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.

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and socio-economic implications. The predominant form is non-specific LBP (NSLBP), lacking treatable pathology. Active physical interventions tailored to individual needs and capabilities are crucial for its management. However, the intricate nature of NSLBP and complexity of clinical classification systems necessitating extensive clinical training, hinder customised treatment access. Recent advancements in machine learning and computer vision demonstrate promise in characterising NSLBP altered movement patters through wearable sensors and optical motion capture. This study aimed to develop and evaluate a machine learning model (i.e., 'BACK-to-MOVE') for NSLBP classification trained with expert clinical classification, spinal motion data from a standard video alongside patient-reported outcome measures (PROMs). METHODS: Synchronised video and three-dimensional (3D) motion data was collected during forward spinal flexion from 83 NSLBP patients. Two physiotherapists independently classified them as motor control impairment (MCI) or movement impairment (MI), with conflicts resolved by a third expert. The Convolutional Neural Networks (CNNs) architecture, HigherHRNet, was chosen for effective pose estimation from video data. The model was validated against 3D motion data (subset of 62) and trained on the freely available MS-COCO dataset for feature extraction. The Back-to-Move classifier underwent fine-tuning through feed-forward neural networks using labelled examples from the training dataset. Evaluation utilised 5-fold cross-validation to assess accuracy, specificity, sensitivity, and F1 measure. RESULTS: Pose estimation's Mean Square Error of 0.35 degrees against 3D motion data demonstrated strong criterion validity. Back-to-Move proficiently differentiated MI and MCI classes, yielding 93.98% accuracy, 96.49% sensitivity (MI detection), 88.46% specificity (MCI detection), and an F1 measure of .957. Incorporating PROMs curtailed classifier performance (accuracy: 68.67%, sensitivity: 91.23%, specificity: 18.52%, F1: .800). CONCLUSION: This study is the first to demonstrate automated clinical classification of NSLBP using computer vision and machine learning with standard video data, achieving accuracy comparable to expert consensus. Automated classification of NSLBP based on altered movement patters video-recorded during routine clinical examination could expedite personalised NSLBP rehabilitation management, circumventing existing healthcare constraints. This advancement holds significant promise for patients and healthcare services alike.

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.

Tackle direction and preferred side affect upper body loads and movements in rugby union tackling.

Tackling in Rugby Union is associated with most match injuries. New tackle regulations have been explored to reduce injuries, but limited quantitative evidence is available to inform any law changes. Using a novel tackle simulator, we investigated upper body loading under different tackling conditions: direction of approach (0° - frontal, 45° and 90° to the ball carrier direction) and side of body (dominant vs. non-dominant). Peak impact force between tackler and simulator , and head and upper trunk segment motions were measured from 10 male players. Impact load averages were 17% higher at (0°) compared with (90°), across the two different tackling sides (p = 0.093), with the highest impact force measured during dominant-side shoulder tackles at 0° (5.63 ± 1.14 kN). Trunk resultant accelerations were higher (+19%, p = 0.010) at 0° compared with 90°, with the highest resultant acceleration measured in frontal tackles with the dominant shoulder (17.52 ± 3.97 g). We observed higher head lateral bending around the impact when tackling with the non-dominant shoulder at 45° (p = 0.024) and 90° (p = 0.047). Tackling from an offset angle from frontal may be safer. Deficiencies in tackling techniques on the non-dominant side should be reduced.

Understanding the role of physical activity on the pathway from intra-articular knee injury to post-traumatic osteoarthritis disease in young people: a scoping review protocol.

INTRODUCTION: The prevalence of intra-articular knee injuries and reparative surgeries is increasing in many countries. Alarmingly, there is a risk of developing post-traumatic osteoarthritis (PTOA) after sustaining a serious intra-articular knee injury. Although physical inactivity is suggested as a risk factor contributing to the high prevalence of the condition, there is a paucity of research characterising the association between physical activity and joint health. Consequently, the primary aim of this review will be to identify and present available empirical evidence regarding the association between physical activity and joint degeneration after intra-articular knee injury and summarise the evidence using an adapted Grading of Recommendations Assessment, Development and Evaluations. The secondary aim will be to identify potential mechanistic pathways through which physical activity could influence PTOA pathogenesis. The tertiary aim will be to highlight gaps in current understanding of the association between physical activity and joint degeneration following joint injury. METHODS: A scoping review will be conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist and best-practice recommendations. The review will be guided by the following research question: what is the role of physical activity in the trajectory from intra-articular knee injury to PTOA in young men and women? We will identify primary research studies and grey literature by searching the electronic databases Scopus, Embase: Elsevier, PubMed, Web of Science: all databases, and Google Scholar. Reviewing pairs will screen abstracts, full texts and will extract data. Data will be presented descriptively using charts, graphs, plots and tables. ETHICS AND DISSEMINATION: This research does not require ethical approval due to the data being published and publicly available. This review will be submitted for publication in a peer-reviewed sports medicine journal irrespective of discoveries and disseminated through scientific conference presentations and social media. TRIAL REGISTRATION NUMBER: https://osf.io/84pnh/.

