assisted model using IMU multivariate time series data is effective. Training can be tailored and constantly altered because the model accurately predicts fatigue and stamina. AI models can effectively forecast the beginning of weariness before any physical symptoms appear. This allows for timely interventions to prevent overtraining and potential accidents. The model shows an exceptional ability to customize training programs according to the physiological reactions of each athlete and enhance the overall training effectiveness. In addition, the study demonstrated the model's efficacy in real-time monitoring performance, improving the decision-making abilities of both coaches and athletes. The approach enables ongoing and thorough data analysis, supporting strategic planning for training and competition, resulting in optimized performance outcomes. These findings highlight the revolutionary capability of AI in sports science, offering a future where data-driven methods greatly enhance athlete training and performance management.

Fifty years of performance-related sports biomechanics research

Over the past fifty years there has been considerable development in motion analysis systems and in computer simulation modelling of sports movements while the relevance and importance of functional variability of sports technique has become increasingly recognised. Technical developments for experimental work have led to increased, and still increasing, subject numbers. Increased subjects per study give better statistical power, the ability to utilise different data analyses, and thus the determination of more subtle and nuanced factors. The overall number of studies has also increased massively. Most actions in sport can, and have, been studied at some level with even the more challenging ones, such as player on player impacts, having some developing research. Computer simulation models of sports movements have ranged from simple (one or two segment) models to very complex musculoskeletal models and have used parameters ranging from the generic to individual-specific. Simple models have given insights into the key mechanics of movement while individual-specific model optimisations have been used to improve athlete performance. Our depth of understanding of the mechanics of sports techniques has increased across a wide range of sports. In the future there is likely to be more development and use of markerless motion capture, individual-specific model parameters, and more consideration of motor control aspects in the analysis of sports technique.

Unexpected running perturbations: Reliability and validity of a treadmill running protocol with analysis of provoked reflex activity in the lower extremities

Introduction

Balance is vital for human health and experiments have been conducted to measure the mechanisms of postural control, for example studying reflex responses to simulated perturbations. Such studies are frequent in walking but less common in running, and an understanding of reflex responses to trip-like disturbances could enhance our understanding of human gait and improve approaches to training and rehabilitation. Therefore, the primary aim of this study was to investigate the technical validity and reliability of a treadmill running protocol with perturbations. A further exploratory aim was to evaluate the associated neuromuscular reflex responses to the perturbations, in the lower limbs.

Methods

Twelve healthy participants completed a running protocol (9 km/h) test-retest (2 weeks apart), whereby 30 unilateral perturbations were executed via the treadmill belts (presets:2.0 m/s amplitude;150 ms delay (post-heel contact);100ms duration). Validity of the perturbations was assessed via mean ± SD comparison, percentage error calculation between the preset and recorded perturbation characteristics (PE%), and coefficient of variation (CV%). Test-retest reliability (TRV%) and Bland-Altman analysis (BLA; bias ± 1.96 * SD) was calculated for reliability. To measure reflex activity, electromyography (EMG) was applied in both legs. EMG amplitudes (root mean square normalized to unperturbed strides) and latencies [ms] were analysed descriptively.

Results

Left-side perturbation amplitude was 1.9 ± 0.1 m/s, delay 105 ± 2 ms, and duration 78 ± 1 ms. Right-side perturbation amplitude was 1.9 ± 0.1 m/s, delay 118 ± 2 ms, duration 78 ± 1 ms. PE% ranged from 5–30% for the recorded perturbations. CV% of the perturbations ranged from 19.5–76.8%. TRV% for the perturbations was 6.4–16.6%. BLA for the left was amplitude: 0.0 ± 0.3m/s, delay: 0 ± 17 ms, duration: 2 ± 13 ms, and for the right was amplitude: 0.1 ± 0.7, delay: 4 ± 40 ms, duration: 1 ± 35 ms. EMG amplitudes ranged from 175 ± 141%–454 ± 359% in both limbs. Latencies were 109 ± 12–116 ± 23 ms in the tibialis anterior, and 128 ± 49-157 ± 20 ms in the biceps femoris.

