Computer Methods in Biomechanics and Biomedical Engineering

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

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.

Finite element (FE) head models are virtual tools to study brain biomechanics and their predictions must be numerically convergent. Previous convergence studies focused on the influence of mesh size, but the potential effect of element formulation on model convergence was often ignored. To address this, one original model with brain mesh size as 6.4 {+/-} 1.9 mm was modified to generate three derivatives with the same mesh topology but different element sizes, i.e., a coarse model (mesh size: 12.2 {+/-} 3.9 mm), a medium model (mesh size: 3.2 {+/-} 1.0 mm), and a fine model (mesh size: 1.6 {+/-} 0.5 mm). Three commonly used element formulations, i.e., reduced integration, selectively reduced (S/R) integration, and full integration, were implemented to the brain elements. These models were subjected to rotational loadings along the axial, coronal, and sagittal axes, respectively. The maximum relative displacement at representative sites and 95th percentile maximum principal strain at the whole brain level were used to evaluate mesh convergency. The results showed that the S/R integration yielded a 5% difference between the original and medium meshes, while the reduced and full integration revealed a difference over 5% even between the medium and fine meshes. This study verified that the mesh convergence of FE brain models is affected by the choice of element formulation and the S/R integration contributes to the fastest convergence behavior than the reduced and full integrations. It provided practical information on how to develop numerically convergent and computationally efficient FE brain models. HighlightsO_LIThis study verifies that the choice of element formulation affects the mesh convergence behavior of finite element brain models C_LIO_LIThis study finds the selectively reduced integration yields the fastest convergence behavior than the reduced and full integration C_LIO_LIThis study provides practical guidance on the choice of mesh density and element formulation on how to develop numerically convergent and computationally efficient finite element brain models. C_LI

Repetitive low-intensity blast (LIB) exposure has been identified as a probable cause of mild blast-induced traumatic brain injury (mbTBI) and a chronic injury risk to U.S. military personnel. However, the human brains biomechanical response to this loading regime remains poorly characterized. Using blast-exposure-validated 3D models of human anatomy, we simulated the intracranial tissue response to blast pressure typically experienced by Warfighters during weapons training. Two scenarios were evaluated, a single-dose exposure and a repetitive-dose exposure, to study intracranial pressure (ICP), shear strains, and spectral content. Ansys LS-DYNA was used to generate planar blast waves with peak overpressures of 4-90 kPa and positive phase durations of 2.2-10 ms. Single exposures produced ICP ranging from 4.7-112.7 kPa, dependent on dose and positive phase duration. Under repetitive LIB exposure, peak ICP increased by 8-26% relative to single exposures, with an increase of high-frequency components (>2 kHz). These results demonstrate that LIB can produce measurable intracranial responses that are amplified through repetition, producing pronounced spectral content and elevated pressures despite low strain levels. This study underscores the need to further investigate cumulative dose effects and the value of computational approaches to clarify hypothesized mbTBI mechanisms in operationally relevant conditions.

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.

Despite the use of technological countermeasures, studies show that the sensory conflict, and thus symptoms of motion sickness such as nausea, cannot be completely prevented while traveling as a car passenger. Accordingly, reliable prediction of motion sickness will represent a possible solution for intelligent vehicles to avoid the abortion of the drive, e.g., through adapted driving strategies or route planning. In previous works, the authors were able to demonstrate an application-oriented parameter set for the popular 6DOF-SVC model to estimate motion sickness incidence (MSI) in passengers with a lowered gaze on a non-driving-related task. In the current study, these parameters were validated and further optimized using five previous conducted motion sickness driving experiments. For the first time, it is also shown that the expected natural MSI fluctuations based on the driving dynamic profile, due to route characteristics or driving style, as well as the variation in experimental determined MSI is approximately 10%. Moreover, findings indicate that the participants appear to have an individual MSI threshold that correlates with their susceptibility to motion sickness, however, this threshold fluctuates too strongly across experiments to be suitable for practical application. As a result, the model can successfully estimate motion sickness risk across the test tracks, however, inaccuracies in the predicted MSI trajectories remain.

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.

