Journal of Biomechanics

ContextClinical assessments of landing mechanics often require complex scoring systems or laboratory-based motion analysis, which can limit feasibility in routine practice. A visually based landing-mechanics score centered on a standardized optimal joint-alignment configuration ("Zero Position") may offer a simple, clinically deployable alternative. ObjectiveTo determine the intra- and inter-rater reliability of a landing mechanics score based on standardized optimal joint alignment at the moment of maximal center-of-mass (COM) descent. DesignCross-sectional reliability study. SettingUniversity athletic training facility. Patients or Other ParticipantsNinety healthy male collegiate athletes. Main Outcome MeasuresLanding mechanics were evaluated using frontal- and sagittal-plane video recordings, with scoring performed on the frame corresponding to maximal COM descent. Five criteria reflecting the standardized joint configuration ("Zero Position") were assessed. Intra- and inter-rater reliability were calculated using Cohens kappa coefficients and Kendalls W. ResultsAll five criteria demonstrated moderate to substantial intra-rater reliability and moderate to almost perfect inter-rater reliability. The total landing-mechanics score showed excellent agreement across all comparisons. The scoring system required minimal training and was feasible to implement using standard video recordings. ConclusionsThe landing-mechanics score centered on the Zero Position demonstrated high reliability and strong clinical feasibility. This simple, visually grounded assessment may support routine clinical screening, injury-risk evaluation, and return-to-sport decision-making. Future research should examine its applicability to single-leg landings and sport-specific high-risk movements.

Walking on sloped terrain requires substantial mechanical and control adaptations for effective energy management compared to level ground locomotion. The Virtual Pivot Point (VPP) hypothesis explains sagittal plane angular momentum regulation during level walking, but its validity in slope walking remains unexplored. This study combines human experiments with template-model simulations to investigate how the VPP strategy is modulated during slope walking. Participants walked on an instrumented ramp at various inclinations (0{degrees}, {+/-} 7.5{degrees}, {+/-} 10{degrees}), while a 2D spring-loaded inverted-pendulum model with a trunk segment simulated the task. Experimental results confirmed that the VPP is a robust feature of slope walking (R2 > 0.975). The simulation reproduced the change in hip torque and trunk adaptations by modulating VPP position. Results of this study indicate that VPP position and trunk dynamics could afford stability and energy management on gentle slopes, but to robustly navigate steeper ramps, humans recruit a multi-joint strategy where the knee and ankle joints play a crucial role in managing the energetic demands of sloped terrain. Beyond advancing our understanding of locomotor control, these insights have practical implications for the design of exoskeletons that adapt to uneven terrain.

BackgroundPersonalized computational neuromusculoskeletal models have great potential for optimizing the design of clinical treatments for movement impairments. While many software tools address specific parts of the model personalization and treatment optimization processes, they typically require significant programming experience to use and do not cover the full breadth of these two processes. Furthermore, published neuromusculoskeletal modeling studies typically do not provide all of the minute methodological details needed for others to reproduce the work. Consequently, researchers seeking to develop skills in the model personalization and treatment optimization processes face a steep learning curve due to the lack of detailed training materials that demonstrate both processes for real-life clinical problems using real-life subject movement data. MethodsThis article presents detailed training tutorials for the model personalization and treatment optimization processes using two real-life clinical problems and the Neuromusculoskeletal Modeling (NMSM) Pipeline. The first clinical problem involves the design of personalized gait modifications and high tibial osteotomy surgery for an individual with bilateral medial knee osteoarthritis, where the goal is to reduce the peak adduction moment in both knees to a specified target level. The second clinical problem involves the design of a synergy-based functional electrical stimulation prescription for an individual post-stroke with impaired walking function, where the goal is to equalize the propulsive and braking impulses between the two legs. Both tutorials were evaluated as course projects given to novice users in a combined undergraduate/graduate mechanical engineering course. ResultsBoth tutorials produced personalized neuromusculoskeletal models and associated dynamically consistent tracking optimizations that closely reproduced subject-specific experimental joint angles, joint moments, ground reaction forces and moments, and (if applicable) muscle activations measured during walking. Subsequent design optimizations predicted personalized treatments that achieved target values of peak knee adduction moments or propulsive and braking impulses. ConclusionsThe detailed step-by-step tutorials presented with this article are the first to walk users step-by-step through the entire process of creating personalized neuromusculoskeletal models and then using them to design personalized treatments for clinical problems. These tutorials can be used to introduce new users to the NMSM Pipeline and as projects in neuromusculoskeletal modeling courses.

Vertical ground reaction force (vGRF) profiles during walking typically exhibit a double-peaked structure with a mid-stance trough, yet the mechanical conditions governing this morphology remain incompletely defined. In this study, we examined how the balance between push-off and collision impulses during the step-to-step transition influences the temporal and structural characteristics of the vGRF trajectory. Empirical relationships describing push-off and collision work were used to compute transition impulses across walking speeds ranging from 0.8 to 1.4 m{middle dot}s{square}1. A normalized Impulse Balance Index (IBI) was defined to quantify the relative dominance of push-off and collision impulses. The temporal position of the mid-stance trough was quantified using a Trough Deficit Index (TDI) derived from quadratic fits of the vGRF trajectory. Across walking speeds, push-off and collision variations produced step-to-step active work performance imbalance. Push-off and collision became approximately balanced near 1.2 m{middle dot}s{square}1, corresponding to the mechanically preferred walking speed. Deviations from this balanced condition were associated with systematic shifts in trough timing: the trough occurred 1.83% and 1.56% earlier in stance at 0.8 and 1.0 m{middle dot}s{square}1, respectively, and 1.31% later at 1.4 m{middle dot}s{square}1 relative to the reference speed. TDI exhibited a strong inverse relationship with impulse balance (IBI), indicating that vGRF morphology is tightly coupled to the mechanical balance of the step transition. A simplified pendular model further demonstrated that active torque, representing work, during single support shifts the quadratic vertex of the force trajectory by approximately 48.6-51.1% of stance, consistent with the observed trough timing variations. These results show that vertical GRF morphology reflects the imbalance between push-off and collision provides a simple signal of step-to-step transition mechanics, that may be used for rehabilitation and exoskeleton modulation.

