Segment Kinematics Research Articles

Machine learning model to study effects of lightweight racket design on elbow and shoulder loading during tennis serve

Tennis is a famous sport in which players perform high-speed, repetitive movements that cause significant load to the shoulder and elbow joints, particularly during tennis serve. Further, the racket design also plays a key role in the efficiency of the player’s performance through the level of mechanical stress that it places on the player’s elbow joints. Therefore, analyzing the biomechanical impact of racket types on the load it renders on elbow and shoulder loading will help optimize the player’s performance and avoid the possibility of risk. However, there are limited studies that are related to the effect of differences in racket mass, balance, and inertia over joint force and moment during the phases of serve. To address this gap, this study employs a Machine Learning (ML)-based model to impact three types of racket such as head-light, even-balanced, and head-heavy, towards joint moments and forces in the shoulder, elbow, and wrist during tennis serves. The kinematic data was collected from eight tennis players, and the collected data was processed using a Long Short-Term Memory (LSTM) neural network to predict joint moments and forces based on racket parameters and segmental kinematics. The results have shown that racket design has an excellent impact on a player’s performance through its impact on shoulder and elbow joints. The head-light racket resulted in a shoulder adduction moment of 9.4 ± 0.8 Nm and a shoulder joint force of 130.2 ± 9.4 N during the acceleration phase, compared to the head-heavy racket, which generated a higher adduction moment of 11.3 ± 1.0 Nm and a shoulder force of 162.3 ± 11.4 N. The even-balanced racket showed intermediate values, with an adduction moment of 10.2 ± 0.9 Nm and a shoulder force of 142.5 ± 9.9 N.

Hamstrings are Stretched More and Faster during Accelerative Running Compared to Speed-Matched Constant-Speed Running.

Hamstring injuries are common in field-based sports and reinjury rates are high. Recent evidence suggests hamstring injuries often occur during accelerative running, but investigations of hamstring mechanics have primarily considered constant-speed running. Thus, our objective was to compare hamstring lengths and velocities between accelerative running and constant-speed running. We recorded videos of 10 participants during 6 accelerative running trials and 6 constant-speed running trials. We used OpenCap to estimate body segment kinematics and a 3-dimensional musculoskeletal model to compute peak length and step-average lengthening velocity of the biceps femoris (long head) muscle-tendon unit. We compared running conditions using linear mixed models with running speed as the independent variable. At running speeds below 75% of top speed, accelerative running resulted in greater peak lengths than constant-speed running. For example, the peak hamstring muscle-tendon length when a person accelerated from running at only 50% of top speed was equivalent to running at a constant 88% of top speed. Lengthening velocities were greater during accelerative running at all running speeds. Differences in hip flexion kinematics drove the greater peak lengths and lengthening velocities observed in accelerative running. Hamstrings are subjected to longer lengths and faster lengthening velocities in accelerative running than in constant-speed running. This provides a potential biomechanical perspective towards understanding the occurrence of hamstring injuries during acceleration. Our results suggest coaches and sports medicine staff should consider the accelerative nature of running in addition to running speed to quantify exposure to high-risk circumstances with long lengths and fast lengthening velocities of the hamstrings.

Head and pelvis are the key segments recruited by adult spinal deformity patients during daily life activities

Functional assessment is a key element in evaluating adult spinal deformity (ASD) patients. The multitude of 3D kinematic parameters provided by movement analysis can be confusing for spine surgeons. The aim was to investigate movement patterns of ASD based on key kinematic parameters. 115 primary ASD and 36 controls underwent biplanar radiographs and 3D movement analysis during walking, sit-to-stand and stair ascent to calculate joint and segment kinematics. Principal component analysis was applied to identify the most relevant kinematic parameters that define movement strategies adopted by ASD. Pelvis and head relative to pelvis kinematics were the most relevant parameters. ASD patients adopted four different movement strategies. Class 1: normative head and pelvis kinematics. Class 2: persistent pelvic backward tilt. Class 3: persistent forward shift of the head. Class 4: both pelvic backward tilt and forward shift of the head. Patients in class 3 and 4 presented sagittal malalignment on static radiographs with increased pelvic tilt, pelvic incidence-lumbar lordosis mismatch and sagittal vertical axis. Surprisingly, patients in class 3 had normal pelvic kinematics during movement, showing the importance of functional evaluation. In addition to being key segments in maintaining static global posture, head and pelvis were found to define movement patterns.

