Journal of Biomechanics

Perturbation training seems a promising tool to improve reactive balance in children with cerebral palsy. However, experimental evidence remains limited. In particular, little is known about how perturbation training alters muscle coordination, limiting insight into the mechanisms underlying training-induced improvements in balance control. Furthermore, it is unclear whether adaptations in balance control generalize to untrained balance tasks. Here, we investigated the effect of rotational perturbation training on reactive balance performance and reactive muscle activity during trained and untrained perturbation conditions in children with cerebral palsy and typically developing children. We performed a longitudinal intervention study in fourteen children with cerebral palsy and ten typically developing children. Reactive balance was assessed before and after the intervention using toe-up rotational and backward translational perturbations of standing balance. The training intervention consisted of nine sessions over three weeks, with each session including 96 rotational perturbations. Perturbation intensity was adapted to the participants performance level. Reactive balance performance was quantified as the ability to stay upright without stepping. Reactive muscle responses were evaluated using the co-contraction index and average muscle activity. Rotational perturbation training improved the ability of children with cerebral palsy to maintain standing balance without stepping. All children were able to perform more difficult perturbation levels after training. Muscle co-activation decreased after training in response to both trained rotational and untrained translational perturbations in children with cerebral palsy. In addition, average reactive muscle activity in both plantarflexors and dorsiflexors decreased after training in both typically developing children and children with cerebral palsy. Our findings suggest that reactive balance control can be modified through perturbation training, and that training-induced adaptations generalize to untrained perturbation conditions.

The relationship between external forces and bone strain in running is often complex and nonintuitive. We used Groucho running (i.e., running with exaggerated knee flexion) as a model to dramatically reduce the vertical ground reaction force (VGRF) and examined the relationship between peak VGRF and finite element (FE)-predicted tibia-fibula bone strain. Nine physically active males ran on an instrumented treadmill at 2.8 m/s with their preferred running technique, increased knee flexion (Groucho), and exaggerated knee flexion (Ex Groucho) in a randomized order. Strains at the tibia-fibula midshaft were calculated using computed-tomography-based FE modeling with loads and boundary conditions calculated from an inverse-dynamics based musculoskeletal model. Pressure-modified von Mises strain was used to quantify the peak strain (90th percentile strain) and strained volume (volume of bone experiencing strains above 3000 {micro}{varepsilon}). We further explored the relationship between peak VGRF, lower leg angle, and FE-predicted strain variables. The results showed that a 15.8% and 22.9% reduction in VGRF during Groucho and Ex Groucho, respectively, had no significant effect on FE-predicted peak strain (p > 0.304) and strained volume (p>0.053). Changes in peak VGRF did not correlate with FE-predicted strain variables (p>0.54) while changes in lower leg angle in the sagittal plane were moderately correlated (r>0.65; p<0.047). Our findings suggest that reductions in peak external forces do not always coincide with reductions in bone strain, especially in cases where running kinematics are dramatically altered. This work has important implications for designing gait retraining interventions based on reductions in external force measures.

Lower-limb torsional deformities have been shown to alter joint loading, although the findings vary between studies perhaps due to the simulation approaches applied. This study used predictive simulations to investigate how femoral neck anteversion (FNA) and external tibial torsion (ETT) influence hip and knee joint loading. Musculoskeletal models with altered FNA (1{degrees}-48{degrees}) and ETT (12{degrees}-53{degrees}), in isolation and combination, were created from a scaled adult model, and predictive walking (speed: 1.33 m/s) simulations were generated. Predictive simulations reproduced adaptations in hip rotation and foot-progression angle reported in individuals with torsional deformities. Hip and knee compressive, shear, and resultant contact forces were estimated, and multiple linear regressions quantified the independent associations of FNA and ETT with each outcome. Regressions accounted for 23%-86% of the variance in hip loading and 5%-87% in knee loading. FNA generally made the largest relative contribution to the variance explained in joint loading across regression models, although its associations varied in direction. Each 10{degrees} increase in FNA reduced the first hip compressive and resultant peaks by 0.076 and 0.035 BW, respectively, while hip shear force showed the largest increase, averaging 0.055 BW across both peaks. Most knee loads also increased, by up to 0.131 BW for the second resultant peak. Associations with ETT were primarily observed at the second peak. Our findings suggest that considering gait adaptations due to torsional alterations is crucial for estimating lower-limb joint loading, and prescribing joint kinematics and external forces while altering lower-limb torsion might lead to overestimation.

