Automating Video-Based Two-Dimensional Motion Analysis in Sport? Implications for Gait Event Detection, Pose Estimation, and Performance Parameter Analysis.

BACKGROUND: Two-dimensional (2D) video is a common tool used during sports training and competition to analyze movement. In these videos, biomechanists determine key events, annotate joint centers, and calculate spatial, temporal, and kinematic parameters to provide performance reports to coaches and athletes. Automatic tools relying on computer vision and artificial intelligence methods hold promise to reduce the need for time-consuming manual methods. OBJECTIVE: This study systematically analyzed the steps required to automate the video analysis workflow by investigating the applicability of a threshold-based event detection algorithm developed for 3D marker trajectories to 2D video data at four sampling rates; the agreement of 2D keypoints estimated by an off-the-shelf pose estimation model compared with gold-standard 3D marker trajectories projected to camera's field of view; and the influence of an offset in event detection on contact time and the sagittal knee joint angle at the key critical events of touch down and foot flat. METHODS: Repeated measures limits of agreement were used to compare parameters determined by markerless and marker-based motion capture. RESULTS: Results highlighted that a minimum video sampling rate of 100 Hz is required to detect key events, and the limited applicability of 3D marker trajectory-based event detection algorithms when using 2D video. Although detected keypoints showed good agreement with the gold-standard, misidentification of key events-such as touch down by 20 ms resulted in knee compression angle differences of up to 20°. CONCLUSION: These findings emphasize the need for de novo accurate key event detection algorithms to automate 2D video analysis pipelines.

Optimal fibre length and maximum isometric force are the most influential parameters when modelling muscular adaptations to unloading using Hill-type muscle models.

Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

A novel computational framework for the estimation of internal musculoskeletal loading and muscle adaptation in hypogravity.

Introduction: Spaceflight is associated with substantial and variable musculoskeletal (MSK) adaptations. Characterisation of muscle and joint loading profiles can provide key information to better align exercise prescription to astronaut MSK adaptations upon return-to-Earth. A case-study is presented of single-leg hopping in hypogravity to demonstrate the additional benefit computational MSK modelling has when estimating lower-limb MSK loading. Methods: A single male participant performed single-leg vertical hopping whilst attached to a body weight support system to replicate five gravity conditions (0.17, 0.25, 0.37, 0.50, 1 g). Experimental joint kinematics, joint kinetics and ground reaction forces were tracked in a data-tracking direct collocation simulation framework. Ground reaction forces, sagittal plane hip, knee and ankle net joint moments, quadriceps muscle forces (Rectus Femoris and three Vasti muscles), and hip, knee and ankle joint reaction forces were extracted for analysis. Estimated quadriceps muscle forces were input into a muscle adaptation model to predict a meaningful increase in muscle cross-sectional area, defined in (DeFreitas et al., 2011). Results: Two distinct strategies were observed to cope with the increase in ground reaction forces as gravity increased. Hypogravity was associated with an ankle dominant strategy with increased range of motion and net plantarflexor moment that was not seen at the hip or knee, and the Rectus Femoris being the primary contributor to quadriceps muscle force. At 1 g, all three joints had increased range of motion and net extensor moments relative to 0.50 g, with the Vasti muscles becoming the main muscles contributing to quadriceps muscle force. Additionally, hip joint reaction force did not increase substantially as gravity increased, whereas the other two joints increased monotonically with gravity. The predicted volume of exercise needed to counteract muscle adaptations decreased substantially with gravity. Despite the ankle dominant strategy in hypogravity, the loading on the knee muscles and joint also increased, demonstrating this provided more information about MSK loading. Discussion: This approach, supplemented with muscle-adaptation models, can be used to compare MSK loading between exercises to enhance astronaut exercise prescription.

Examination of 2D frontal and sagittal markerless motion capture: Implications for markerless applications.