Soft ankle exoskeleton to counteract dropfoot and excessive inversion.

Wearable exoskeletons are emerging technologies for providing movement assistance and rehabilitation for people with motor disorders. In this study, we focus on the specific gait pathology dropfoot, which is common after a stroke. Dropfoot makes it difficult to achieve foot clearance during swing and heel contact at early stance and often necessitates compensatory movements. We developed a soft ankle exoskeleton consisting of actuation and transmission systems to assist two degrees of freedom simultaneously: dorsiflexion and eversion, then performed several proof-of-concept experiments on non-disabled persons. The actuation system consists of two motors worn on a waist belt. The transmission system provides assistive force to the medial and lateral sides of the forefoot via Bowden cables. The coupling design enables variable assistance of dorsiflexion and inversion at the same time, and a force-free controller is proposed to compensate for device resistance. We first evaluated the performance of the exoskeleton in three seated movement tests: assisting dorsiflexion and eversion, controlling plantarflexion, and compensating for device resistance, then during walking tests. In all proof-of-concept experiments, dropfoot tendency was simulated by fastening a weight to the shoe over the lateral forefoot. In the first two seated tests, errors between the target and the achieved ankle joint angles in two planes were low; errors of <1.5° were achieved in assisting dorsiflexion and/or controlling plantarflexion and of <1.4° in assisting ankle eversion. The force-free controller in test three significantly compensated for the device resistance during ankle joint plantarflexion. In the gait tests, the exoskeleton was able to normalize ankle joint and foot segment kinematics, specifically foot inclination angle and ankle inversion angle at initial contact and ankle angle and clearance height during swing. Our findings support the feasibility of the new ankle exoskeleton design in assisting two degrees of freedom at the ankle simultaneously and show its potential to assist people with dropfoot and excessive inversion.

Protocol to record and analyze primate leaping in three dimensions in the wild.

Several studies comparing primate locomotion under lab versus field conditions have shown the importance of implementing both types of studies, as each has their advantages and disadvantages. However, three-dimensional (3D) motion capture of primates has been challenging under natural conditions. In this study, we provide a detailed protocol on how to collect 3D biomechanical data on primate leaping in their natural habitat that can be widely implemented. To record primate locomotion in the dense forest we use modified GoPro Hero Black cameras with zoom lenses that can easily be carried around and set up on tripods. We outline details on how to obtain camera calibrations at greater heights and how to process the collected data using the MATLAB camera calibration app and the motion tracking software DLTdv8a. We further developed a new MATLAB application "WildLeap3D" to generate biomechanical performance metrics from the derived x, y, z coordinates of the leaps. We provide details on how to collect data on support diameter, compliance, and orientation, and combine these with the jumps to study locomotor performance in an ecological context. We successfully reconstructed leaps of wild primates in the 3D space under natural conditions and provided data on four representative leaps. We provide exemplar data on primate velocity and acceleration during a leap and show how our protocol can be used to analyze segmental kinematics. This study will help to make motion capture of freely moving animals more accessible and help further our knowledge about animal locomotion and movement.

A Vehicle Velocity Prediction Method with Kinematic Segment Recognition

Accurate vehicle velocity prediction is of great significance in vehicle energy distribution and road traffic management. In light of the high time variability of vehicle velocity itself and the limitation of single model prediction, a velocity prediction method based on K-means-QPSO-LSTM with kinematic segment recognition is proposed in this paper. Firstly, the K-means algorithm was used to cluster samples with similar characteristics together, extract kinematic fragment samples in typical driving conditions, calculate their feature parameters, and carry out principal component analysis on the feature parameters to achieve dimensionality reduction transformation of information. Then, the vehicle velocity prediction sub-neural network models based on long short-term memory (LSTM) with the QPSO algorithm optimized were trained under different driving condition datasets. Furthermore, the kinematic segment recognition and traditional vehicle velocity prediction were integrated to form an adaptive vehicle velocity prediction method based on driving condition identification. Finally, the current driving condition type was identified and updated in real-time during vehicle velocity prediction, and then the corresponding sub-LSTM model was used for vehicle velocity prediction. The simulation experiment demonstrated a significant enhancement in both the velocity and accuracy of prediction through the proposed method. The proposed hybrid method has the potential to improve the accuracy and reliability of vehicle velocity prediction, making it applicable in various fields such as autonomous driving, traffic management, and energy management strategies for hybrid electric vehicles.

