The expert eye? An inter-rater comparison of elite tennis serve kinematics and performance.

This study examined the reliability of expert tennis coaches/biomechanists to qualitatively assess selected features of the serve with the aid of two-dimensional (2D) video replays. Two expert high-performance coaches rated the serves of 150 male and 150 female players across three different age groups from two different camera viewing angles. Serve performance was rated across 13 variables that represented commonly investigated and coached (serve) mechanics using a 1-7 Likert rating scale. A total of 7800 ratings were performed. The reliability of the experts' ratings was assessed using a Krippendorffs alpha. Strong agreement was shown across all age groups and genders when the experts rated the overall serve score (0.727-0.924), power or speed of the serve (0.720-0.907), rhythm (0.744-0.944), quality of the trunk action (0.775-1.000), leg drive (0.731-0.959) and the likelihood of back injury (0.703-0.934). They encountered greater difficulty in consistently rating shoulder internal rotation speed (0.688-0.717). In high-performance settings, the desire for highly precise measurement and large data sets powered by new technologies, is commonplace but this study revealed that tennis experts, through the use of 2D video, can reliably rate important mechanical features of the game's most important shot, the serve.

Synthesising 2D Video from 3D Motion Data for Machine Learning Applications.

To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames from historic 3D motion data. We applied the video-based human pose estimation model OpenPose to real (in situ) and synthesised 2D videos and compared anatomical landmark keypoint outputs, with trivial observed differences (2.11−3.49 mm). We further demonstrated the utility of the method in a downstream machine learning use-case in which we trained and then tested the validity of an artificial neural network (ANN) to estimate ground reaction forces (GRFs) using synthesised and real 2D videos. Training an ANN to estimate GRFs using eight OpenPose keypoints derived from synthesised 2D videos resulted in accurate waveform GRF estimations (r > 0.9; nRMSE < 14%). When compared with using the smaller number of real videos only, accuracy was improved by adding the synthetic views and enlarging the dataset. The results highlight the utility of the developed approach to enlarge small 2D video datasets, or to create 2D video images to accompany 3D motion capture datasets to make them accessible for machine learning applications.

Changes in acceleration load as measured by inertial measurement units manifest in the upper body after an extended running task.

The purpose of this study was to investigate the behaviour of physiological load measures as well as ground reaction forces (GRF) and acceleration load during a prolonged running task that simulated the running demands of an intermittent team sport. Nineteen males completed a maximal aerobic fitness test and an extended running protocol across two sessions. Participants wore a portable metabolic system, and four inertial measurement units (IMU), one on each foot, the lower back and upper back. GRF were measured via an instrumented treadmill. Change in metabolic, IMU and GRF variables across five blocks during the running protocol were assessed using a one-way repeated measures ANOVA. The running protocol elicited large increases in heart rate and oxygen consumption over time. No statistically significant changes in any peak impact accelerations were observed. Resultant acceleration area under the curve (AUC) increased at the lower and upper back locations but was unchanged at the foot. GRF active peak but not impact peak increased during the prolonged run. The results of this study indicate that the effect of an extended running task on IMU measures of external mechanical load is manifested in the upper body, and is effectively measured by AUC.

The effect of planning time on penultimate and ultimate step kinematics and subsequent knee moments during sidestepping.

Frontal plane postures during the ultimate step of sidestepping are linked to increased anterior cruciate ligament injury risk. However, there is a lack of research detailing the kinematic strategies present in the penultimate step. This study, therefore, investigated penultimate and ultimate step kinematics of planned sidestepping (pSS) and unplanned sidestepping (upSS) to further understand the effect of planning time on known ultimate step kinematic and kinetic differences. Sixty male amateur Australian Rules football players performed three trials of straight-line running (RUN), pSS, and upSS in a randomized order. Mediolateral foot placement and three-dimensional joint kinematics for the knee, pelvis, and trunk were measured at final foot contact of the penultimate step and initial foot contact of the ultimate step. Peak knee moments were measured during the weight acceptance phase of the ultimate step. In pSS, at the penultimate step final foot contact, the support foot was placed across the midline of the center of mass, in the frontal plane, contralateral to the sidestep direction. Greater trunk lateral flexion toward the sidestep direction and greater negative pelvic lateral tilt were observed in pSS compared with upSS and RUN. Differences between pSS and upSS frontal plane kinematics at penultimate step final foot contact suggest preparatory reorientation strategies are likely constrained by the amount of planning time available. As there are clear differences in preparatory kinematics, we recommend that planning time be considered when training and assessing sidestepping maneuvers and planned and unplanned maneuvers not be treated as interchangeable skills.