This study examined if occluded joint locations, obtained from 2D markerless motion capture (single camera view), produced 2D joint angles with reduced agreement compared to visible joints, and if 2D frontal plane joint angles were usable for practical applications. Fifteen healthy participants performed over-ground walking whilst recorded by fifteen marker-based cameras and two machine vision cameras (frontal and sagittal plane). Repeated measures Bland-Altman analysis illustrated that markerless standard deviation of bias and limits of agreement for the occluded-side hip and knee joint angles in the sagittal plane were double that of the camera-side (visible) hip and knee. Camera-side sagittal plane knee and hip angles were near or within marker-based error values previously observed. While frontal plane limits of agreement accounted for 35-46% of total range of motion at the hip and knee, Bland-Altman bias and limits of agreement (-4.6-1.6 ± 3.7-4.2˚) were actually similar to previously reported marker-based error values. This was not true for the ankle, where the limits of agreement (± 12˚) were still too high for practical applications. Our results add to previous literature, highlighting shortcomings of current pose estimation algorithms and labelled datasets. As such, this paper finishes by reviewing methods for creating anatomically accurate markerless training data using marker-based motion capture data.

Public attitudes towards the use of novel technologies in their future healthcare: a UK survey.

BACKGROUND: Innovation in healthcare technologies can result in more convenient and effective treatment that is less costly, but a persistent challenge to widespread adoption in health and social care is end user acceptability. The purpose of this study was to capture UK public opinions and attitudes to novel healthcare technologies (NHTs), and to better understand the factors that contribute to acceptance and future use. METHODS: An online survey was distributed to the UK public between April and May 2020. Respondents received brief information about four novel healthcare technologies (NHTs) in development: a laser-based tool for early diagnosis of osteoarthritis, a virtual reality tool to support diabetes self-management, a non-invasive continuous glucose monitor using microwave signals, a mobile app for patient reported monitoring of rheumatoid arthritis. They were queried on their general familiarity and attitudes to technology, and their willingness to accept each NHT in their future care. Responses were analysed using summary statistics and content analysis. RESULTS: Knowledge about NHTs was diverse, with respondents being more aware about the health applications of mobile apps (66%), followed by laser-based technology (63.8%), microwave signalling (28%), and virtual reality (18.3%). Increasing age and the presence of a self-reported medical condition favoured acceptability for some NHTs, whereas self-reported understanding of how the NHT works resulted in elevated acceptance scores across all NHTs presented. Common contributors to hesitancy were safety and risks from use. Respondents wanted more information and evidence to help inform their decisions, ideally provided verbally by a general practitioner or health professional. Other concerns, such as privacy, were NHT-specific but equally important in decision-making. CONCLUSIONS: Early insight into the knowledge and preconceptions of the public about NHTs in development can assist their design and prospectively mitigate obstacles to acceptance and adoption.

Movement in low gravity environments (MoLo) programme-The MoLo-L.O.O.P. study protocol.

BACKGROUND: Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity. OBJECTIVES: The aim of this paper is to define an experimental protocol and methodology suitable to estimate in high-fidelity hypogravity conditions the lower limb internal joint reaction forces. State-of-the-art movement kinetics, kinematics, muscle activation and muscle-tendon unit behaviour during locomotor and plyometric movements will be collected and used as inputs (Objective 1), with musculoskeletal modelling and an optimisation framework used to estimate lower limb internal joint loading (Objective 2). METHODS: Twenty-six healthy participants will be recruited for this cross-sectional study. Participants will walk, skip and run, at speeds ranging between 0.56-3.6 m/s, and perform plyometric movement trials at each gravity level (1, 0.7, 0.5, 0.38, 0.27 and 0.16g) in a randomized order. Through the collection of state-of-the-art kinetics, kinematics, muscle activation and muscle-tendon behaviour, a musculoskeletal modelling framework will be used to estimate lower limb joint reaction forces via tracking simulations. CONCLUSION: The results of this study will provide first estimations of internal musculoskeletal loads associated with human movement performed in a range of hypogravity levels. Thus, our unique data will be a key step towards modelling the musculoskeletal deconditioning associated with long term habitation on the Lunar surface, and thereby aiding the design of Lunar exercise countermeasures and mitigation strategies.

The development and evaluation of a fully automated markerless motion capture workflow.

This study presented a fully automated deep learning based markerless motion capture workflow and evaluated its performance against marker-based motion capture during overground running, walking and counter movement jumping. Multi-view high speed (200 Hz) image data were collected concurrently with marker-based motion capture (criterion data), permitting a direct comparison between methods. Lower limb kinematic data for 15 participants were computed using 2D pose estimation, our 3D fusion process and OpenSim based inverse kinematics modelling. Results demonstrated high levels of agreement for lower limb joint angles, with mean differences ranging "0.1° - 10.5° for hip (3 DoF) joint rotations, and 0.7° - 3.9° for knee (1 DoF) and ankle (2 DoF) rotations. These differences generally fall within the documented uncertainties of marker-based motion capture, suggesting that our markerless approach could be used for appropriate biomechanics applications. We used an open-source, modular and customisable workflow, allowing for integration with other popular biomechanics tools such as OpenSim. By developing open-source tools, we hope to facilitate the democratisation of markerless motion capture technology and encourage the transparent development of markerless methods. This presents exciting opportunities for biomechanics researchers and practitioners to capture large amounts of high quality, ecologically valid data both in the laboratory and in the wild.