Consensus on a jockey's injury prevention framework for video analysis: a modified Delphi study.

Professional horse racing is a high-risk and dangerous sport with a high incidence of falls and injuries. While falls in horse racing are considered somewhat inevitable and carry an inherent occupational risk, little is known about the actual mechanisms of jockey injuries. Establishing injury aetiology and mechanism is a fundamental step in informing the design and implementation of future injury prevention strategies. Despite the availability of horse racing video footage, the use of video analysis to examine injury mechanisms is an underused practice. Using an expert consensus-based approach, an industry expert steering committee was assembled to develop a framework for video analysis research in horse racing. The aim of the framework is to encourage and facilitate the use of video analysis in the sport and to ensure consistency and quality of future application. To achieve consensus, a systematic review and modified Delphi method study design was used. Responses of the steering committee to two open-ended questions regarding the risk factors of falls and injury were collated and combined with findings from a literature search strategy. Appropriate descriptors and definitions were then formulated that defined and described key features of a jockey fall in horse racing and grouped into six discrete phases of an inciting event. Each member of the steering committee then examined the framework of proposed descriptors and definitions and rated their level of agreement on the 5-point Likert scale. A consensus was achieved on a total of 73 horse racing-specific descriptors and 268 associated definitions. The framework outlined in this study provides a valuable starting point for further research and practice within this area, while the recommendations and implications documented aim to facilitate the practical application of video analysis in horse racing.

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.

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.

Incidence and predictive factors of problems after fixation of trochanteric hip fractures with sliding hip screw or intramedullary devices.

INTRODUCTION: Hip fractures are common and disabling injuries, usually managed surgically. The most common type outside the joint capsule are trochanteric fractures, usually fixed with either sliding hip screw or intramedullary nail. Data are available in the National Hip Fracture Database (NHFD) on early failure and other major complications, but late or subtler complications may escape recording. This study sought to quantify such problems after fixation performed at 3different sites and identify their predictors. METHODS: Patients with a trochanteric fracture treated at 1 of 3 sites were identified from the NHFD over a 3-year period. Any with further, related episodes of care were identified, and reasons recorded, then age- and sex-matched with those with no such episodes. Data was collected on Arbeitsgemeinschaft für Osteosynthesefragen classification, tip-apex distance, American Society of Anesthesiologists (ASA) grade, Abbreviated Mental Test Score and pre-injury mobility. The cohorts were compared, and a binomial logistic regression model used to identify predictors of problems. RESULTS: A total of 4010 patients were entered in the NHFD across 3 sites between January 2013 and December 2015. Of these, 1260 sustained trochanteric fractures and 57 (4.5%) subsequently experienced problems leading to re-presentation. The most common was failure of fixation, occurring in 22 patients (1.7%). The binomial logistic regression model explained 47.6% of the variance in incidence of postoperative problems with ASA grade and tip-apex distance being predictive. DISCUSSION: The incidence of re-presentation with problems was around of 5%. A failure rate of less than 2% was seen, in keeping with existing data. This study has quantified the incidence of subtler postoperative problems and identified their predictors. The type of implant used was not amongst them and patients with both implants experienced problems. Fixation continues to yield imperfect results, but patient health and robust surgical technique remain important factors in a good outcome.

Electromyography-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts.

Knowledge of neck muscle activation strategies before sporting impacts is crucial for investigating mechanisms of severe spinal injuries. However, measurement of muscle activations during impacts is experimentally challenging and computational estimations are not often guided by experimental measurements. We investigated neck muscle activations before impacts with the use of electromyography (EMG)-assisted neuromusculoskeletal models. Kinematics and EMG recordings from four major neck muscles of a rugby player were experimentally measured during rugby activities. A subject-specific musculoskeletal model was created with muscle parameters informed from MRI measurements. The model was used in the calibrated EMG-informed neuromusculoskeletal modeling toolbox and three neural solutions were compared: (i) static optimization (SO), (ii) EMG-assisted (EMGa), and (iii) MRI-informed EMG-assisted (EMGaMRI). EMGaMRI and EMGa significantly (p < 0.01) outperformed SO when tracking cervical spine net joint moments from inverse dynamics in flexion/extension (RMSE = 0.95, 1.14, and 2.32 N·m) but not in lateral bending (RMSE = 1.07, 2.07, and 0.84 N·m). EMG-assisted solutions generated physiological muscle activation patterns and maintained experimental cocontractions significantly (p < 0.01) outperforming SO, which was characterized by saturation and nonphysiological "on-off" patterns. This study showed for the first time that physiological neck muscle activations and cervical spine net joint moments can be estimated without assumed a priori objective criteria before impacts. Future studies could use this technique to provide detailed initial loading conditions for theoretical simulations of neck injury during impacts.