Measurement of uni-planar and sport specific trunk motion using magneto-inertial measurement units: The concurrent validity of Noraxon and Xsens systems relative to a retro-reflective system.

BACKGROUND: There is a range of magneto-inertial measurement unit (MIMU) systems commercially available, however sensor specifications and fusion methods vary considerably between manufacturers. Such variability can influence the concurrent validity of MIMUs relative to reference standard measurement devices. Different MIMUs have been compared during static or low-velocity conditions, with higher-velocity movements assessed in robotic-based studies. However, there is a need for the concurrent validity of higher-velocity movements to be established in human-based studies. RESEARCH QUESTION: This study aimed to assess the concurrent validity of two commercial MIMU systems (Noraxon and Xsens), relative to a 'gold-standard' retro-reflective motion capture system, when measuring trunk angles during uni-planar range of motion (ROM) and cricket bowling, which involves high-speed, multi-planar movements. METHODS: For this criterion-based validity study, both MIMU systems incorporated comparable sensor specifications and employed Kalman filter sensor fusion algorithms. The MIMU based angles were compared with angles derived from concurrently captured three-dimensional retro-reflective data for 10 fast-medium bowlers. Statistical parametric mapping and root mean squared differences (RMSD) were computed for both MIMU systems. RESULTS: One-dimensional statistical parametric mapping showed no significant differences for angles from both MIMU systems when compared with retro-reflective based angle outputs. The MIMU systems produced ROM RMSDs between 1.4 ± 1.0° and 2.6 ± 1.5°. One system displayed RMSDs between 4.6 ± 1.4° and 7.4 ± 1.9° during bowling, indicating functionally relevant differences to retro-reflective derived angles. There were some small but statistically significant differences in RMSDs between the MIMU systems. SIGNIFICANCE: MIMU-based angle accuracy is poorer during high-speed, multi-planar movement than uni-planar tasks. Comparable MIMU systems can produce varying measurements during ROM and bowling tasks. It is likely that varying sample rates and sensor fusion algorithm parameters contributed to the differences.

Estimating Ground Reaction Forces from Two-Dimensional Pose Data: A Biomechanics-Based Comparison of AlphaPose, BlazePose, and OpenPose.

The adoption of computer vision pose estimation approaches, used to identify keypoint locations which are intended to reflect the necessary anatomical landmarks relied upon by biomechanists for musculoskeletal modelling, has gained increasing traction in recent years. This uptake has been further accelerated by keypoint use as inputs into machine learning models used to estimate biomechanical parameters such as ground reaction forces (GRFs) in the absence of instrumentation required for direct measurement. This study first aimed to investigate the keypoint detection rate of three open-source pose estimation models (AlphaPose, BlazePose, and OpenPose) across varying movements, camera views, and trial lengths. Second, this study aimed to assess the suitability and interchangeability of keypoints detected by each pose estimation model when used as inputs into machine learning models for the estimation of GRFs. The keypoint detection rate of BlazePose was distinctly lower than that of AlphaPose and OpenPose. All pose estimation models achieved a high keypoint detection rate at the centre of an image frame and a lower detection rate in the true sagittal plane camera field of view, compared with slightly anteriorly or posteriorly located quasi-sagittal plane camera views. The three-dimensional ground reaction force, instantaneous loading rate, and peak force for running could be estimated using the keypoints of all three pose estimation models. However, only AlphaPose and OpenPose keypoints could be used interchangeably with a machine learning model trained to estimate GRFs based on AlphaPose keypoints resulting in a high estimation accuracy when OpenPose keypoints were used as inputs and vice versa. The findings of this study highlight the need for further evaluation of computer vision-based pose estimation models for application in biomechanical human modelling, and the limitations of machine learning-based GRF estimation models that rely on 2D keypoints. This is of particular relevance given that machine learning models informing athlete monitoring guidelines are being developed for application related to athlete well-being.