Modifications to the net knee moments lead to the greatest improvements in accelerative sprinting performance: a predictive simulation study.

The current body of sprinting biomechanics literature together with the front-side mechanics coaching framework provide various technique recommendations for improving performance. However, few studies have attempted to systematically explore technique modifications from a performance enhancement perspective. The aims of this investigation were therefore to explore how hypothetical technique modifications affect accelerative sprinting performance and assess whether the hypothetical modifications support the front-side mechanics coaching framework. A three-dimensional musculoskeletal model scaled to an international male sprinter was used in combination with direct collocation optimal control to perform (data-tracking and predictive) simulations of the preliminary steps of accelerative sprinting. The predictive simulations differed in the net joint moments that were left 'free' to change. It was found that the 'knee-free' and 'knee-hip-free' simulations resulted in the greatest performance improvements (13.8% and 21.9%, respectively), due to a greater knee flexor moment around touchdown (e.g., 141.2 vs. 70.5 Nm) and a delayed and greater knee extensor moment during stance (e.g., 188.5 vs. 137.5 Nm). Lastly, the predictive simulations which led to the greatest improvements were also found to not exhibit clear and noticeable front-side mechanics technique, thus the underpinning principles of the coaching framework may not be the only key aspect governing accelerative sprinting.

Performance and Micro-Pacing Strategies in a Freestyle Cross-Country Skiing Distance Race.

This study examined the micro-pacing strategies during a distance freestyle cross-country (XC) skiing competition. Nine female and 10 male highly trained XC skiers wore a GNSS device during a FIS-sanctioned race. The course was ~4900 m; women completed two-laps; men completed three-laps. The course was divided into uphill (S1, S3, S5, S7), downhill (S2, S4, S6, S8), and flat (S9) sections for analyses. Statistical parametric mapping was used to determine the course positions (clusters) where total race time or section time was significantly associated with instantaneous skiing speed. Total race time was associated with instantaneous skiing speed during a cluster in S1 on lap 2 for both sexes (t ≥ 5.899, p ≤ 0.008). The two longest uphill sections (S1; S5) and the flat section (S9) contained clusters where section times were related to instantaneous skiing speed for both sexes (p < 0.05). The fastest woman gained 6.9 s on the slowest woman during a cluster in S1 on lap 1 and 7.3 s during a cluster in S9 on lap 1. The fastest man gained 51.7 s on the slowest man over all clusters in S5 over the 3 laps combined. Compared to skiers with longer total race times, skiers with shorter race times skied with faster instantaneous speeds in some clusters of the uphill sections, as well as on the flat section of the course. This study also identified different relative micro-pacing strategies for women and men during freestyle distance XC skiing races. Finally, statistical parametric mapping analyses can help to identify individual strengths and weaknesses for guiding training programs and optimise competition pacing strategies.

Association between biological maturation and anterior cruciate ligament injury risk factors during cutting.

BACKGROUND: Adolescent females are particularly susceptible to suffering anterior cruciate ligament (ACL) injuries, likely influenced by well-established maturational changes. This study investigated ACL biomechanical injury risk factors and their association with biological maturation in females. METHODS: Thirty-five adolescent females (15±1 year) completed a series of maximum-effort 90° unanticipated cutting maneuvers. Established biomechanical ACL injury risk factors (including external knee abduction moments, knee abduction, hip abduction, knee flexion, ground reaction force) were derived from an optoelectronic motion analysis system and force platforms, with inter-limb asymmetries in these risk factors also computed. Biological maturation (percentage of predicted adult stature) was assessed using validated regression equations, incorporating anthropometric measures of participants and their biological parents. RESULTS: Significant bilateral asymmetries were observed with higher peak external knee abduction moments, higher ground reaction forces and less knee flexion (from 0-18% and 30-39% of contact) during the non-dominant vs. dominant cuts (effect sizes =0.36, 0.63 and 0.50, respectively). Maturation did not appear to influence these asymmetries; however, less hip abduction was observed (e.g., 21-51% of contact for dominant cuts) in more biologically-mature females. CONCLUSIONS: These results highlight a potential maturation-related change in cutting technique that may explain the apparent heightened ACL injury risk in this population. As females mature, training targeted at neuromuscular control of hip abductor (e.g. gluteal) muscle groups could potentially mitigate ACL injury risk.