Discussion

Generally, this study indicated sufficient validity and reliability of the current setup considering the technical challenges and limitations, although the reliability of the right-sided perturbations could be questioned. The protocol provoked reflex responses in the lower extremities, especially in the leading leg. Acute neuromusculoskeletal adjustments to the perturbations could be studied and compared in clinical and healthy running populations, and the protocol could be utilised to monitor chronic adaptations to interventions over time.

Biomechanics and lower limb function are altered in athletes and runners with achilles tendinopathy compared with healthy controls: A systematic review

Achilles tendinopathy (AT) is a debilitating injury in athletes, especially for those engaged in repetitive stretch-shortening cycle activities. Clinical risk factors are numerous, but it has been suggested that altered biomechanics might be associated with AT. No systematic review has been conducted investigating these biomechanical alterations in specifically athletic populations. Therefore, the aim of this systematic review was to compare the lower-limb biomechanics of athletes with AT to athletically matched asymptomatic controls. Databases were searched for relevant studies investigating biomechanics during gait activities and other motor tasks such as hopping, isolated strength tasks, and reflex responses. Inclusion criteria for studies were an AT diagnosis in at least one group, cross-sectional or prospective data, at least one outcome comparing biomechanical data between an AT and healthy group, and athletic populations. Studies were excluded if patients had Achilles tendon rupture/surgery, participants reported injuries other than AT, and when only within-subject data was available.. Effect sizes (Cohen's d) with 95% confidence intervals were calculated for relevant outcomes. The initial search yielded 4,442 studies. After screening, twenty studies (775 total participants) were synthesised, reporting on a wide range of biomechanical outcomes. Females were under-represented and patients in the AT group were three years older on average. Biomechanical alterations were identified in some studies during running, hopping, jumping, strength tasks and reflex activity. Equally, several biomechanical variables studied were not associated with AT in included studies, indicating a conflicting picture. Kinematics in AT patients appeared to be altered in the lower limb, potentially indicating a pattern of "medial collapse". Muscular activity of the calf and hips was different between groups, whereby AT patients exhibited greater calf electromyographic amplitudes despite lower plantar flexor strength. Overall, dynamic maximal strength of the plantar flexors, and isometric strength of the hips might be reduced in the AT group. This systematic review reports on several biomechanical alterations in athletes with AT. With further research, these factors could potentially form treatment targets for clinicians, although clinical approaches should take other contributing health factors into account. The studies included were of low quality, and currently no solid conclusions can be drawn.

The motor Wisdom of the Crowd

Wisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. Because of its enormous social potential, this effect has been thoroughly investigated, but predominantly on tasks that involve rational thinking (such as estimating a number). Here we tested this effect in the context of drawing geometrical shapes, which still enacts cognitive processes but mainly involves visuomotor control. We asked more than 700 school students to trace five patterns shown on a touchscreen and then aggregated their individual trajectories to improve the match with the original pattern. Our results show the characteristics of the strongest examples of Wisdom of the Crowd. First, the aggregate trajectory can be up to 5 times more accurate than the individual ones. Second, this great improvement requires aggregating trajectories from different individuals (rather than trials from the same individual). Third, the aggregate trajectory outperforms more than 99% of individual trajectories. Fourth, while older individuals outperform younger ones, a crowd of young individuals outperforms the average older one. These results demonstrate for the first time Wisdom of the Crowd in the realm of motor control, opening the door to further studies of human and also animal behavioural trajectories and their mechanistic underpinnings.

An ecological-dynamical approach to golf science: implications for swing biomechanics, club design and customisation, and coaching practice

It has previously been argued that science has only made a limited contribution to the sport of golf, particularly the human element. This lack of impact could, in part, be attributed to the absence of an appropriate theoretical framework in most empirical investigations of the golf swing. This position paper outlines an ecological-dynamical approach to golf science that is better able to capture the interactions among the many structural parts of a golfer, and the relations between a golfer, his or her equipment, and his or her surrounding environment than other theoretical approaches have hitherto. It is proposed that the conjoining of principles and concepts of ecological psychology and dynamical systems theory could make a significant contribution to the enhancement of knowledge and understanding of swing biomechanics, club design and customisation, and coaching practice. This approach could also provide a platform on which to integrate the various subdisciplines of sport and human movement science to gain a more holistic understanding of golf performance.