ObjectiveThis study investigates knee joint biomechanics during lunges under varying tibial angles and external loads using musculoskeletal modeling and finite element analysis. The goal is to provide a biomechanical basis for understanding knee loading patterns and optimizing sports training and rehabilitation. MethodsTwenty-six healthy young men performed lunges under tibial inclination angles relative to the ground (60{degrees} and 90{degrees}) and two external load conditions (bodyweight and an additional 98 N external load). Kinematic and kinetic data were captured using motion capture and force plates. Musculoskeletal models were used to estimate joint moments, range of motion, and stiffness, with data analyzed using two-way repeated-measures ANOVA. Finite element analysis was performed at 90{degrees} tibial angle to evaluate tissue stress and displacement. ResultsThe joint moment at a 60{degrees} tibial angle was much higher than at a 90{degrees}. External load showed significant effects on knee stiffness, with lower rotational stiffness in the horizontal plane (P < 0.001) and lower coronal plane stiffness at 90{degrees} (P = 0.012) under the 98 N external-load condition, indicating reduced resistance to angular displacement in these planes. Under the 90{degrees} tibial-angle condition with external load, peak stress and displacement were concentrated in the posterior horn of the meniscus, with a maximum displacement of 3.12 mm. ConclusionThe anterior tilt of the tibia increased sagittal-plane knee loading, while external load mainly reduced joint stiffness in the coronal and horizontal planes. Under the 90{degrees} loaded condition, the concentration of stress and displacement in the posterior horn of the meniscus suggests a mechanically unfavorable loading pattern rather than direct evidence of injury risk. These findings may provide useful biomechanical information for load management during lunge-based training and rehabilitation.

Most widely used lower-limb musculoskeletal models are derived from male anatomy and adapted to female participants solely by linear scaling, which may not capture sex-specific differences in pelvic and hip geometry. We developed a population-averaged, female lower-limb musculoskeletal model, built from MRI-based models of a cohort of 25 adult women using thin-plate-spline muscle-path mapping, bilateral symmetrisation, and wrapping-surface optimisation. We hypothesised that this average model, adapted to a new individual by standard linear scaling alone, would reproduce that individual's MRI-based model's walking biomechanics more closely than a linearly scaled generic male-based model. We also expected that this advantage would be concentrated in pelvis- and hip-dependent outputs rather than distributed evenly across all joints. Using 5-fold cross-validation, the scaled average-female model and the scaled male model were each compared against the held-out individual's MRI-based model across gait kinematics, joint moments, muscle moment arms, muscle forces/activations, and joint reaction forces. The average-female model outperformed the male model in every output category (Holm-corrected p [&le;] *10-5), supporting our primary hypothesis. Consistent with our secondary hypothesis, differences were largest and most sustained for pelvis tilt, hip flexion, and gluteal/adductor moment arms and forces, and smaller for knee and ankle kinematics. Some divergence remained localised to early-stance knee kinematics and patellofemoral loading. The population-averaged female musculoskeletal model is freely available on SimTK https://simtk.org/projects/aver_fem and is recommended for studies involving female participants, particularly when pelvic and hip biomechanics are the primary outcomes.

Humans tend to walk at speeds that minimize energy expenditure and time duration. While most walking experiments examine individuals in relative isolation, everyday locomotion frequently occurs in social contexts. We investigated whether walking speed is modulated in response to a social interaction during a cooperative task. Participants completed 96 randomized walking trials where they approached and retrieved boxes varying in distance (2.5-10 m) and mass (0-6.8 kg). Boxes either rested on the ground or were handed off by an experimenter, signaling prosocial effort benefitting the participant. Approach speed was measured with inertial measurement units placed at the feet and fit to a saturating exponential function of walking distance using a nonlinear mixed-effects regression model. Based on the energy-time optimization framework, we hypothesized that participants would approach more quickly when larger boxes were held at farther distances, to reduce energy and time costs of the experimenter, despite exerting more effort themselves. Participants walked 8.5% faster (1.29 m s-1 versus 1.19 m s-1; p = 3.85 x 10-6) when the largest box was held out by the experimenter versus left on the ground. However, the manner in which the box was held had no influence on approach speeds (p = 0.31). Exploratory analyses identified modest trends between experiment responses and individual characteristics, but none reached statistical significance. The findings suggest that locomotor decisions reflect not only an individuals own energy and time costs but also the perceived costs borne by others. This study demonstrates that social context can meaningfully influence walking behavior. Summary StatementHumans walk more quickly in response to the perceived energy and time others spend helping them, even at the cost of exerting more energy themselves.