Development and validation of FootNet; a new kinematic algorithm to improve foot-strike and toe-off detection in treadmill running.

The accurate detection of foot-strike and toe-off is often critical in the assessment of running biomechanics. The gold standard method for step event detection requires force data which are not always available. Although kinematics-based algorithms can also be used, their accuracy and generalisability are limited, often requiring corrections for speed or foot-strike pattern. The purpose of this study was to develop FootNet, a novel kinematics and deep learning-based algorithm for the detection of step events in treadmill running. Five treadmill running datasets were gathered and processed to obtain segment and joint kinematics, and to identify the contact phase within each gait cycle using force data. The proposed algorithm is based on a long short-term memory recurrent neural network and takes the distal tibia anteroposterior velocity, ankle dorsiflexion/plantar flexion angle and the anteroposterior and vertical velocities of the foot centre of mass as input features to predict the contact phase within a given gait cycle. The chosen model architecture underwent 5-fold cross-validation and the final model was tested in a subset of participants from each dataset (30%). Non-parametric Bland-Altman analyses (bias and [95% limits of agreement]) and root mean squared error (RMSE) were used to compare FootNet against the force data step event detection method. The association between detection errors and running speed, foot-strike angle and incline were also investigated. FootNet outperformed previously published algorithms (foot-strike bias = 0 [-10, 7] ms, RMSE = 5 ms; toe-off bias = 0 [-10, 10] ms, RMSE = 6 ms; and contact time bias = 0 [-15, 15] ms, RMSE = 8 ms) and proved robust to different running speeds, foot-strike angles and inclines. We have made FootNet's source code publicly available for step event detection in treadmill running when force data are not available.

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.

A novel IMU-based clinical assessment protocol for Axial Spondyloarthritis: a protocol validation study.

Clinical assessment of spinal impairment in Axial Spondyloarthritis is currently performed using the Bath Ankylosing Spondylitis Metrological Index (BASMI). Despite being appreciated for its simplicity, the BASMI index lacks sensitivity and specificity of spinal changes, demonstrating poor association with radiographical range of motion (ROM). Inertial measurement units (IMUs) have shown promising results as a cost-effective method to quantitatively examine movement of the human body, however errors due to sensor angular drift have limited their application to a clinical space. Therefore, this article presents a wearable sensor protocol that facilitates unrestrained orientation measurements in space while limiting sensor angular drift through a novel constraint-based approach. Eleven healthy male participants performed five BASMI-inspired functional movements where spinal ROM and continuous kinematics were calculated for five spine segments and four spinal joint levels (lumbar, lower thoracic, upper thoracic and cervical). A Bland-Altman analysis was used to assess the level of agreement on range of motion measurements, whilst intraclass correlation coefficient (ICC), standardised error measurement, and minimum detectable change (MDC) to assess relative and absolute reliability. Continuous kinematics error was investigated through root mean square error (RMSE), maximum absolute error (MAE) and Spearman correlation coefficient (ρ). The overall error in the measurement of continuous kinematic measures was low in both the sagittal (RMSE = 2.1°), and frontal plane (RMSE = 2.3°). ROM limits of agreement (LoA) and minimum detectable change were excellent for the sagittal plane (maximum value LoA 1.9° and MDC 2.4°) and fair for lateral flexion (overall value LoA 4.8° and MDC 5.7°). The reliability analysis showed excellent level of agreement (ICC > 0.9) for both segment and joint ROM across all movements. The results from this study demonstrated better or equivalent accuracy than previous studies and were considered acceptable for application in a clinical setting. The protocol has shown to be a valuable tool for the assessment of spinal ROM and kinematics, but a clinical validation study on Axial Spondyloarthritis patients is required for the development and testing of a novel mobility index.

Training Load and Injury Risk in Elite Rugby Union: The Largest Investigation to Date.