How reliable are femoropelvic kinematics during deep squats? The influence of subject-specific skeletal modelling on measurement variability

BackgroundBiplanar radiography displays promising results in the production of subject-specific (S.specific) biomechanical models. However, the focus has predominantly centred on methodological investigations in gait analysis. Exploring the influence of such models on the analysis of high range of motion tasks linked to hip pathologies is warranted. The aim of this study is to investigate the effect of S.Specific modelling techniques on the reliability of deep squats kinematics in comparison to generic modelling. Methods8 able-bodied male participants attended 5 motion capture sessions conducted by 3 observers and performed 5 deep squats in each. Prior to each session a biplanar scan was acquired with the reflective-markers attached. Inverse kinematics of pelvis and thigh segments were calculated based on S.specific and Generic model definition. Agreement between the two models femoropelvic orientation in standing was assessed with Bland-Altman plots and paired t- tests. Inter-trial, inter-session, inter-observer variability and observer/trial difference and ratio were calculated for squat kinematic data derived from the two modelling approaches. ResultsCompared to the Generic model, the S.Specific model produced a calibration trial that is significantly offset into more posterior pelvis tilt (–2.8±2.7), hip extension (–2.2±3.8), hip abduction (–1.2±3.6) and external rotation (–13.8±11.4). The S.specific model produced significantly different squat kinematics in the sagittal plane of the pelvis (entire squat cycle) and hip (between 40 % and 60 % of the squat cycle). Variability analysis indicated that the error magnitude between the two models was comparable (difference<2°). The S.specific model exhibited a lower variability in the observer/trial ratio in the sagittal pelvis and hip, the frontal hip, but showed a higher variability in the transverse hip. SignificanceS.specific modelling appears to introduce a calibration offset that primarily translates into an effect in the sagittal plane kinematics. However, the clinical added value of S.specific modelling in terms of reducing experimental sources of kinematic variability was limited.

Working cycle condition construction for electric wheel loader based on principal component analysis and cluster analysis

With the rapid development of new energy technology, cycle condition is significant for the design of powertrain system, whole machine economy, endurance, and other performance parameters of pure electric drive machines. Many cycle conditions of the passenger car industry have been defined. While that for the loader which has complex operation modes and working conditions, has less research on this aspect. Cycle conditions suitable for loader have not been constructed. To support the research and development of electric loader power system, the cycle conditions that can reflect the driving characteristics of electric loader are studied in this paper. According to the typical “V” cycle condition of loader, the actual driving condition data are collected and the kinematic segments are divided. The kinematic segments are grouped into five categories by using principal component analysis and K-means clustering algorithm to obtain the clustering center of each category. The working cycle condition is formed by extracting the combination of segments closest to the clustering center. Finally, based on AMESim simulation and whole machine test analysis, the error between the simulation and vehicle test results of the energy consumption is 3.4%. The accuracy and effectiveness of the proposed constructed cycle conditions are verified.

Jumping towards field-based ground reaction force estimation and assessment with OpenCap

Low-cost and field-viable methods that can simultaneously assess external kinetics and kinematics are necessary to enhance field-based biomechanical monitoring. The aim of this study was to determine the accuracy and usability of ground reaction force (GRF) profiles estimated from segmental kinematics, measured with OpenCap (a low-cost markerless motion-capture system), during common jumping movements. Full-body segmental kinematics were recorded for fifteen recreational athletes performing countermovement, squat, bilateral drop, and unilateral drop jumps, and used to estimate vertical GRFs with a mechanics-based method. Eleven distinct performance-, fatigue-, or injury-related GRF variables were then validated against a gold-standard force platform. Across jumping movements, a total of six and three GRF variables were estimated with a bias or limits of agreement <5 % respectively. Bias and limits of agreement were between 5 and 15 % for seventeen and nineteen variables respectively. Moreover, we show that estimated force variables with a bias <15 % can adequately assess the within-athlete changes in GRF variables between jumping conditions (arm swing or leg dominance). These findings indicate that using a low-cost and field-viable markerless motion capture system (OpenCap) to estimate and assess GRF profiles during common jumping movements is approaching acceptable limits of accuracy. The presented method can be used to monitor force variables of interest and examine underlying segmental kinematics. This application is a jump towards researchers and sports practitioners performing biomechanical monitoring of jumping efficiently, regularly, and extensively in field settings.