Altered walking mechanics in individuals with obesity can contribute to knee osteoarthritis. The gait deviations may become more pronounced during obstacle crossing. In women, body fat distribution may further influence knee load, especially when excess fat accumulates in the thighs and hips. However, relatively little is known about how regional fat distribution affects gait in women with obesity. This study investigated how obesity and, among women, different fat distributions (Apple: more abdominal fat; Pear: more lower-limb fat) influence knee biomechanics during walking with and without obstacle crossing. Participants were 15 controls without obesity (NB) and 27 with obesity (OB). Within female participants, 10 without obesity (fNB) were compared with 20 with obesity, stratified by waist-hip ratio (Apple:10, Pear:10). Speed-adjusted statistical parametric mapping applied a general linear model (NB vs. OB) and an analysis of covariance (fNB vs. Apple vs. Pear). OB exhibited a significantly greater late-stance knee extension moment than NB across all tasks, and this difference persisted among fNB, Apple, and Pear in obstacle tasks (p<0.05). OB walked with reduced knee flexion during the early-stance leading limb after crossing a medium-height obstacle (p=0.048) and a high-height obstacle (p=0.008) compared to NB. There were significant body-shape effects (p<0.05), and post-hoc comparisons confirmed that Pear had lower knee angles than fNB in both leading-limb conditions after crossing medium- and high-height obstacles (p=0.008 and p=0.001, respectively). These findings suggest that obstacle crossing helps illuminate how excess weight influences knee biomechanics, and how regional fat distribution modulates the degree of this alteration.

Markerless motion capture offers a practical alternative to marker-based optoelectronic systems, yet validation studies have focused almost exclusively on linear gait measures. Nonlinear measures of gait dynamics, sensitive to the fine temporal structure of locomotor signals, remain unvalidated in markerless systems. This study assessed the concurrent validity of a three-camera markerless system against a 15-camera optoelectronic system across four treadmill speeds in 22 healthy adults. Inter-system agreement was evaluated for spatiotemporal parameters (mean, variability, detrended fluctuation analysis [DFA] scaling exponents) and for joint angle and trunk acceleration time series (maximum Lyapunov exponents, sample entropy, Attractor Complexity Index [ACI]). Temporal measures reached near-perfect agreement, and spatial measures showed good to excellent agreement with small speed-dependent positive biases. Sagittal-plane joint kinematic waveforms were compared using statistical parametric mapping, with root-mean-square error (RMSE) reported for significant intervals. Agreement was best at the hip, with knee and ankle showing comparable, higher error (RMSE: 1.2-3.0{degrees} hip, 3.7-5.5{degrees} knee and 3.8-5.1{degrees} ankle). ACI demonstrated moderate to good agreement across all joints and good agreement across trunk acceleration directions. Most DFA scaling exponents for step-based series supported group-level comparisons: both measures are usable for markerless assessment of gait's nonlinear dynamics. Maximum Lyapunov exponents and sample entropy showed lower absolute agreement: at the hip and knee, they preserved inter-individual ranking and remained usable for within-system group comparisons, but agreement collapsed at the ankle and for trunk sample entropy, indicating these measures still need refinement. These findings define a tiered, measure-specific scope for markerless gait analysis, extending validation beyond spatiotemporal parameters.

Balance is fundamental to mobility and independence, yet it remains difficult to measure in a way that is both clinically meaningful and feasible for widespread adoption. There is a need for more quantitative, objective, and accessible balance assessments. To this end, we created the Stanford Balance Level Evaluation (StaBLE), a battery of 18 balance-challenging tasks and accompanying digital performance metrics computed from video that aimed to capture widely ranging balance abilities across 180 participants. We validated the StaBLE score against existing clinical scales and found that it correlated with age ({rho} = -0.76, p<0.001), the Activities-Specific Balance Confidence Scale ({rho} = 0.60, p<0.001), a Mini-Balance Evaluation Systems Test task ({tau}=0.55, p<0.001), 4-Stage Balance Test ({tau} = 0.55, p<0.001), and Short Physical Performance Battery ({tau} =0.57, p<0.001). StaBLE overcame ceiling effects in these existing scales and had a different underlying distribution for those identified at risk of falling and not (KS: 0.67, p<0.001). To reduce the time it takes to perform the test, we identified subsets of balance tasks that best predicted the StaBLE score across different populations. Together, our dataset, balance assessment protocol, and performance-based score demonstrate the validity of digital measures of balance.