Functional calibration does not improve the concurrent validity of magneto-inertial wearable sensor-based thorax and lumbar angle measurements when compared with retro-reflective motion capture.

 Magneto-inertial measurement unit (MIMU) systems allow calculation of simple sensor-to-sensor Euler angles, though this process does not address sensor-to-segment alignment, which is important for deriving meaningful MIMU-based kinematics. Functional sensor-to-segment calibrations have improved concurrent validity for elbow and knee angle measurements but have not yet been comprehensively investigated for trunk or sport-specific movements. This study aimed to determine the influence of MIMU functional calibration on thorax and lumbar joint angles during uni-planar and multi-planar, sport-specific tasks. It was hypothesised that functionally calibrating segment axes prior to angle decomposition would produce smaller differences than a non-functional method when both approaches were compared with concurrently collected 3D retro-reflective derived angles. Movements of 10 fast-medium cricket bowlers were simultaneously recorded by MIMUs and retro-reflective motion capture. Joint angles derived from four different segment definitions were compared, with three incorporating functionally defined axes. Statistical parametric mapping and root mean squared differences (RMSD) quantified measurement differences one-dimensionally and zero-dimensionally, respectively. Statistical parametric mapping found no significant differences between MIMU and retro-reflective data for any method across bowling and uni-planar trunk movements. The RMSDs for the functionally calibrated methods and non-functional method were not significantly different. Functional segment calibration may be unnecessary for MIMU-based measurement of thorax and lumbar joint angles.

A Comparison of Three Neural Network Approaches for Estimating Joint Angles and Moments from Inertial Measurement Units.

The application of artificial intelligence techniques to wearable sensor data may facilitate accurate analysis outside of controlled laboratory settings-the holy grail for gait clinicians and sports scientists looking to bridge the lab to field divide. Using these techniques, parameters that are difficult to directly measure in-the-wild, may be predicted using surrogate lower resolution inputs. One example is the prediction of joint kinematics and kinetics based on inputs from inertial measurement unit (IMU) sensors. Despite increased research, there is a paucity of information examining the most suitable artificial neural network (ANN) for predicting gait kinematics and kinetics from IMUs. This paper compares the performance of three commonly employed ANNs used to predict gait kinematics and kinetics: multilayer perceptron (MLP); long short-term memory (LSTM); and convolutional neural networks (CNN). Overall high correlations between ground truth and predicted kinematic and kinetic data were found across all investigated ANNs. However, the optimal ANN should be based on the prediction task and the intended use-case application. For the prediction of joint angles, CNNs appear favourable, however these ANNs do not show an advantage over an MLP network for the prediction of joint moments. If real-time joint angle and joint moment prediction is desirable an LSTM network should be utilised.

Understanding the determinants of stress-induced eating - A qualitative study.

The relationship between stress and food consumption is complex and often characterised by substantial between- and within-person variation. From a theoretical and practical perspective, more research is needed to improve our understanding of the factors that influence this relationship. The aim of this study was to identify those factors, and to derive insight into the nature of their effects on the relationship between stress and food consumption. Using semi-structured interviews, 41 adult participants (M ± SD age = 26.7 ± 6.3 yr, BMI = 22.9 ± 3.0 kg/m2) were invited to reflect on their food consumption following stressor exposure, and to elaborate on the factors that influence stress-induced eating behaviour. Reflexive thematic analyses revealed insight into the different ways in which individuals respond to stress in terms of food quantity and choices, and more significantly, highlighted a range of factors that may influence stress-induced eating behaviours. These factors included the intensity and/or nature of the stressor, aspects of prioritisation, rewarding, knowledge of and perceptions about food, normative (e.g., family, friend) influences, automated or habituated behaviours, the availability of food, and selected coping mechanisms. These findings present important directions for researchers seeking to study the variation in stress-induced eating, and may hold substantial practical value by way of informing interventions designed to alleviate unhealthy dietary responses to stress.

The inter-laboratory equivalence for lower limb kinematics and kinetics during unplanned sidestepping.