Can We Modify Maximal Speed Running Posture? Implications for Performance and Hamstring Injury Management.

PURPOSE: Sprint kinematics have been linked to hamstring injury and performance. This study aimed to examine if a specific 6-week multimodal intervention, combining lumbopelvic control and unning technique exercises, induced changes in pelvis and lower-limb kinematics at maximal speed and improved sprint performance. METHODS: Healthy amateur athletes were assigned to a control or intervention group (IG). A sprint test with 3-dimensional kinematic measurements was performed before (PRE) and after (POST) 6 weeks of training. The IG program included 3 weekly sessions integrating coaching, strength and conditioning, and physical therapy approaches (eg, manual therapy, mobility, lumbopelvic control, strength and sprint "front-side mechanics"-oriented drills). RESULTS: Analyses of variance showed no between-group differences at PRE. At POST, intragroup analyses showed PRE-POST differences for the pelvic (sagittal and frontal planes) and thigh kinematics and improved sprint performance (split times) for the IG only. Specifically, IG showed (1) a lower anterior pelvic tilt during the late swing phase, (2) greater pelvic obliquity on the free-leg side during the early swing phase, (3) higher vertical position of the front-leg knee, (4) an increase in thigh angular velocity and thigh retraction velocity, (5) lower between-knees distance at initial contact, and (6) a shorter ground contact duration. The intergroup analysis revealed disparate effects (possibly to very likely) in the most relevant variables investigated. CONCLUSION: The 6-week multimodal training program induced clear pelvic and lower-limb kinematic changes during maximal speed sprinting. These alterations may collectively be associated with reduced risk of muscle strain and were concomitant with significant sprint performance improvement.

Development, evaluation and application of a novel markerless motion analysis system to understand push-start technique in elite skeleton athletes.

This study describes the development, evaluation and application of a computer vision and deep learning system capable of capturing sprinting and skeleton push start step characteristics and mass centre velocities (sled and athlete). Movement data were captured concurrently by a marker-based motion capture system and a custom markerless system. High levels of agreement were found between systems, particularly for spatial based variables (step length error 0.001 ± 0.012 m) while errors for temporal variables (ground contact time and flight time) were on average within ± 1.5 frames of the criterion measures. Comparisons of sprinting and pushing revealed decreased mass centre velocities as a result of pushing the sled but step characteristics were comparable to sprinting when aligned as a function of step velocity. There were large asymmetries between the inside and outside leg during pushing (e.g. 0.22 m mean step length asymmetry) which were not present during sprinting (0.01 m step length asymmetry). The observed asymmetries suggested that force production capabilities during ground contact were compromised for the outside leg. The computer vision based methods tested in this research provide a viable alternative to marker-based motion capture systems. Furthermore, they can be deployed into challenging, real world environments to non-invasively capture data where traditional approaches are infeasible.

The accuracy of several pose estimation methods for 3D joint centre localisation.

Human movement researchers are often restricted to laboratory environments and data capture techniques that are time and/or resource intensive. Markerless pose estimation algorithms show great potential to facilitate large scale movement studies 'in the wild', i.e., outside of the constraints imposed by marker-based motion capture. However, the accuracy of such algorithms has not yet been fully evaluated. We computed 3D joint centre locations using several pre-trained deep-learning based pose estimation methods (OpenPose, AlphaPose, DeepLabCut) and compared to marker-based motion capture. Participants performed walking, running and jumping activities while marker-based motion capture data and multi-camera high speed images (200 Hz) were captured. The pose estimation algorithms were applied to 2D image data and 3D joint centre locations were reconstructed. Pose estimation derived joint centres demonstrated systematic differences at the hip and knee (~ 30-50 mm), most likely due to mislabeling of ground truth data in the training datasets. Where systematic differences were lower, e.g., the ankle, differences of 1-15 mm were observed depending on the activity. Markerless motion capture represents a highly promising emerging technology that could free movement scientists from laboratory environments but 3D joint centre locations are not yet consistently comparable to marker-based motion capture.