Musculoskeletal model degrees of Freedom: Frontal plane constraints are hindering our understanding of human movement

Induced acceleration analyses have expanded our understanding on the contributions of muscle forces to center of mass and segmental kinematics during a myriad of tasks. While these techniques have identified a subset of major muscle that contribute to locomotion, most analyses have included models with only one frontal plane degree of freedom (dof) actuated by the hip joint. The purpose of this study was to define the impact of including knee and subtalar joint frontal plane dof on model superposition accuracy and muscle specific contributions to mediolateral accelerations. Induced acceleration analyses were performed using OpenSim with the Lai model on a freely available dataset of one subject running at 4 m/s. Analyses were performed on four models (standard, with subtalar joint, with frontal plane knee, and combined frontal plane knee with subtalar) with the kinematic constraint and perturbation analyses. Root mean square error and correlations were computed against experimental kinematics. Adding frontal plane dofs improved mediolateral acceleration correlations on average by > 0.25 while only minimally impacting errors. The constraints method performed better than the perturbation method for mediolateral accelerations. Including frontal plane knee dof resulted in muscle and method specific responses. All muscles presented with a complete flip of polarity for constraint method, imparted by allowing the medial/lateral muscles to contribute according to their anatomical function. Only the gluteus medius flipped for the perturbation method. This study provides significant support for the inclusion of frontal plane knee and subtalar dof and the need for reevaluation of muscle contributions via induced acceleration.

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization.

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subject's skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2 cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

Lower extremity kinematic and kinetic factors associated with bat speed at ball contact during the baseball swing

ABSTRACT The purpose of this study was to determine which biomechanical variables measured during the baseball swing are associated with linear bat speed at ball contact (bat speed). Twenty collegiate baseball players hit a baseball from a tee into a net. Kinematics were recorded with a motion capture system sampling at 500 Hz and kinetics were measured by force plates under each foot sampling at 1000 Hz. Associations between bat speed, individual joint and segment kinematics, joint moments and ground reaction forces (GRF) were assessed using Pearson correlations and stepwise linear regression. Average bat speed was 30 ± 2 m/s. Lead foot peak vertical (159 ± 29% BW, r = 0.622, P = 0.001), posterior (−57 ± 12% BW, r = –0.574, P = 0.008) and resultant (170 ± 30% BW, r = 0.662, P = 0.001) GRF were all correlated with bat speed. No combination of factors strengthened the relationship to bat speed beyond these individual variables. These results illustrate the role of the lead leg in generating and transferring ground reaction forces through the kinetic chain in order to accelerate the bat. Training to improve bat speed should include both general lower extremity strengthening exercises and sport-specific hitting drills to improve lower extremity force production following lead foot contact.

Common modelling assumptions affect the joint moments measured during passive joint mobilizations

Joint resistance to passive mobilization has already been estimated in-vivo in several studies by measuring the applied forces and moments while manipulating the joint. Nevertheless, in most of the studies, simplified modelling approaches are used to calculate this joint resistance. The impact of these simplifications is still unknown. We propose a protocol that enables a reference 3D inverse dynamics approach to be implemented and compared to common simplified approaches. Eight typically developed children and eight children with cerebral palsy were recruited and underwent a passive testing protocol, while applied forces and moments were measured through a 3D handheld dynamometer, simultaneously to its 3D kinematics and the 3D kinematics of the different segments. Then, passive joint resistance was estimated using the reference 3D inverse dynamics approach and according to 5 simplified approaches found in the literature, i.e. ignoring either the dynamometer kinematics, the measured moments alone or together with the measured tangential forces, the gravity and the inertia of the different segments, or the distal segments kinematics. These simplifications lead to non-negligible differences with respect to the reference 3D inverse dynamics, from 3 to 32% for the ankle, 4 to 34% for the knee and 1 to 58% for the hip depending of the different simplifications. Finally, we recommend a complete 3D kinematics and dynamics modelling to estimate the joint resistance to passive mobilization.

Effect of the Skill, Gender, and Kick Order on the Kinematic Characteristics of Underwater Undulatory Swimming in the Dorsal Position.