Training load monitoring has grown in recent years with the acute:chronic workload ratio (ACWR) widely used to aggregate data to inform decision-making on injury risk. Several methods have been described to calculate the ACWR and numerous methodological issues have been raised. Therefore, this study examined the relationship between the ACWR and injury in a sample of 696 players from 13 professional rugby clubs over two seasons for 1718 injuries of all types and a further analysis of 383 soft tissue injuries specifically. Of the 192 comparisons undertaken for both injury groups, 40% (all injury) and 31% (soft tissue injury) were significant. Furthermore, there appeared to be no calculation method that consistently demonstrated a relationship with injury. Some calculation methods supported previous work for a "sweet spot" in injury risk, while a substantial number of methods displayed no such relationship. This study is the largest to date to have investigated the relationship between the ACWR and injury risk and demonstrates that there appears to be no consistent association between the two. This suggests that alternative methods of training load aggregation may provide more useful information, but these should be considered in the wider context of other established risk factors.

Fusing Accelerometry with Videography to Monitor the Effect of Fatigue on Punching Performance in Elite Boxers.

Wearable sensors and motion capture technology are accepted instruments to measure spatiotemporal variables during punching performance and to study the externally observable effects of fatigue. This study aimed to develop a computational framework enabling three-dimensional inverse dynamics analysis through the tracking of punching kinematics obtained from inertial measurement units and uniplanar videography. The framework was applied to six elite male boxers performing a boxing-specific punch fatigue protocol. OpenPose was used to label left side upper-limb landmarks from which sagittal plane kinematics were computed. Custom-made inertial measurement units were embedded into the boxing gloves, and three-dimensional punch accelerations were analyzed using statistical parametric mapping to evaluate the effects of both fatigue and laterality. Tracking simulations of a sub-set of left-handed punches were formulated as optimal control problems and converted to nonlinear programming problems for solution with a trapezoid collocation method. The laterality analysis revealed the dominant side fatigued more than the non-dominant, while tracking simulations revealed shoulder abduction and elevation moments increased across the fatigue protocol. In future, such advanced simulation and analysis could be performed in ecologically valid contexts, whereby multiple inertial measurement units and video cameras might be used to model a more complete set of dynamics.

Musculoskeletal modelling of the human cervical spine for the investigation of injury mechanisms during axial impacts.

Head collisions in sport can result in catastrophic injuries to the cervical spine. Musculoskeletal modelling can help analyse the relationship between motion, external forces and internal loads that lead to injury. However, impact specific musculoskeletal models are lacking as current viscoelastic values used to describe cervical spine joint dynamics have been obtained from unrepresentative quasi-static or static experiments. The aim of this study was to develop and validate a cervical spine musculoskeletal model for use in axial impacts. Cervical spine specimens (C2-C6) were tested under measured sub-catastrophic loads and the resulting 3D motion of the vertebrae was measured. Specimen specific musculoskeletal models were then created and used to estimate the axial and shear viscoelastic (stiffness and damping) properties of the joints through an optimisation algorithm that minimised tracking errors between measured and simulated kinematics. A five-fold cross validation and a Monte Carlo sensitivity analysis were conducted to assess the performance of the newly estimated parameters. The impact-specific parameters were integrated in a population specific musculoskeletal model and used to assess cervical spine loads measured from Rugby union impacts compared to available models. Results of the optimisation showed a larger increase of axial joint stiffness compared to axial damping and shear viscoelastic parameters for all models. The sensitivity analysis revealed that lower values of axial stiffness and shear damping reduced the models performance considerably compared to other degrees of freedom. The impact-specific parameters integrated in the population specific model estimated more appropriate joint displacements for axial head impacts compared to available models and are therefore more suited for injury mechanism analysis.

On the Estimation Accuracy of the 3D Body Center of Mass Trajectory during Human Locomotion: Inverse vs. Forward Dynamics.

The dynamics of body center of mass (BCoM) 3D trajectory during locomotion is crucial to the mechanical understanding of the different gaits. Forward Dynamics (FD) obtains BCoM motion from ground reaction forces while Inverse Dynamics (ID) estimates BCoM position and speed from motion capture of body segments. These two techniques are widely used by the literature on the estimation of BCoM. Despite the specific pros and cons of both methods, FD is less biased and considered as the golden standard, while ID estimates strongly depend on the segmental model adopted to schematically represent the moving body. In these experiments a single subject walked, ran, (uni- and bi-laterally) skipped, and race-walked at a wide range of speeds on a treadmill with force sensors underneath. In all conditions a simultaneous motion capture (8 cameras, 36 markers) took place. 3D BCoM trajectories computed according to five marker set models of ID have been compared to the one obtained by FD on the same (about 2,700) strides. Such a comparison aims to check the validity of the investigated models to capture the "true" dynamics of gaits in terms of distance between paths, mechanical external work and energy recovery. Results allow to conclude that: (1) among gaits, race walking is the most critical in being described by ID, (2) among the investigated segmental models, those capturing the motion of four limbs and trunk more closely reproduce the subtle temporal and spatial changes of BCoM trajectory within the strides of most gaits, (3) FD-ID discrepancy in external work is speed dependent within a gait in the most unsuccessful models, and (4) the internal work is not affected by the difference in BCoM estimates.