This study aimed to (1) establish the distance-averaged F-V relationship framework and (2) develop elasticity metrics that quantify how F-V relationship variables govern jump height and inform training prescription. Theoretical derivation and experimental validation across 108 F-V relationship models derived from 1578 jumps (countermovement jump and squat jump at three knee angles; 20 well-trained subjects) yielded a standard error of 2.1% and a nearly perfect correlation (r = 0.96, p < 0.001) between measured and predicted jump height. Four elasticity metrics were formulated: force elasticity (F_{e}), the elasticity of jump height to maximal force (F_{0}); velocity elasticity (v_{e}), the elasticity of jump height to maximal velocity (v_{0}); the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), reflecting the overall sensitivity of jump height to changes in F-V relationship variables; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the jump height response. Simulations and experiments revealed that F_{e} bore an inverse relationship to F_{0}, and v_{e} was inversely related to v_{0}, reflecting diminishing marginal returns. At a fixed jump height, simulations showed {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} and {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}} displayed a U-shaped relationship; a balanced profile ({\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=1) did not always correspond to the lowest {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}. The distance-averaged F-V elasticity framework offers a physically grounded and quantitative tool for linking F-V relationship variables directly to jump performance, providing a basis for informing individualized training decisions.

Marker-based optical motion capture remains the gold standard for kinematic analysis across biomechanical research. However, when tracking dynamic movements, severe occlusions often create missing data and noisy signals that require time-consuming manual cleaning. Existing automated methods usually rely on predefined skeleton models or need massive training datasets for machine learning solutions. This study presents the AMP: an automated marker based motion capture processing pipeline. The AMP is a fully analytical approach that uses hierarchical algorithms including 1) rigid-body constraint, 2) Kalman Filter state estimation and 3) kinematic pattern match to label markers and fill data gaps without manual human intervention. First, the algorithm identifies and removes mislabeling markers before any data scrubbing. During the data cleaning process, our hierarchical algorithm uses a translation-based step to track segments even when there are insufficient donor markers to form a full rigid body. To reconstruct missing marker trajectories, the pipeline initially uses Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation for short marker gaps. However, the PCHIP creates massive spatial errors during long occlusions, the system automatically switches to rigid-body tracking for gaps over 40 ms. Results showed the pipeline drastically reduced processing time compared to manual human expert methods by 73.5%. In addition, the AMP kept spatial errors within 10 mm of the manual ground truth. By using this combined hierarchical approach to match marker processing accuracy, the pipeline provides a fast, general-purpose tool that fully automates data cleaning and saves hours of manual effort.

The spring-loaded inverted pendulum (SLIP) model has effectively explained center of mass (CoM) and ground reaction force (GRF) dynamics during human gait despite its simplicity, describing both walking and running within the same mechanical principles. A recent study extended the explanatory capability of the SLIP model to joint dynamics by reproducing ankle joint dynamics during walking. However, during running, the model did not capture the empirical ankle torque profile, suggesting that such mechanical unification may not hold at the joint level. Because the previous model represented the body as a single point mass, it neglected leg inertia, which may become important during running as rapid motion generates substantial angular momentum. To address this limitation, we propose an extended two-mass model that separates the whole-body mass into the swing-leg and the remaining body mass, thereby explicitly incorporating swing-leg inertia into stance-leg joint dynamics. The swing leg is modeled using a linear spring and a torsional spring at the hip joint for its radial and rotational motion. Through inertial coupling, swing-leg dynamics influence the stance-leg ankle torque. Consequently, the proposed model reproduces the symmetric, single-peaked ankle torque profile observed experimentally while preserving the CoM and GRF of the previous model. These findings suggest that the discrepancy of the previous model during running may be explained by the omission of swing-leg inertia. By accounting for the gait-mode-dependent contribution of swing-leg inertia, the proposed model provides a unified mechanical framework for extending simple gait models from CoM-level behavior to joint dynamics.