Predictive Value of Technical Throwing Skills on Nomination Status in Youth and Long-Term Career Attainment in Handball

BACKGROUND

Research on talent in sports aims to identify predictors of future performance. This study retrospectively investigated 1) relationships between young handball field players' technical throwing skills and (a) their potential nomination to youth national teams and (b) their long-term career attainment 10 years later, and 2) associations between nomination status and career attainment.

RESULTS

Results from retrospectively predicting nomination status and career attainment using logistic regression analyses show that technical throwing skills were partly able to explain players' nomination status (Nagelkerke R2: females 9.2%, males 13.1%) and career attainment (Nagelkerke R2: 9.8% for female players). Here, variables throwing velocity and time on exercise showed statistically significant effects. In addition, nomination status and career attainment were shown to be associated using chi-square tests (w of .37 and .23 for female and male players, respectively) and nomination status as a predictor increased the prediction of career attainment remarkably (Nagelkerke R2: females 20.3%, males 12.7%).

CONCLUSIONS

Given these results, basic technical throwing skills may serve rather as a prerequisite in this age group on national level, emphasizing its importance already on lower levels and in younger age groups. Furthermore, advantages from entering the national TID system early especially for females are discussed.

Explaining "What for" in Motion Analysis Research: A Proposal for a Counterfactual Framework That Is Slightly Different From the Theory of Causation

In motion analysis research, the methodology for estimating the physical processes of human movement is highly developed, but the methodology for interpreting such data is relatively undeveloped. One of the aims of this paper is to demonstrate the importance of developing a conceptual basis for interpreting data about the physical processes of body movement. In this conceptual study, one topic was discussed as a central question: what it means to answer the question what a certain movement technique is aimed for. We first introduced the distinction between explanations from the perspective of causes and explanations from the perspective of purposes as a mode of explaining events, and pointed out the importance of explanations from the perspective of purposes. We next argued that by taking the perspective of whether a given movement technique leads to a desired outcome in comparison to other movement techniques, we can expect to interpret what a given movement technique is for based on objectively observable information rather than the subjective intentions of the athlete. In addition, we discussed how the criterion movement patterns should be defined when assessing the fitness for purpose of a given movement technique in terms of its consequences. In this regard, our argument is that it is necessary to take into account that the exact same movement pattern cannot be performed every time, even for the same motor task, and that there are multiple options for how to define the set of possible movement patterns that can be performed. Our discussion reveals the peculiarity of grasping the meaning of movement techniques, and therefore suggests that there is a substantial need for motion analysis researchers to deepen their conceptual analysis to understand the nature of this issue.

Beyond animated skeletons: How can biomechanical feedback be used to enhance sports performance?

Biomechanical feedback technologies are becoming increasingly prevalent in elite athletic training environments but how the kinematic and kinetic data they produce can be best used to improve sports techniques and enhance sports performance is unclear. This paper draws on theoretical and empirical developments in the motor control, skill acquisition, and sports biomechanics literatures to offer practical guidance and strategic direction on this issue. It is argued that the information produced by biomechanical feedback technologies can only describe, with varying degrees of accuracy, what patterns of coordination and control are being adopted by the athlete but, crucially, it cannot prescribe how these patterns of coordination and control should be modified to enhance sports performance. As conventional statistical and theoretical modelling paradigms in applied sports biomechanics provide limited information about patterns of coordination and control, and do not permit the identification of athlete-specific optimum sports techniques, objective criteria on which to base technical modifications that will consistently lead to enhanced performance outcomes cannot reliably be established for individual athletes. Given these limitations, an alternative approach, which is harmonious with the tenets of dynamical systems theory and aligned with the pioneering insights of Bernstein (1967) on skill acquisition, is advocated. This approach involves using kinematic and kinetic data to channel the athlete's search towards their own unique 'optimum' pattern of coordination and control as they actively explore their perceptual-motor workspace during practice. This approach appears to be the most efficacious use of kinematic and kinetic data given current biomechanical knowledge about sports techniques and the apparent inability of existing biomechanical modelling approaches to accurately predict how technique changes will impact on performance outcomes for individual athletes.