Much inter-intra-tester kinematic and kinetic repeatability research exists, with a paucity investigating inter-laboratory equivalence. The objective of this research was to evaluate the inter-laboratory equivalence between time varying unplanned kinematics and moments of unplanned sidestepping (UnSS). Eight elite female athletes completed an established UnSS procedure motion capture laboratories in the UK and Australia. Three dimensional time varying unplanned sidestepping joint kinematics and moments were compared. Discrete variables were change of direction angles and velocity. Waveform data were compared using mean differences, 1D 95%CI and RMSE. Discrete variables were compared using 0D 95% CI. The mean differences and 95%CI for UnSS kinematics broadly supported equivalence between laboratories (RMSE≤5.1°). Excluding hip flexion/extension moments (RMSE = 1.04 Nm/kg), equivalence was also supported for time varying joint moments between laboratories (RMSE≤0.40 Nm/kg). Dependent variables typically used to characterise UnSS were also equivalent. When consistent experimental and modelling procedures are employed, consistent time varying UnSS lower limb joint kinematic and moment estimates between laboratories can be obtained. We therefore interpret these results as a support of equivalence, yet highlight the challenges of establishing between-laboratory experiments or data sharing, as well as establishing appropriate ranges of acceptable uncertainty. These findings are important for data sharing and multi-centre trials.

Test Re-test Reliability of Single and Multijoint Strength Properties in Female Australian Footballers.

PURPOSE: To examine the test re-test reliability of isometric maximal voluntary contractions (MVC) of hip adduction (ADDISO), hip abduction (ABDISO), and multijoint leg extension (SQUATISO) in sub-elite female Australian footballers. METHODS: Data were collected from 24 sub-elite female Australian footballers (age 22.6 ± 4.5 years; height 169.4 ± 5.5 cm; body mass 66.6 ± 8.0 kg; 4.5 ± 4.4 years sport-specific training; 2.5 ± 2.0 years unstructured resistance training) from the same club on two non-consecutive days. Participants performed three isometric MVCs of ADDISO, ABDISO, and SQUATISO. The SQUATISO was performed at 140° knee flexion with a vertical trunk position and ADDISO and ABDISO measures were performed in a supine position at 60° of knee flexion and 60° hip flexion. Reliability was assessed using paired t tests and the intraclass correlation coefficient (ICC) with 95% confidence intervals (CI), typical error (TE), and coefficient of variation (CV%) with 95% CI. RESULTS: SQUATISO peak force (ICC .95; CV% 4.1), ABDISO for left, right, and sum (ICC .90-.92; CV% 5.0-5.7), and ADDISO for left, right, and sum (ICC .86-.91; CV% 6.2-6.9) were deemed acceptably reliable based on predetermined criteria (ICC ≥ .8 and CV% ≤ 10). CONCLUSION: SQUATISO, ABDISO, and ADDISO tests demonstrated acceptable reliability for the assessment of peak force in sub-elite female Australian footballers, suggesting these assessments are suitable for muscle strength testing and monitoring adaptations to training.

Perceived daily tension and food cravings and consumption: A within- and between-person investigation.

Previous research examining the relationship between negative states such as tension/anxiety and food intake has typically overlooked the naturally occurring variability of day-to-day experiences and the subsequent consequences for eating behavior. In this study, the relationship of within- and between-person perceived daily tension with food cravings and consumption was assessed. One hundred and forty-two men and women (Mage=21.3, SDage=5.3) completed a survey daily for 7 consecutive days. Levels of perceived daily tension, food cravings, and consumption were assessed. Linear and logistic mixed effect regression models were used to examine associations between tension and food cravings and consumption variables, respectively. Individuals reported greater cravings (for sweets, OR 95% CI 1.05-1.26; carbohydrates/starches, OR 95% CI 1.02-1.26; and fast foods, OR 95% CI 1.01-1.19) and consuming more carbohydrates/starches (b 95% CI 0.05-0.79) on days when they felt more tension. Individuals with higher tension had more cravings (total OR 95% CI 1.09-1.71; and specifically for sweets, OR 95% CI 1.04-1.42; and fast foods, OR 95% CI 1.15-1.54) and reported consuming more sweet (b 95% CI 0.21-1.10) and fast foods (b 95% CI 0.55-1.66). These findings suggest that greater perceived tension (both within and between individuals) is associated with increased food cravings and consumption.

Prescribing joint co-ordinates during model preparation in OpenSim improves lower limb unplanned sidestepping kinematics.