Ultrasound is commonly used to assess structural changes in symptomatic Achilles tendons, but quantitative biomechanical metrics for progressive tendon deterioration remain limited. The goal of this study was to develop and validate an automated ultrasound tracking algorithm for regional tendon deformation and evaluate strain progression in survived and ruptured tendons during fatigue loading. We hypothesized that maximum strain, average strain, and strain heterogeneity would exhibit different trajectories between groups. Ten cadaveric Achilles tendons underwent cyclic loading with stress tests every 500 cycles until rupture or 150,000 cycles. Ultrasound images acquired during stress tests were analyzed using an automated tracking algorithm to generate spatially resolved regional strain fields. Ultrasound-derived bulk strain was highly correlated with actuator-derived strain in survived (R^2 = 0.968 +/- 0.017) and ruptured tendons (R^2 = 0.972 +/- 0.014). Maximum and average longitudinal strains progressively diverged between groups across fatigue life (Group x FatigueLife: p = 0.003 and p < 0.0001, respectively). During the first 10,000 cycles, average strain decreased in survived tendons ({beta} = -0.0268%, p = 0.0215) but not ruptured tendons ({beta} = 0.0147%, p = 0.1197), with a significant Group x Cycle interaction (p = 0.0061). This study demonstrates that the algorithm quantified Achilles tendon deformation with high fidelity and enabled spatially resolved strain assessment throughout fatigue loading. Maximum and average strain followed different trajectories between groups, whereas strain heterogeneity did not. Early differences in tendon biomechanics suggest that regional strain behavior may change before pronounced differences in absolute magnitude develop.

Purpose: Identifying head impacts linked to brain injury in sport remains challenging. Instrumented mouthguards quantify head-impact kinematics, and finite element (FE) modelling can transform these data into brain strain estimates, which may better reflect injury risk than kinematics alone. Here, we examined associations between mouthguard-measured kinematics, FE-derived strain, and plasma brain injury biomarker GFAP following head impacts. Methods: We analysed 41 video-verified impacts from male Australian football players, including 22 assessed for concussion (17 diagnosed) and 19 unassessed. Instrumented mouthguards recorded peak linear acceleration (PLA), peak rotational acceleration, and peak rotational velocity (PRV). Brain strain was estimated using the Imperial College FE brain model, and plasma GFAP was quantified using Simoa. Biomechanical-GFAP associations were examined using Spearman correlations and segmented regression. Results: For impacts overall, plasma GFAP was moderately correlated with PLA ({rho}=0.46, 95% CI: 0.20-0.66), PRV ({rho}=0.53, 95% CI: 0.20-0.78), and strain ({rho}=0.60, 95% CI: 0.32-0.80). Associations were stronger within concussion cases for strain ({rho}=0.86, 95% CI: 0.58-0.97) and PRV ({rho}=0.64, 95% CI: 0.15-0.93). Piecewise regression identified strain levels above which strain-GFAP relationships steepened across the whole-brain and brainstem. In concussion cases, supra-threshold brainstem strain was associated with greater symptoms. Conclusion: Finite element brain strain may better predict brain injury risk following a sport-related head impact than peak acceleration metrics. Stronger associations with plasma GFAP, particularly among concussion cases, and evidence of a biomechanical threshold, support the use of biomarker-informed strain measures in future risk modelling and the development of brain injury screening thresholds.

Objective: Rotator cuff tears involving the supraspinatus tendon are a common cause of shoulder pain. Ultrasound (US) is accessible, dynamic, and lower cost than MRI, but diagnostic performance may vary by tear severity, operator expertise. This systematic review and meta-analysis compared the US with MRI for supraspinatus tear detection. Methods: MEDLINE, Embase, Scopus, and CINAHL Plus were searched for studies published from January 2015 to June 2026. Study quality was assessed using QUADAS-2. Diagnostic outcomes included sensitivity, specificity, accuracy, PPV, NPV. Meta-analyses were performed separately for any, partial-thickness, and full-thickness tears when complete 2 x 2 data were available. Results: 23 studies comprising 1,452 participants were included. US demonstrated stronger and more consistent performance for full-thickness than partial-thickness tears. Mean sensitivity, specificity, and accuracy were 88.5%, 95.2%, and 93.4%, respectively, for full-thickness tears, compared with 71.5%, 91.5%, and 79.2% for partial-thickness tears. HSROC analysis showed pooled sensitivity and specificity of 96% and 76% for any tear, 94% and 80% for partial-thickness tears, and 96% and 98% for full-thickness tears. Agreement measures also generally favored full-thickness tears. Operator expertise, study quality varied, and only one study evaluated a handheld ultrasound system. Conclusion: Ultrasound demonstrates strong diagnostic performance for supraspinatus tears, particularly full-thickness tears, while partial-thickness tears remain more challenging. Given the high observed sensitivity, well-performed US may serve as a practical first-line modality to rule out full-thickness tears, with MRI remaining complementary for equivocal partial-thickness tears, associated pathology, and preoperative assessment.