Objective: To evaluate quantitative gait analysis in a sheep model (Ovis aries) of in-utero spina bifida repair. Method: Using a 3D marker-based motion capture system, we quantified spatiotemporal gait parameters and hindlimb joint angles in a sheep model of in-utero spina bifida repair and normal controls. A linear support vector machine classifier, trained and tested on subject-disjoint partitions with individual gait cycles as the unit of analysis, evaluated the relationship between hindlimb joint angles and clinician-assigned Texas Spinal Cord Injury Scale scores. Linear mixed-effects models compared spatiotemporal parameters, hoof height, and hip drop across 3- to 6-month evaluations and between groups. Results: In treated (n=14) and control (n=3) lambs, front- and hindlimb gait speed differed by timepoint (both p=0.025). Across 1,632 left and 1,661 right hindlimb gait cycles, held-out classification accuracy was 85.9% and 88.6% (Cohen's {kappa}=0.78 and 0.84) for left and right hindlimbs, respectively, against majority-class proportions of 76.5% and 75%. Left hindlimb hip drop differed between treated lambs and controls ({Delta}=0.8 cm, p=0.027). Between-group contrasts were considered exploratory given the small control group. Conclusion: Quantitative gait analysis was feasible in an in-utero spina bifida repair model. Hindlimb kinematic profiles classified clinical ambulation scores above the majority-class baseline.

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.

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.

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.

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.

Background: Cerebral autoregulation stabilizes cerebral blood flow over a range of cerebral perfusion pressures, but the precise shape of the pressure-flow relationship remains debated. The classical triphasic pressure-flow relationship was recently challenged by experiments demonstrating a quadriphasic response, hypothesized to arise from vessel-size-dependent pressure-diameter responses. We tested this hypothesis and investigated whether these size-dependent responses originate from heterogeneity in smooth muscle cell (SMC) abundance, SMC behavior, or neither. Methods: We developed a computational multi-scale physics-based model of cerebral autoregulation linking SMC activity to vessel-scale diameter regulation and organ-scale blood flow. Four scenarios were evaluated: passive vessels, homogeneous SMC abundance and behavior, heterogeneous SMC abundance, and heterogeneous SMC behavior. Predicted pressure-diameter responses and pressure-flow relationships were compared across scenarios and against experimental observations. Results: In contrast to passive vessels, homogeneous SMC activation produced partial flow stabilization, highlighting the key role of SMCs in autoregulation. However, only heterogeneous SMC behavior reproduced the experimentally observed vessel-size-dependent trends in pressure-diameter responses. This scenario also showed the best agreement with the experimental organ-scale pressure-flow relationship (R-squared = 0.93, nRMSE = 5.96%). Conclusion: The model suggests that vessel-size-dependent SMC behavior underlies vessel-size-dependent pressure-diameter responses and shapes the relationship between cerebral perfusion pressure and cerebral blood flow.

Devireddy et al. [1] previously showed that an enthalpy-based, macroscale model simulated tissue freezing histories are in close agreement with a coupled model incorporating cellular water transport and intracellular ice formation (IIF). That comparison, however, was performed for a limited set of tissue geometries, cooling conditions, and biophysical parameters. Here, we revisit that conclusion by reimplementing the published model from its governing equations and systematically expanding the parameter space to determine when microscale processes alter the predicted macroscale freezing response. We incorporate both surface catalyzed nucleation (SCN) and volume catalyzed nucleation (VCN) of intracellular ice with cellular osmotic dehydration and examine a broad range of tissue dimensions, cooling rates, convective boundary conditions, membrane permeabilities, cell sizes, activation energies, intracellular water fractions, and nucleation rates. Linearization of the cellular water transport equation about osmotic equilibrium yields an osmotic relaxation timethat can be compared with the local residence time of tissue undergoing phase change. Their ratio defines a dimensionless group, that organizes the transition between regimes in which the uncoupled enthalpy formulation and the coupled micro and macroscale formulation produce similar or substantially different results. Across the one-dimensional parameter space examined here, the two models remain within a prescribed thermal-error bound for the dimensionless group below approximately 0.1, whereas the discrepancy increases systematically above this threshold. Model divergence also depends on intracellular ice nucleation, i.e., when nucleation is sufficiently slow, cellular water transport can become rate limiting for latent heat release. Conversely, sufficiently rapid intracellular ice formation reduces the macroscopic discrepancy by providing an additional pathway for latent-heat release. Multidimensional simulations further show that geometry alone can move a nominally conventional freezing protocol into the coupled regime. In particular, multidirectional cooling can reduce the local residence time sufficiently to produce substantial differences in predicted frozen volume even when the corresponding thermal histories appear similar. Finally, we formulate an inverse approach for estimating IIF parameters from tissue scale thermal histories. Synthetic simulations indicate that parameter recovery is feasible within a finite range of cooling conditions, providing a testable strategy for future experimental measurements. Together, these results provide a mechanistic criterion for deciding when microscale biophysical processes must be retained in macroscale tissue-freezing models.