Ratio of forces during sprint acceleration: A comparison of different calculation methods.

The orientation of the ground reaction force (GRF) vector is a key determinant of human sprint acceleration performance and has been described using ratio of forces (RF) which quantifies the ratio of the antero-posterior component to the resultant GRF. Different methods have previously been used to calculate step-averaged RF, and this study therefore aimed to compare the effects of three calculation methods on two key "technical" ability measures: decline in ratio of forces (DRF) and theoretical maximal RF at null velocity (RF0). Twenty-four male sprinters completed maximal effort 60 m sprints from block and standing starts on a fully instrumented track (force platforms in series). RF-horizontal velocity profiles were determined from the measured GRFs over the entire acceleration phase using three different calculation methods for obtaining an RF value for each step: A) the mean of instantaneous RF during stance, B) the step-averaged antero-posterior component divided by the step-averaged resultant GRF, C) the step-averaged antero-posterior component divided by the resultant of the step-averaged antero-posterior and vertical components. Method A led to significantly greater RF0 and shallower DRF slopes than Methods B and C. These differences were very large (Effect size Cohen's d = 2.06 - 4.04) and varied between individuals due to differences in the GRF profiles, particularly during late stance as the acceleration phase progressed. Method B provides RF values which most closely approximate the mechanical reality of step averaged accelerations progressively approaching zero and it is recommended for future analyses although it should be considered a ratio of impulses.

Can Markerless Pose Estimation Algorithms Estimate 3D Mass Centre Positions and Velocities during Linear Sprinting Activities?

The ability to accurately and non-invasively measure 3D mass centre positions and their derivatives can provide rich insight into the physical demands of sports training and competition. This study examines a method for non-invasively measuring mass centre velocities using markerless human pose estimation and Kalman smoothing. Marker (Qualysis) and markerless (OpenPose) motion capture data were captured synchronously for sprinting and skeleton push starts. Mass centre positions and velocities derived from raw markerless pose estimation data contained large errors for both sprinting and skeleton pushing (mean ± SD = 0.127 ± 0.943 and -0.197 ± 1.549 m·s-1, respectively). Signal processing methods such as Kalman smoothing substantially reduced the mean error (±SD) in horizontal mass centre velocities (0.041 ± 0.257 m·s-1) during sprinting but the precision remained poor. Applying pose estimation to activities which exhibit unusual body poses (e.g., skeleton pushing) appears to elicit more erroneous results due to poor performance of the pose estimation algorithm. Researchers and practitioners should apply these methods with caution to activities beyond sprinting as pose estimation algorithms may not generalise well to the activity of interest. Retraining the model using activity specific data to produce more specialised networks is therefore recommended.

Three-dimensional data-tracking simulations of sprinting using a direct collocation optimal control approach.

Biomechanical simulation and modelling approaches have the possibility to make a meaningful impact within applied sports settings, such as sprinting. However, for this to be realised, such approaches must first undergo a thorough quantitative evaluation against experimental data. We developed a musculoskeletal modelling and simulation framework for sprinting, with the objective to evaluate its ability to reproduce experimental kinematics and kinetics data for different sprinting phases. This was achieved by performing a series of data-tracking calibration (individual and simultaneous) and validation simulations, that also featured the generation of dynamically consistent simulated outputs and the determination of foot-ground contact model parameters. The simulated values from the calibration simulations were found to be in close agreement with the corresponding experimental data, particularly for the kinematics (average root mean squared differences (RMSDs) less than 1.0° and 0.2 cm for the rotational and translational kinematics, respectively) and ground reaction force (highest average percentage RMSD of 8.1%). Minimal differences in tracking performance were observed when concurrently determining the foot-ground contact model parameters from each of the individual or simultaneous calibration simulations. The validation simulation yielded results that were comparable (RMSDs less than 1.0° and 0.3 cm for the rotational and translational kinematics, respectively) to those obtained from the calibration simulations. This study demonstrated the suitability of the proposed framework for performing future predictive simulations of sprinting, and gives confidence in its use to assess the cause-effect relationships of technique modification in relation to performance. Furthermore, this is the first study to provide dynamically consistent three-dimensional muscle-driven simulations of sprinting across different phases.

Part 2 of the 11+ as an effective home-based exercise programme in elite academy football (soccer) players: a one-club matched-paired randomised controlled trial.