The metabolic cost of walking is widely used to evaluate human performance and effectiveness of clinical interventions. Decades of laboratory research, largely based on treadmill experiments, have established a canonical relationship between walking speed and metabolic cost, and suggested that ageing shifts this relationship upward, implying reduced efficiency in older adults. However, this relationship has not been well tested during overground walking across matched speeds. We compared healthy younger (n=16; 26{+/-}2yr) and older (n=11; 74{+/-}3yr) adults across eight outdoor overground walking trials at different speeds: preferred walking speed (PWS), three fixed speeds (0.8, 1.2, 1.6 m{middle dot}s-{superscript 1}), and four speeds at {+/-}5% and {+/-}10% of PWS. Contrary to our hypothesis, older adults did not show higher gross or net metabolic cost of walking (GCOW and NCOW) than younger adults at any speed; rather, both trended consistently lower in older adults, reaching significance for GCOW at 0.8 m{middle dot}s-{superscript 1} only. Comparisons of resting metabolic rate and respiratory exchange ratio to prior reference groups did not indicate that our older cohort was unusually fit. Independent of age, GCOW was significantly higher at 0.8 m{middle dot}s-{superscript 1} than at the remaining speeds (1.2-1.6 m{middle dot}s-{superscript 1}), confirming that walking at slower speeds increases GCOW. These findings challenge the view that ageing intrinsically increases the energetic cost of walking, suggesting instead that previously reported upward shifts in cost may reflect treadmill-specific constraints or speed effects. Future work is needed to explore direct comparisons of outdoor, overground walking with treadmill walking at fixed speeds in both younger and older adults.

Introduction: Knee muscle coactivation is elevated after anterior cruciate ligament reconstruction (ACLR), contributing to altered joint loading and post-traumatic osteoarthritis. Existing methods average coactivation within predefined gait phases and require priori designation of muscles roles, limiting the resolution for when differences occur. Objective: Characterize knee joint coactivation and dynamics throughout gait in individuals with ACLR using statistical parametric mapping. Methods: Ten individuals with unilateral ACLR and ten healthy matched controls performed overground walking at their preferred speed, while kinematics, kinetics, and electromyography of the quadriceps, hamstring, and gastrocnemius muscles were recorded. Coactivation was quantified using time-varying, multi-muscle coactivation, and was compared using a one-tailed statistical parametric mapping (SPM) t-test. Knee joint angle, angular speed, and moment were compared using SPM Hotelling's T2 tests with Bonferroni-adjusted post hoc comparisons (= 0.05). Results: Coactivation was greater in the ACLR group at 0.01%-6.14%, 35.23%-40.94%, 69.73-71.99%, 72.12-77.31%, 77.89-78.05%, and 94.63%-95.87% (p < 0.0001) of stride. The ACLR group also demonstrated greater knee internal-external rotation angle at 0.01%-47.34%, 52.14%-61.87%, and 66.47%-100% (p <0.0001) and lower knee flexion angle at 55.79%-65.93% (p = 0.004) of stride, than healthy controls. Finally, a smaller knee flexion-extension moment was observed in the ACLR group at 57.43%-62.18% (p = 0.005) of stride. Conclusions: Coactivation after ACLR is elevated at loading response, late mid-stance, terminal stance and early push-off phase. Greater coactivation was observed during weight-acceptance phases, whereas lower knee moments characterized initial swing. These alterations are localized rather than uniformly distributed, supporting phase-targeted rehabilitation.