Cervical Spine Injuries: A Whole-Body Musculoskeletal Model for the Analysis of Spinal Loading.

Cervical spine trauma from sport or traffic collisions can have devastating consequences for individuals and a high societal cost. The precise mechanisms of such injuries are still unknown as investigation is hampered by the difficulty in experimentally replicating the conditions under which these injuries occur. We harness the benefits of computer simulation to report on the creation and validation of i) a generic musculoskeletal model (MASI) for the analyses of cervical spine loading in healthy subjects, and ii) a population-specific version of the model (Rugby Model), for investigating cervical spine injury mechanisms during rugby activities. The musculoskeletal models were created in OpenSim, and validated against in vivo data of a healthy subject and a rugby player performing neck and upper limb movements. The novel aspects of the Rugby Model comprise i) population-specific inertial properties and muscle parameters representing rugby forward players, and ii) a custom scapula-clavicular joint that allows the application of multiple external loads. We confirm the utility of the developed generic and population-specific models via verification steps and validation of kinematics, joint moments and neuromuscular activations during rugby scrummaging and neck functional movements, which achieve results comparable with in vivo and in vitro data. The Rugby Model was validated and used for the first time to provide insight into anatomical loading and cervical spine injury mechanisms related to rugby, whilst the MASI introduces a new computational tool to allow investigation of spinal injuries arising from other sporting activities, transport, and ergonomic applications. The models used in this study are freely available at simtk.org and allow to integrate in silico analyses with experimental approaches in injury prevention.

Specific tackling situations affect the biomechanical demands experienced by rugby union players.

Tackling in Rugby Union is an open skill which can involve high-speed collisions and is the match event associated with the greatest proportion of injuries. This study aimed to analyse the biomechanics of rugby tackling under three conditions: from a stationary position, with dominant and non-dominant shoulder, and moving forward, with dominant shoulder. A specially devised contact simulator, a 50-kg punch bag instrumented with pressure sensors, was translated towards the tackler (n = 15) to evaluate the effect of laterality and tackling approach on the external loads absorbed by the tackler, on head and trunk motion, and on trunk muscle activities. Peak impact force was substantially higher in the stationary dominant (2.84 ± 0.74 kN) than in the stationary non-dominant condition (2.44 ± 0.64 kN), but lower than in the moving condition (3.40 ± 0.86 kN). Muscle activation started on average 300 ms before impact, with higher activation for impact-side trapezius and non-impact-side erector spinae and gluteus maximus muscles. Players' technique for non-dominant-side tackles was less compliant with current coaching recommendations in terms of cervical motion (more neck flexion and lateral bending in the stationary non-dominant condition) and players could benefit from specific coaching focus on non-dominant-side tackles.

Can coordination variability identify performance factors and skill level in competitive sport? The case of race walking.

BACKGROUND: Marginal changes in the execution of competitive sports movements can represent a significant change for performance success. However, such differences may emerge only at certain execution intensities and are not easily detectable through conventional biomechanical techniques. This study aimed to investigate if and how competition standard and progression speed affect race walking kinematics from both a conventional and a coordination variability perspective. METHODS: Fifteen experienced athletes divided into three groups (elite, international, and national) were studied while race walking on a treadmill at two different speeds (12.0 and 15.5 km/h). Basic gait parameters, the angular displacement of the pelvis and lower limbs, and the variability in continuous relative phase between six different joint couplings were analyzed. RESULTS: Most of the spatio-temporal, kinematic, and coordination variability measures proved sensitive to the change in speed. Conversely, non-linear dynamics measures highlighted differences between athletes of different competition standard when conventional analytical tools were not able to discriminate between different skill levels. Continuous relative phase variability was higher for national level athletes than international and elite in two couplings (pelvis obliquity-hip flex/extension and pelvis rotation-ankle dorsi/plantarflexion) and gait phases (early stance for the first coupling, propulsive phase for the second) that are deemed fundamental for correct technique and performance. CONCLUSION: Measures of coordination variability showed to be a more sensitive tool for the fine detection of skill-dependent factors in competitive race walking, and showed good potential for being integrated in the assessment and monitoring of sports motor abilities.