Background: Adults post hemiparetic stroke exhibit motor deficits in both the trunk and arm that impact function. In the paretic arm, involuntary coupling of torques in the fingers, wrist, and elbow during shoulder abduction, known as the flexion synergy, reduces reaching function. While there have been deficits shown to exist at the trunk such as weakness and altered coordination, it remains unclear if active trunk control compounds reaching deficits. This study examined if active trunk control with progressive shoulder abduction loading impacts reaching function in stroke and control participants. Methods: Thirteen adults, 9 post hemiparetic stroke (64.11 {+/-} 6.57 years) and 4 age matched controls (66.25 {+/-} 0.96 years), completed seated reaching tasks with the trunk restrained and unrestrained while reaching with their arm coupled to the ACT-3D robotic device on a frictionless table, lifting against 25% MVT, and 50% MVT. A linear mixed effects model was used with limb as a random factor, and group, trunk restraint, and shoulder abduction load as fixed factors for quantifying changes in reaching distance expressed percent limb length (% LL). Findings: Across limbs (paretic, non-paretic, control), when the trunk was un-restrained, reaching distance was reduced (p<.05). Further reduction in reaching distance was observed in the paretic compared to the non-paretic and control (p< .05) limbs. Reaching velocity was fastest for controls (3.26 {+/-} 1.52 m/s) compared to non-paretic (3.24 {+/-} 1.19 m/s) and paretic (1.59 {+/-} 1.32 m/s) limbs in stroke. Shoulder abduction loading had an effect on reaching distance in the paretic limb (p<.05) Table: .83 {+/-} .13 % LL, 25% MVT: .77 {+/-} .14 % LL, 50% MVT: .76 {+/-} .15 %LL). Greater shoulder excursion occurred during non-paretic limb reaching compared to the paretic limb with an increase of 14.80 mm (p<.05). Conclusion: Active trunk control impacted reaching function and further reduced reaching distance in chronic hemiparetic stroke participants. However, the primary driver of reduced reaching distance was the flexion synergy. While reaching speed increased the demand at the trunk, excursions were comparable during paretic and non-paretic limb reaching, suggesting that overall trunk function was intact during this paradigm.

OBJECTIVE: To describe (1) US emergency department-treated pickleball injury burden and the injury-to-participation measure among total players, with burden among adults aged 60 to 79 years as a descriptive subgroup, and (2) determine whether general internet search interest for 'pickleball' is also associated with total pickleball-related injuries. DESIGN: Ecological time series study, United States, 2014 to 2023. DATA SOURCES: National Electronic Injury Surveillance System (NEISS) emergency department microdata yielded 1,738 adjudicated pickleball cases, 921 of them orthopedic, weighted to an estimated 101,450 injuries nationally. Google Trends, English Wikipedia pageviews, and GDELT news volume served as general pickleball attention signals, with the Trends index for 'sourdough' as a negative control. Sports and Fitness Industry Association (SFIA) participation estimates supplied a total player denominator. MAIN OUTCOME MEASURES: Annual national injury estimates with design-based 95 percent confidence intervals; injury-to-participation measures; and correlations between total pickleball-related injuries and general pickleball attention signals before and after removing trend and seasonality. RESULTS: Estimated emergency department-treated pickleball injuries rose 17.5-fold, from 1,391 in 2014 (highly unstable) to 24,294 in 2023. 70 percent of adjudicated cases involved adults aged 60 to 79. During 2017-2023, injury estimates rose 4.0-fold and participation rose about 4.4-fold. No temporal trend was detected in the injury-to-participation measure (P=0.59). Search interest looked like an excellent proxy: in annual levels it correlated with total pickleball-related injuries at R=0.96, and Pickleball Wikipedia pageviews at R=0.98. However, so did searches for "sourdough", at R=0.76. Removing trend and seasonality left little (monthly residual R=0.084; year-on-year R=0.28 over 96 months, 2015-2023), and the seasons ran opposite, with injuries peaking in February and searches in July, such that, on 12-month mean profiles, the sourdough negative control fitted the injury season (R=0.96) while pickleball ran against it (R=-0.40). General pickleball search interest and pickleball news coverage remained correlated in year-on-year changes in 2017-2023 (R=0.64), whereas their corresponding correlations with total pickleball-related injuries in 2017-2023 were 0.25 and 0.20. CONCLUSIONS: The absolute burden of emergency department-treated pickleball injury has grown substantially, but the available surveillance data cannot resolve whether the sport has become more hazardous per participant. The observed rise is consistent with growth in exposure alone. The strong correlation between search interest and injury counts was not specific, the association was substantially attenuated after detrending, and the seasonal patterns were opposed. These descriptive results do not establish that search interest can substitute for injury surveillance, and series that rise together should not be assumed to be related.