OBJECTIVES: Investigate how prescribing participant-specific joint co-ordinates during model preparation influences the measurement agreement of inverse kinematic (IK) derived unplanned sidestepping (UnSS) lower limb kinematics in OpenSim in comparison to an established direct kinematic (DK) model. DESIGN: Parallel forms repeatability. METHODS: The lower limb UnSS kinematics of 20 elite female athletes were calculated using: 1) an established DK model (criterion) and, 2) two IK models; one with (IKPC) and one without (IK0) participant-specific joint co-ordinates prescribed during the marker registration phase of model preparation in OpenSim. Time-varying kinematic analyses were performed using one dimensional (1D) statistical parametric mapping (α=0.05), where zero dimensional (0D) Root Mean Squared Error (RMSE) estimates were calculated and used as a surrogate effect size estimates. RESULTS: Statistical differences were observed between the IKPC and DK derived kinematics as well as the IK0 and DK derived kinematics. For the IKPC and DK models, mean kinematic differences over stance for the three dimensional (3D) hip joint, 3D knee joint and ankle flexion/extension (F/E) degrees of freedom (DoF) were 46±40% (RMSE=5±5°), 56±31% (RMSE=7±4°) and 3% (RMSE=2°) respectively. For the IK0 and DK models, mean kinematics differences over stance for the 3D hip joint, 3D knee joint and ankle F/E DoF were 70±53% (RMSE=14±11°), 46±48% (RMSE=8±7°) and 100% (RMSE=11°) respectively. CONCLUSIONS: Prescribing participant-specific joint co-ordinates during model preparation improves the agreement of IK derived lower limb UnSS kinematics in OpenSim with an established DK model, as well as previously published in-vivo knee kinematic estimates.

Multidimensional Ground Reaction Forces and Moments From Wearable Sensor Accelerations via Deep Learning.

OBJECTIVE: Monitoring athlete internal workload exposure, including prevention of catastrophic non-contact knee injuries, relies on the existence of a custom early-warning detection system. This system must be able to estimate accurate, reliable, and valid musculoskeletal joint loads, for sporting maneuvers in near real-time and during match play. However, current methods are constrained to laboratory instrumentation, are labor and cost intensive, and require highly trained specialist knowledge, thereby limiting their ecological validity and wider deployment. An informative next step towards this goal would be a new method to obtain ground kinetics in the field. METHODS: Here we show that kinematic data obtained from wearable sensor accelerometers, in lieu of embedded force platforms, can leverage recent supervised learning techniques to predict near real-time multidimensional ground reaction forces and moments (GRF/M). Competing convolutional neural network (CNN) deep learning models were trained using laboratory-derived stance phase GRF/M data and simulated sensor accelerations for running and sidestepping maneuvers derived from nearly half a million legacy motion trials. Then, predictions were made from each model driven by five sensor accelerations recorded during independent inter-laboratory data capture sessions. RESULTS: The proposed deep learning workbench achieved correlations to ground truth, by maximum discrete GRF component, of vertical Fz 0.97, anterior Fy 0.96 (both running), and lateral Fx 0.87 (sidestepping), with the strongest mean recorded across GRF components 0.89, and for GRM 0.65 (both sidestepping). CONCLUSION: These best-case correlations indicate the plausibility of the approach although the range of results was disappointing. The goal to accurately estimate near real-time on-field GRF/M will be improved by the lessons learned in this study. SIGNIFICANCE: Coaching, medical, and allied health staff could ultimately use this technology to monitor a range of joint loading indicators during game play, with the aim to minimize the occurrence of non-contact injuries in elite and community-level sports.

The effect of antecedent exercise on the acute stress response and subsequent food consumption: a preliminary investigation.

Physical activity has been shown to be protective against many of the deleterious consequences of stress; however, the effects of exercise on stress-induced food consumption are unclear. This study examined the effect of an acute bout of exercise prior to exposure to an acute stressor on subsequent eating behavior, together with the physiological (e.g., heart rate, blood pressure, salivary cortisol) and psychological (e.g., mood, perceived stress) responses to stress. Twenty-three men and women completed four experimental conditions (control, exercise only, stress only, and exercise prior to stress) conducted in a counterbalanced order using a within-subjects repeated measures design. Ad libitum energy intake from a laboratory test meal was assessed at each trial, together with monitoring of physiological and psychological responses. No difference in total energy intake (p = 0.146) or energy intake from 'unhealthy' foods was noted between conditions (p = 0.783), despite lower circulating ghrelin when antecedent exercise was performed compared with stress alone (p < 0.05). Exposure to an acute stressor is not necessarily associated with alterations in subsequent food intake, nor does antecedent exercise prior to stress exposure affect food choices, despite transient alterations in the hunger hormone ghrelin.