Backstroke swimmers display the greatest contribution of underwater kicking during the swimming race distances, but, surprisingly, there is little evidence of how kicking kinematics in the dorsal position should be performed. The aim of the present study was to examine the kinematic characteristics of competitive swimmers during underwater undulatory swimming in the dorsal position, with special attention to the swimmers' gender, the level of skill, and kick order. Forty-one national-level swimmers (27 females and 14 males) were filmed from an underwater lateral view while performing a 25-m backstroke from a push start, and they were divided into fast and slow groups according to their kicking velocity. Direct linear algorithms were employed to reconstruct the two-dimensional kinematic characteristics of the first and final kicks of the underwater section. There were no differences between males and females in kicking performance when data were normalised to the swimmers' height. However, swimmers in the fast-kicking group were distinguished by a greater kicking frequency (η2: 0.15) and specific segmental kinematics related to a lower knee range of motion. Swimmers decreased kicking velocity (η2: 0.47) in addition to the kicking frequency (η2: 0.31) and length (η2: 0.16), but increased the kicking amplitude (η2: 0.11) between the first and the final kicks. Changes in kicking segmental kinematics were more related to modification in body orientation during the underwater trajectory than to the kicking motion itself. These results provide the first solid evidence of how swimmers should kick for better performance in dorsal underwater swimming.

Dynamic segmental kinematics of the lumbar spine during diagnostic movements.

Background: In vivo measurements of segmental-level kinematics are a promising avenue for better understanding the relationship between pain and its underlying, multi-factorial basis. To date, the bulk of the reported segmental-level motion has been restricted to single plane motions. Methods: The present work implemented a novel marker set used with an optical motion capture system to non-invasively measure dynamic, 3D in vivo segmental kinematics of the lower spine in a laboratory setting. Lumbar spinal kinematics were measured for 28 subjects during 17 diagnostic movements. Results: Overall regional range of motion data and lumbar angular velocity measurement were consistent with previously published studies. Key findings from the work included measurement of differences in ascending versus descending segmental velocities during functional movements and observations of motion coupling paradigms in the lumbar spinal segments. Conclusion: The work contributes to the task of establishing a baseline of segmental lumbar movement patterns in an asymptomatic cohort, which serves as a necessary pre-requisite for identifying pathological and symptomatic deviations from the baseline.

Integrated UWB/MIMU Sensor System for Position Estimation towards an Accurate Analysis of Human Movement: A Technical Review.

Integrated Ultra-wideband (UWB) and Magnetic Inertial Measurement Unit (MIMU) sensor systems have been gaining popularity for pedestrian tracking and indoor localization applications, mainly due to their complementary error characteristics that can be exploited to achieve higher accuracies via a data fusion approach. These integrated sensor systems have the potential for improving the ambulatory 3D analysis of human movement (estimating 3D kinematics of body segments and joints) over systems using only on-body MIMUs. For this, high accuracy is required in the estimation of the relative positions of all on-body integrated UWB/MIMU sensor modules. So far, these integrated UWB/MIMU sensors have not been reported to have been applied for full-body ambulatory 3D analysis of human movement. Also, no review articles have been found that have analyzed and summarized the methods integrating UWB and MIMU sensors for on-body applications. Therefore, a comprehensive analysis of this technology is essential to identify its potential for application in 3D analysis of human movement. This article thus aims to provide such a comprehensive analysis through a structured technical review of the methods integrating UWB and MIMU sensors for accurate position estimation in the context of the application for 3D analysis of human movement. The methods used for integration are all summarized along with the accuracies that are reported in the reviewed articles. In addition, the gaps that are required to be addressed for making this system applicable for the 3D analysis of human movement are discussed.

Biomechanical characterisation of the pull-up exercise

PurposePerformance is the benchmark to assess the level of an athlete: in this respect, a more precise qualitative and quantitative evaluation of the performance represents an important target to be achieved.MethodsThe work presents a possible method, based on the biomechanical evaluation of the motor exercise with an optoelectronic system, to characterise single or multiple repetitions of pull-ups of 12 athletes of sport climbing and sportive healthy subjects, monitoring and scoring the performance and the safety of the executions. The analysis includes the time courses of the segmental kinematics and some newly developed synthetic indices in the form of performance and safety scores.ResultsThe time courses make it possible to analyse the linear and angular kinematics district-by-district and have a direct overview of the ranges of motion, the patterns of task execution, together with the possible strategies adopted to complete the exercise in terms of compensations. The proposed characterisation provides a condensed summary of the global execution quality and offers the possibility to identify which single biomechanical parameters are modified.ConclusionThe method is intended as a practical tool to enrich the training schedule in terms of the qualitative and quantitative evaluation of the performances and to increase the self-awareness while training.