The Q-Pass Index: A Multifactorial IMUs-Based Tool to Assess Passing Skills in Basketball

Despite being a key sport-specific characteristic in performance, there is no practical tool to assess the quality of the pass in basketball. The aim of this study is to develop a tool (the quality-pass index or Q-Pass) able to deliver a quantitative, practical measure of passing skills quality based on a combination of accuracy, execution time and pass pattern variability. Temporal, kinematics and performance parameters were analysed in five different types of passes (chest, bounce, crossover, between-the-leg and behind-the-back) using a field-based test, video cameras and body-worn inertial sensors (IMUs). Data from pass accuracy, time and angular velocity were collected and processed in a custom-built excel spreadsheet. The Q-pass index (0–100 score) resulted from the sum of the three factors. Data were collected from 16 young basketball players (age: 16 ± 2 years) with high (experienced) and low (novice) level of expertise. Reliability analyses found the Q-pass index as a reliable tool in both novice (CV from 4.3 to 9.3%) and experienced players (CV from 2.8 to 10.2%). Besides, important differences in the Q-pass index were found between players’ level (p < 0.05), with the experienced showing better scores in all passing situations: behind-the-back (ES = 1.91), bounce (ES = 0.82), between-the-legs (ES = 1.11), crossover (ES = 0.58) and chest (ES = 0.94). According to these findings, the Q-pass index was sensitive enough to identify the differences in passing skills between young players with different levels of expertise, providing a numbering score for each pass executed.

Assessing Technical Skills in Talented Youth Athletes: A Systematic Review

Background

Talent identification and development (TID) programs aim to identify players with the greatest potential for long-term success. Previous research suggests that the assessment of sport-specific technical skills is valuable for discriminating between more and less skilled individuals and/or for predicting future performance.

Objective

This review aims to provide an overview on both the instruments used to assess sport-specific technical skills and their discriminatory, explanatory and/or predictive findings in the context of TID.

Methods

Electronic searches were conducted in PubMed, Web of Knowledge, SPORTDiscus, SURF and Scopus (January 1990–October 2019). Search terms covered the areas of sport, technical skills assessment, performance, skill level and youth. In the end, 59 relevant studies were identified and evaluated.

Results

The results highlight the widespread and important role of technical skills in TID; almost all studies (93%) reported discriminatory, explanatory and/or predictive benefits for the assessment of sport-specific technical skills. Analyzing and categorizing the number of assessment methods applied in the studies (n = 69) according to their method type (‘technique-related’ or ‘outcome-related’ variables) and method set-up (‘experimental’ or ‘competition’ data acquisition environment) indicated a clear tendency towards ‘outcome-related’ (73%) and ‘experimental’ (75%) assessment methods. We also found a strong overrepresentation of studies assessing cross-sectional data (75%) in soccer (53%) in male samples (74% of studies reporting subjects’ sex) from European countries (64%).

Conclusions

On the one hand, our findings demonstrate the great capability of sport-specific technical skills assessments to discriminate different performance levels and predict future performance in TID activities. On the other hand, this review highlights the focus on ‘outcome-related’ and ‘experimental’ methods in specific populations and, consequently, the limited knowledge in other areas. Here, the application of ‘technique-related’ and ‘competition’ methods appears promising for adding new knowledge, especially in the light of technological advances.

A Review of Forward-Dynamics Simulation Models for Predicting Optimal Technique in Maximal Effort Sporting Movements

The identification of optimum technique for maximal effort sporting tasks is one of the greatest challenges within sports biomechanics. A theoretical approach using forward-dynamics simulation allows individual parameters to be systematically perturbed independently of potentially confounding variables. Each study typically follows a four-stage process of model construction, parameter determination, model evaluation, and model optimization. This review critically evaluates forward-dynamics simulation models of maximal effort sporting movements using a dynamical systems theory framework. Organismic, environmental, and task constraints applied within such models are critically evaluated, and recommendations are made regarding future directions and best practices. The incorporation of self-organizational processes representing movement variability and “intrinsic dynamics” remains limited. In the future, forward-dynamics simulation models predicting individual-specific optimal techniques of sporting movements may be used as indicative rather than prescriptive tools within a coaching framework to aid applied practice and understanding, although researchers and practitioners should continue to consider concerns resulting from dynamical systems theory regarding the complexity of models and particularly regarding self-organization processes.

Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine

The scientific and practical fields-especially high-performance sports-increasingly request a stronger focus be placed on individual athletes in human movement science research. Machine learning methods have shown efficacy in this context by identifying the unique movement patterns of individuals and distinguishing their intra-individual changes over time. The objective of this investigation is to analyze biomechanically described movement patterns during the fatigue-related accumulation process within a single training session of a high number of repeated executions of a ballistic sports movement-specifically, the frontal foot kick (mae-geri) in karate-in expert athletes. The two leading research questions presented for consideration are (1) Can characteristics of individual movement patterns be observed throughout the entire training session despite continuous changes, i.e., even as fatigue-related processes increase? and (2) How do intra-individual movement patterns change as fatigue-related processes increase throughout a training session? Sixteen expert karatekas performed 606 frontal foot kicks directed toward an imaginary target. The kicks were performed in nine sets at 80% (K-80) of the self-experienced maximal intensity. In addition, six kicks at maximal intensity (K-100) were performed after each of the nine sets. Between the sets, the participants took a 90-s break. Three-dimensional full-body kinematic data of all kicks were recorded with 10 infrared cameras. The normalized waveforms of nine upper- and lower-body joint angles were classified using a supervised machine learning method (support vector machine). The results of the classification revealed a disjunct distinction between the kinematic movement patterns of individual athletes. The identification of unique movement patterns of individual athletes was independent of the intensity and the degree of fatigue-related processes. In other words, even with the accumulation of fatigue-related processes, the unique movement patterns of an individual athlete can be clearly identified. During the training session, changes in intra-individual movement patterns could also be detected, indicating the occurrence of adaptations in individual movement patterns throughout the fatigue-related accumulation process. The results suggest that these adaptations can be modeled in terms of changes in patterns rather than increasing variance. Practical consequences are critically discussed.

Biomechanical determinants of placekicking success in professional Rugby Union players

The ability to score from placekicks discriminates winning from losing Rugby Union teams. We aimed to identify which biomechanical variables related to successful placekicking in professional Rugby Union players, and use self-organising maps (SOM) to determine whether meaningful sub-groups existed. Three professional placekickers performed 10 kicks outdoors. Placekicks were categorised into best, worst, and typical performances based on outcomes and coach and player perceptions. Seven 3D biomechanical variables consistently and meaningfully (moderate Cohen's effect size) discriminated best from worst placekicks in all players. The three-cluster solution from SOM on these seven variables highlighted differences between players rather than best, worst, and typical attempts. Within-clusters, however, the best and worst placekicks tended to be represented in separate map regions. The seven variables identified using standardised effect sizes can be useful for group-level coaching of placekicking skills in absence of individual data, and translated in an applied setting using verbal and visual cues to promote overall placekicking performance. However, players' idiosyncrasies formed the main SOM boundaries, indicating that optimising placekicking success would benefit from an individualised approach and numerous effective movement templates may exist.

Assessment of movement coordination strategies to inform health of movement and guide retraining interventions

INTRODUCTION

Exploring characteristics of human movement has long been the focus of clinicians and researchers. Changes in movement coordination strategies have been identified in the presence of pain highlighting the need for assessment in clinical practice. A major development in the understanding of movement related disorders is recognition of individual differences in presentation and consequently the need to tailor interventions based on assessment.

PURPOSE

The purpose of this masterclass is to build a rationale for the clinical assessment of movement coordination strategies, exploring loss of movement choices, coordination variability, and to present a clinical framework for individualised management, including the use of cognitive movement control tests and retraining interventions. An approach for the qualitative rating of movement coordination strategies is presented. A compromised movement system may be one characterised by a lack of ability to access motor abundance and display choice in the use of movement coordination strategies. The identification of lost movement choices revealed during the assessment of movement coordination strategies is proposed as a marker of movement health.

IMPLICATIONS FOR PRACTICE

The health of the movement system may be informed by the ability to display choice in movement coordination strategies. There is evidence that restoring these choices has clinical utility and an influence on pain and improved function. This approach seeks to provide individuals with more flexible problem solving, enabled through a movement system that is robust to each unique challenge of function. This assessment framework sits within a bigger clinical reasoning picture for sustained quality of life.