Field hockey sport-specific postures during unanticipated sidestepping: Implications for anterior cruciate ligament injury prevention.

Much research has investigated whole-body postures and associated knee joint loading during unanticipated sidestepping (UnSS). However, no research has considered sport-specific postures in field hockey. The purpose of this study was to investigate differences in trunk and lower limb angle and lower extremity joint moment waveforms during UnSS while holding a hockey stick in a flexed posture (HS-UnSS) and traditional UnSS. Additionally, we aimed to determine if differences in posture during HS-UnSS were associated with changes in knee joint moments. Twelve elite female field hockey athletes underwent 3D motion analysis during UnSS and HS-UnSS. Athletes increased trunk (0-100% of stance phase, hip (0-15%), knee (12-29%; 39-59%; 78-100%) and ankle (41-57%) flexion angles, and increased hip flexion (19-24%; 42-45%; 75-84%) and external rotation moments (75-80%) during HS-UnSS compared with UnSS (p < 0.05). Flexed postures observed during HS-UnSS did not influence knee flexion and valgus moments when compared with UnSS (p > 0.05), however knee external rotation moments reduced. Changes in trunk flexion were positively associated with peak knee internal rotation moments from UnSS to HS-UnSS (r = 0.779, p = 0.005). These findings indicate that field hockey players sidestep with significantly different techniques when holding a hockey stick, which should be considered in injury prevention training protocols.

Measurement of lower-limb asymmetry in professional rugby league: a technical note describing the use of inertial measurement units.

BACKGROUND: Quantifying lower-limb load and asymmetry during team sport match-play may be important for injury prevention and understanding performance. However, current analysis methods of lower-limb symmetry during match-play employ wearable microtechnology that may not be best suited to the task. A popular microtechnology is global positioning systems (GPS), which are torso worn. The torso location, and the summary workload measures calculated by GPS are not suited to the calculation of lower-limb load. Instead, research grade accelerometers placed directly on the lower-limb may provide better load information than GPS. This study proposes a new technique to quantify external mechanical load, and lower-limb asymmetry during on-field team sport play using inertial measurement units. METHODS: Four professional rugby league players (Age: 23.4  ± 3.1 years; Height: 1.89  ± 0.05 m; Mass: 107.0  ± 12.9 kg) wore two accelerometers, one attached to each foot by the boot laces, during match simulations. Custom Matlab (R2017b, The Mathworks Inc, Natick, MA) code was used to calculate total time, area under the curve (AUC), and percentage of time (%Time) spent in seven acceleration categories (negative to very high, <0 g to >16 g), as well as minimum and maximum acceleration during match simulations. Lower-limb AUC and %Time asymmetry was calculated using the Symmetry Angle Equation, which does not require normalization to a reference leg. RESULTS: The range of accelerations experienced across all participants on the left and right sides were 15.68-17.53 g, and 16.18-17.69 g, respectively. Clinically significant asymmetry in AUC and %Time was observed for all but one participant, and only in negative (<0 g) and very high accelerations (>16 g). Clinically significant AUC differences in very high accelerations ranged from 19.10%-26.71%. Clinically significant %Time differences in negative accelerations ranged from 12.65%-25.14%, and in very high accelerations from 18.59%-25.30%. All participants experienced the most AUC at very low accelerations (2-4 g), and the least AUC at very high accelerations (165.00-194.00 AU vs. 0.32-3.59 AU). The %Time results indicated that all participants spent the majority of match-play (73.82-92.06%) in extremely low (0-2 g) to low (4-6 g) acceleration intensities, and the least %Time in very high accelerations (0.01%-0.05%). DISCUSSION: A wearable located on the footwear to measure lower-limb load and asymmetry is feasible to use during rugby league match-play. The location of the sensor on the boot is suited to minimize injury risk occurring from impact to the sensor. This technique is able to quantify external mechanical load and detect inter limb asymmetries during match-play at the source of impact and loading, and is therefore likely to be better than current torso based methods. The results of this study may assist in preparing athletes for match-play, and in preventing injury.