Société de Biomécanique Young Investigator Award 2019: Upper body behaviour of seated humans in vivo under controlled lateral accelerations

BackgroundA deep understanding of human reactions and stabilization strategies is required to predict their kinematics under external dynamic loadings, such as those that occur in vehicle passengers. Low-level frontal accelerations have been thoroughly investigated; however, the human response to different lateral accelerations is not well understood. The objective of this study is to gain insight regarding the responses of seated humans to lateral perturbations from volunteer experiments in different configurations. MethodsFive volunteers anthropometrically comparable to the 50th-percentile American male, were seated on a sled and submitted to 21 lateral pulses. Seven configurations, each repeated three times, were investigated in this study: a relaxed muscular condition with four pulses, namely, sine and plateau pulses of 0.1 and 0.3 g in a straight spinal posture; a relaxed muscular condition with a plateau pulse of 0.3 g in a sagging spinal posture; and a braced condition with both plateau pulses in a straight spinal posture. Upper body segment kinematics were assessed using inertial measurement units. FindingsThe maximum lateral bending of the head was found to differ significantly among the four acceleration pulses (p < 0.001). Braced muscles significantly reduced lateral bending compared to relaxed muscles (p < 0.001). However, no significant difference was found in lateral bending between straight and sagging spinal postures (p = 0.23). InterpretationThe study shows that not only pulse amplitude but also pulse shape influences human responses to low accelerations, while spinal posture does not influence lateral head bending. These data can be used to evaluate numerical active human body models.

Kinematic changes in the undulatory kicking during underwater swimming

ABSTRACT The contribution to total race distances of underwater undulatory swimming (UUS) is increasing at the elite level. However, little is known about the technical modifications during underwater swimming. In the present research, the aim was to compare the kinematic characteristics of competitive swimmers between the first and last kick of UUS. Fifty-four national level swimmers (26 males and 28 females) performed 25 m maximal efforts from a push start, and two sequential video cameras captured the underwater segment. Kicking parameters and segmental kinematics were calculated by means of two-dimensional direct linear transformation algorithms. Dolphin kick performance showed a clear impairment in velocity (η2 : 0.65), but changes on kicking parameters depended on the swimmer’s gender, with males decreasing kicking amplitude (η2 : 0.25) and females decreasing kicking frequency (η2 : 0.18) in the last kick. Decline in kicking performance seemed to be more related to the swimmers’ body configuration when approaching the water surface (greater trunk inclination and maximal body amplitude in sagittal plane) than to technical modifications in the dolphin kick movement (no changes in the joints range of movement except the hip). Swimmers should control their vertical body amplitude at the end of underwater sections to minimise the decrease in kicking performance.

The effect of external loads and biological sex on coupling variability during load carriage

BackgroundLoad carriage is a fundamental requirement for military personnel that commonly results in lower-limb injuries. Coupling variability represents a potential injury mechanism for such repetitive tasks and its unknown whether external loads and biological sex affect coupling variability during load carriage. Research questionIs there a sex-by-load interaction during load carriage at self-selected walking speeds? MethodsTwenty-six participants (13 males, 13 females) completed three 10-minute treadmill-based trials wearing body-borne external load (0 %BM, 20 %BM, and 40 %BM) at load-specific self-selected walking speeds. A Vicon motion capture system tracked markers with a lower-body direct-kinematic model calculating sagittal-plane segment kinematics of the thigh, shank, and foot across 19 strides. Continuous relative phase standard deviation (CRPv) provided a measure of coupling variability for each coupling angle (Thigh-Shank and Shank-Foot). The CRPv for each load and sex was compared using statistical parametric mapping repeated measures ANOVA and paired t tests. ResultsSignificant sex-by-load interactions were reported for the Thigh-Shank coupling. Males demonstrated no significant load differences in CRPv, however, females displayed significantly higher CRPv in the 40 %BM than the 0 %BM condition. A significant main effect of load was observed in the Shank-Foot coupling, with the 40 %BM having significantly greater CRPv than the other load conditions. SignificanceBoth biological sex and external loads significantly affected CRPv during load carriage at self-selected walking speeds. Females demonstrated greater CRPv at the heavier loads, suggesting that the perturbation from the heavier mass increases coupling variability, which may also be amplified by a greater total passive load due to their relatively higher adipose tissue compared to males. The consistent CRPv in males suggests that higher relative loads may be required to change coupling variability. Collectively, these results suggest that external load affects the coupling variability of males and females differently, providing potential for injury screening and monitoring programs.