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.

This study presents a physiologically detailed biomechanical model of the mouse distal forelimb that incorporates intrinsic musculature, tendon routing, and digit-level skeletal anatomy, features simplified or omitted in existing musculoskeletal models. Using high-resolution anatomical reconstruction and computational modeling, we created a physiological representation of the wrist and digits capable of simulating complex forelimb movements. The model enables simulation of coordinated distal forelimb movement and digit-level muscle behavior during grasping-related tasks. Simulations were performed for multiple tasks, including grasping, grasping with supination, wrist flexion, and digit I flexion, with analysis focused on the grasping task due to its integration of both intrinsic and extrinsic musculature. Model performance was evaluated through comparisons of marker trajectories between torque-driven reference motion and muscle-driven simulations, temporal shuffle control, and comparisons between experimentally recorded electromyography (EMG) activity and model-predicted muscle excitation profiles. The model successfully reproduced coordinated distal forelimb kinematics, demonstrated strong agreement between torque-driven and muscle-driven simulation approaches, and generated physiologically plausible muscle excitation patterns consistent with experimentally observed EMG activity during grasping-related movement. These findings establish the model as a framework for studying fine motor control, neuromuscular coordination, and movement-related impairments in mice while providing a foundation for future investigation of neurological disorders and their underlying biomechanical mechanisms.

Classical neuronal cable theory relies on quasi-static electric field approximations and neglects magnetic induction, Lorentz force coupling, and transient electromagnetic currents, limiting its ability to fully characterize action potential propagation within geometrically branched axons and dendrites. This work develops a coupled Maxwell-electromagnetic cable framework by integrating finite-difference time-domain (FDTD) solutions of Maxwells equations with extended Hodgkin-Huxley and Fitzhugh-Nagumo membrane dynamics, incorporating magnetic gating perturbations, electromagnetic trans-membrane currents IEM, and nanoscale quantum corrections for thin neural segments. Controlled propagation experiments are designed to quantify deviations from standard cable predictions across asymmetric and symmetric axonal bifurcation geometries. Numerical results demonstrate that inductive magnetic effects lower the critical branch radius for junction conduction failure and break symmetric action potential invasion in geometrically identical child branches under external transverse magnetic fields. An electromagnetic corrected geometric ratio GREM is proposed to revise impedance-matching conditions at branch points, accounting for size-dependent axial current imbalance induced by magnetic and displacement currents. Parent axon conduction velocity deviates substantially from the canonical [Formula] scaling law when electromagnetic feedback and quantum charge distributions are included, triggering early signal blockage at large cable diameters. Collectively, this study establishes that quasi-static cable models underestimate electromagnetic corrections to propagation speed, waveform shape, and bifurcation transmission fidelity; the coupled Maxwell-cable framework provides a comprehensive multi-physics tool for modeling electrodynamic signal behavior in complex neuronal architectures.

Computational models of the middle ear are typically developed within the linear range of the middle ear's response, which corresponds to typical sounds in daily life. Understanding middle-ear biomechanics under high-intensity sounds is also important for assessing potential auditory damage under adverse conditions. In this study, a finite-element (FE) model of the human middle ear plus the external ear canal is presented, employing a first-order Ogden hyperelastic material formulation and time-domain nonlinear analysis to capture nonlinear deformation of soft tissues and the resulting middle-ear response. The model was analyzed using pure-tone pressure excitations applied at the ear canal entrance over the 80 Hz to 8 kHz frequency range and 110 to 180 dB sound pressure levels (SPL). The ear canal pressure near the tympanic membrane (TM) and full-field three-dimensional response of the middle ear structures were examined. Across the investigated frequency range, the simulated middle-ear motion exhibited a transition from predominantly piston-like behavior at low frequencies, up to 1 kHz, to increasingly intricate multi-modal and multi-directional vibration patterns at higher frequencies. Nonlinear behaviors became increasingly significant at high frequencies and high stimulus levels, including compressive/expansive pressure-displacement relationships, waveform distortions, and the emergence of non-harmonic spectral components. The model developed in this study provides a computational framework for studying nonlinear sound transmission through the middle ear and its implications for high-intensity acoustic exposure. The findings contribute to a better understanding of middle-ear mechanics under adverse conditions and support future investigations of acoustic trauma and hearing protection strategies.