By failing to prepare, you are preparing your anterior cruciate ligament to fail.

There is strong evidence linking an athlete's movement technique during sidestepping with anterior cruciate ligament (ACL) injury risk. However, it is unclear how these injurious postures are influenced by prior movement. We aim to describe preparatory trunk and thigh kinematics at toe-off of the penultimate-step and flight-phase angular momenta, and explore their associations with frontal-plane risk factors during unplanned sidestepping maneuvers. We analyzed kinematic and kinetic data of 33 male Australian Football players performing unplanned sidestepping tasks (103 trials). Linear mixed models tested for reliable associations between ACL injury risk during weight acceptance of the execution-step, with preparatory kinematics and angular momenta of the trunk and thigh during the penultimate-step. Multi-planar flight-phase trunk momenta along with hip abduction angle at penultimate-step toe-off were significantly associated with peak knee valgus moments during the execution-step (R2  = .21, P < .01). Execution-step trunk lateral flexion was significantly predicted by frontal and sagittal-plane preparatory trunk positioning at toe-off of the penultimate-step (R2  = .44, P < .01). Multi-planar flight-phase trunk momenta as well as multi-planar trunk and hip positioning at penultimate-step toe-off were associated with hip abduction during the execution-step (R2  = .53, P < .01). Preparatory positioning of the trunk and hip, along with flight-phase trunk momentum adjusting this positioning are linked to known ACL injury risk factors. We recommend that during the penultimate-step athletes maintain an upright trunk, as well as minimize frontal-plane trunk momentum and transverse-plane trunk momentum toward the sidestep direction to reduce risk of ACL injury during unplanned sidesteps.

The influence of upper-body mechanics, anthropometry and isokinetic strength on performance in wrist-spin cricket bowling.

Delivering a cricket ball with a wrist-spin (WS) bowling technique is considered one of the game's most difficult skills. Limited biomechanical information exists for WS bowlers across skill levels. The purpose of this study was to compare biomechanical, isokinetic strength and anthropometric measures between elite (12) and pathway bowlers (eight). Data were collected using a motion analysis system, dynamometer and a level-two anthropometrist. A regression analysis identified that performance was best explained by increased wrist radial deviation torque and longitudinal axis rotational moments at the shoulder and wrist. From back foot impact (BFI) to ball release (BR), elite bowlers rotated their trunks less, experienced less trunk deceleration resulting in a more front-on position and increased pelvis rotation angular velocity. They also displayed an increased shoulder internal rotation moment as the upper arm moved from external into internal rotation and was a major contributor in the subsequent differences observed in the distal segments of the bowling limb. Anthropometric differences were observed at the wrist and finger joints and may be used to form the basis for talent identification programmes. This study highlights the important contribution to bowling performance of the musculature responsible for producing long axis rotations of the bowling limb.

Foot accelerations are larger than tibia accelerations during sprinting when measured with inertial measurement units.

Accelerometers are often placed on the tibia to measure segmental accelerations, and external mechanical load during running. However, in applied sport settings it is sometimes preferable to place accelerometers on the dorsal foot to avoid tibial impact injuries. This study aimed to quantify the differences in accelerations measured at the dorsal foot compared with the distal tibia during running. Sixteen recreationally active participants performed a sprint protocol on a non-motorised treadmill. Accelerometers were positioned bilaterally on the medial tibia (TIBLeft and TIBRight), and bilateral dorsal foot surfaces (DORLeft and DORRight). Continuous acceleration signal waveform analysis was performed using one-dimensional statistical parametric mapping (1DSPM). Resultant accelerations were greater for DORLeft than TIBLeft for 60% of the gait cycle (p < 0.001) and greater for DORRight than TIBRight for 50% of the gait cycle (p < 0.003). The larger accelerations at the dorsal foot than the tibia can be explained by movement at the ankle joint, and the placement location relative to the hip. The dorsal foot location can be used to effectively measure accelerations and external mechanical load when it is not feasible to place the accelerometer on the tibia, however results between the two locations should not be compared.