Ankle stiffness is decreased during movement compared to posture; however, the etiology of this decrease remains unknown. Determining what gives rise to this decrease is critical for understanding how humans successfully interact with their physical world and how that ability is compromised by functional impairments. While the triceps surae and Achilles tendon primarily dictate ankle stiffness, the relative contributions across posture and movement remain unknown. Therefore, our study sought to quantify the relative contributions of the muscle and tendon to ankle stiffness and how those contributions differ between posture and movement. We used our technique, which combines B-mode ultrasound imaging with joint-level perturbations, to quantify ankle, muscle, and tendon stiffness simultaneously. Since ankle, muscle, and tendon stiffness all scale with torque, participants matched torque between posture and movement tasks. During posture, the Achilles tendon is the dominant contributor to ankle stiffness. However, during movement, the triceps surae and Achilles tendon contribute more equally to ankle stiffness, which can be attributed to a significant decrease in muscle stiffness during movement. Here, we provide the first empirical data on how state-dependent properties of the triceps surae and Achilles tendon contribute to ankle stiffness in conditions relevant to locomotion.

Background: Newly available arm angle data offers a new dimension to understand rising rates of arm injury in MLB pitchers. Purpose: To evaluate the relationship between arm angle, pitch characteristics, and elbow and forearm injury in MLB pitchers.<br><br> Study Design: Retrospective cohort study; Level of evidence, 3 Methods: Statcast data from 2020 to 2025 and MLB injured list (IL) data were used to evaluate arm angle and pitch characteristics in relation to elbow and forearm injuries. Results are presented with and without requirements on prior season workload and for same-season and next-season injury incidence. A generalized additive model (GAM) was used to capture non-linear dependence and interactions between selected features and injury incidence to the elbow or forearm. Average marginal effect (AME) odds ratios are reported for main effect terms. Results: N = 3,812 pitcher-seasons were included. 29% pitchers who underwent UCLR did so in the same season as a forearm injury (tmean=44, tmedian=27 days to surgery). Arm angle, fastball usage, and their interaction were the three most predictive features. Arm angle was positively related to incidence of injury (ORmeanAME=1.014), fastball usage was inversely related to incidence of injury (ORmeanAME=0.243), and arm angle moderated the effect fastball usage at high arm angle, where increased usage was no longer protective. Slider velocity (ORmeanAME=1.072), spin rate (ORmeanAME=1.001), and usage (ORmeanAME=2.039) also significantly predicted injury risk. Fastball velocity was not significant in any fit, with ORmeanAME=0.999 across all fits. Fit-level Nagelkerke R2 values ranged from .019 to .052. Conclusion: Fastball usage and arm angle, not velocity, predicted elbow and forearm injury risk among MLB pitchers, and arm angle was the single most predictive feature. The heterogeneity of risk factors as a function of arm angle, and the novelty of MLB arm angle data, may explain why fastball usage has been previously underexplored as a risk factor. Keywords: baseball; arm angle; fastball velocity; fastball usage; spin rate; UCL; ulnar collateral ligament; elbow injury; forearm injury; Statcast

Adolescent idiopathic scoliosis (AIS) alters spinal geometry and may influence the biomechanical response of the spine during functional postures. However, posture-dependent changes in spinal loading and paraspinal muscle forces in AIS remain poorly understood. This study investigated the effects of trunk posture on intervertebral loading and paraspinal muscle forces using a subject-specific musculoskeletal model of an adolescent with AIS. The spinal deformity was reconstructed from biplanar radiographs and incorporated into a full-body musculoskeletal model. Flexion, extension, lateral bending, and axial rotation were simulated at three incremental magnitudes, with motion distributed across the thoracolumbar spine. Intervertebral compressive and lateral forces around the curve apex and forces in the erector spinae (ES) and multifidus (MF) muscles were evaluated. Trunk flexion produced the greatest compressive loading, reaching 337 N at the curve apex and 372 N two levels below the apex at 30{degrees} flexion. Lateral bending produced pronounced direction-dependent loading: concave-side bending increased lateral forces, whereas convex-side bending increased compressive forces. Axial rotation produced similar but smaller direction-dependent changes. Paraspinal muscle forces were consistently asymmetric, with concave-side dominance of the ES and convex-side dominance of the MF. Flexion and convex-sided movements generally produced greater muscle imbalance, while increasing posture magnitude amplified spinal loading and muscle forces. These findings demonstrate that trunk posture, movement direction, and magnitude substantially influence the biomechanical environment of the scoliotic spine and should be considered when evaluating spinal mechanics in AIS.