Background:Although the 11+ is known to reduce injuries and improve performance in adolescent footballers, its duration presents a notable barrier to implementation. Hence, this study investigated injury and performance outcomes when 65 elite male academy footballers either performed Part 2 3x/week at training (TG) or at home (HG).Methods:Time to stabilisation (TTS), eccentric hamstring strength (EH-S) and countermovement jump height (CMJ-H) were collected 4 times during the 2019 football season. Linear mixed models were used to evaluate main and interaction effects of group and time. Bonferroni post-hoc tests were used to account for multiple comparisons. Differences in time loss and medical attention injuries were determined using a two-tailed Z test for a comparison of rates.Results:Relative to baseline, EH-S (HG 4.3 kg, 95% CI 3 to 5.7, p < 0.001; TG 5.5 kg, 95% CI 4.3 to 6.6, p < 0.001) and CMJ-H (HG 3.5 cm, 95% CI 2.2 to 4.7, p < 0.001; TG 3.2 cm, 95% CI 2.2 to 4.3, p < 0.001) increased, with no difference between groups observed at the end of the season. All injury outcomes were similar.Conclusion: Rescheduling Part 2 did not affect performance or increased injury risks in academy footballers.

Performance and Micro-Pacing Strategies in a Classic Cross-Country Skiing Sprint Race.

The purpose of the present study was to analyze micro-pacing strategies in cross-country skiing, and their relation to section and total race times. Eleven competitive female cross-country skiers were tracked during a classic sprint time-trial race using a global navigation satellite system (GNSS) unit. A coordinate mapping procedure was applied to the GNSS unit measurements to analyze the instantaneous velocities and split times. The track was divided into nine sections and individual section times were calculated. Statistical parametric mapping (SPM) was used to analyze the relationships between instantaneous velocity and section or total race time. SPM analyses revealed two uphill sections and one flat section where greater instantaneous velocities were related to faster total race times. The first major uphill section on the track demonstrated a more conservative micro-pacing strategy (SPM supra-threshold clusters along the entire uphill, p < 0.05-0.001) compared to the more aggressive strategy used in the last uphill section (clusters on the first half of the uphill, p < 0.05-0.001). Faster flat section times were associated with greater instantaneous velocities throughout the section (p < 0.001), while faster downhill section times were related to greater instantaneous velocities at the top of the downhill (p < 0.001), and in the downhill turns (p < 0.001). In conclusion, micro-pacing strategies were related to overall skiing performance and distinct track sections were identified where instantaneous velocities were related to section or total race times. In order to improve skiing performance, athletes could focus on more aggressive pacing early on in the "end spurt", during the transitions from uphill to flat sections, and during the transitions from flat or uphill to downhill sections.

The effect of biological maturity status on ground reaction force production during sprinting.

Sprint ability develops nonlinearly across childhood and adolescence. However, the underpinning ground reaction force (GRF) production is not fully understood. This study aimed to uncover the kinetic factors that explain these maturation-related sprint performance differences in Japanese boys and girls. A total of 153 untrained schoolchildren (80 boys, 73 girls) performed two 50-m maximal effort sprints over a 52-force-platform system embedded in an indoor track. Maturity offset (years from peak height velocity; PHV) was estimated using anthropometric data and used to categorise the children into six-year-long maturation groups (from group 1 [5.5-4.5 years before PHV] to group 6 [0.5 years before to 0.5 years after PHV). Maximum and mean step-averaged velocities across 26 steps were compared across consecutive maturation groups, with further GRF analysis (means and waveforms [statistical parametric mapping]) performed when velocity differences were observed. For boys, higher maximum velocities (effect size ± 90% CI = 1.63 ± 0.69) were observed in maturation group 2 (4.5-3.5 years before PHV) compared to group 1 (5.5-4.5 years before PHV), primarily attributable to higher antero-posterior GRFs across shorter ground contacts. Maximum velocities increased from maturation group 4 (2.5-1.5 years before PHV) to group 5 (1.5-0.5 years before PHV) in the girls (effect size ± 90% CI = 1.00 ± 0.78), due to longer ground contacts rather than higher GRFs per se. Waveform analyses revealed more effective reversal of braking forces and higher propulsive forces (e.g. 14%-77% of stance 4), particularly for comparisons involving boys, which suggested potentially enhanced stretch-shortening ability. Youth sport practitioners should consider these maturation-specific alterations when evaluating young athletes' sprint abilities.