ObjectiveTo investigate the effects of different gait patterns on knee joint biomechanics and dynamic stability during stair ascent. MethodsFourteen healthy males were recruited to ascend stairs using two distinct gait patterns: the "single-step" (leading with the same leg) and "cross-step" (alternating legs) strategies. Kinematic and kinetic data were collected synchronously using a Qualisys infrared motion capture system and a Kistler 3D force plate. Dynamic stability was quantified using the Margin of Stability (MOS), and knee joint biomechanics were evaluated using Patellofemoral Joint Stress (PFJS) and other relevant metrics. ResultsThroughout the gait cycle, there was no significant difference in the Medio-Lateral (ML) MOS between the single-step and cross-step patterns (P=0.318). However, in the Anterior-Posterior (AP) direction, the MOS for both patterns remained negative and decreased over time, with the cross-step pattern exhibiting significantly lower AP MOS values than the single-step pattern (P=0.002). At the moment of left foot-off, significant differences were observed in the right knee joint angle, right knee joint moment, net joint moment, effective quadriceps muscle lever arm, Quadriceps Force (QF), the angle between the quadriceps tendon and patellar ligament, Patellofemoral Joint Force (PFJF), patellofemoral joint stress, and patellofemoral contact area (all P<0.001). ConclusionsDuring stair ascent, the cross-step pattern reduces body stability, thereby increasing the risk of backward falls. Furthermore, this pattern increases patellofemoral joint stress, subjecting the knee to greater loading. Therefore, it is recommended to enhance lower limb muscle strength through targeted training to reduce fall risk. Additionally, adopting a more cautious gait strategy (such as the single-step pattern) can help minimize patellofemoral joint loading and mitigate the risk of patellofemoral pain.

BackgroundInertial measurement units (IMUs) have potential to be inexpensive, portable sensors for collecting gait parameters and joint kinematics. Current validation protocols generally do not investigate IMU accuracy in measuring altered gait; therefore, they cannot assess an IMUs ability to detect pathologies. The Stridelink IMU-based gait analysis device is intended for use in detecting and monitoring gait abnormalities, thus there is a need to evaluate the devices accuracy under abnormal gait conditions. Research questionHow well do measurements from the StrideLink IMU agree with motion capture (MoCap), particularly when gait is mechanically altered to simulate pathology? MethodsTwenty-eight healthy participants (ages 18-40) were analyzed during a one-minute tread-mill walk with Vicon MoCap and StrideLink. Tests were performed under normal and mechanically induced abnormal conditions (knee brace, walking boot). Equivalence testing and correlation analysis evaluated StrideLinks accuracy against MoCap. ResultsStrideLink showed statistical equivalence (within 5%) for average cadence, stride, swing, and stance times but not double support time. Many metrics were statistically equivalent (p < .001) despite induced abnormalities. Correlation analysis showed almost perfect agreement with MoCap for stride times, cadence, and stance. However, the abnormal gait protocol revealed nuances not observed in normal gait; specifically, the device underestimated swing time by [~]10 ms in knee brace restricted limbs. SignificanceThis study utilized mechanically induced gait abnormalities to assess the robustness of IMU measurements. Results indicate StrideLink yields valid temporal gait measurements comparable to reference systems, even under conditions of significant deviation, supporting the utility of using induced abnormalities for sensor validation.

BackgroundComputational modeling is a tool being deployed for orthopaedic solutions but its use in the hand and wrist remains limited. This work used a model to simulate a clinically relevant provocative scaphoid shift maneuver (SSM) with different levels of scapholunate interosseous ligament (SLIL) injuries to observe the effect on different metrics. MethodsA personalized model simulated the full SSM motion cycle from ulnar deviation with extension to radial deviation with flexion informed by the participants motion obtained from dynamic computed tomography. Models repeated the SSM under different levels of SLIL injury and reported changes in joint kinematics, contact mechanics, and ligament forces. ResultsThe fully injured model increased scaphoid dorsal translation, flexion, and radial deviation compared to the intact condition and caused a subluxation of the scaphoid. Radioscaphoid contact areas were approximately 200% greater in the fully injured model compared with all others and the fully injured model was the only condition where contact force decreased across the motion cycle. Ligament forces in the intact condition were on average 33.0 N and 54.2 N for the volar and dorsal SLIL, respectively. Lastly, the long radiolunate, an extrinsic stabilizer, had forces that increased following SLIL injury. ConclusionsComputational models can successfully recreate clinically observed behaviors of an SSM, including scaphoid subluxation, while providing new insights via quantification of contact mechanics and ligament forces. Contact mechanics metrics may be important for understanding the long-term progression of untreated SLIL injuries to osteoarthritis. Additionally, ligament force metrics may explain the progression of SLIL injuries from volar SLIL to dorsal SLIL and highlight the importance of repairing extrinsic stabilizers of the joint, due to increased force sharing following SLIL injury. This work provides a pathway to future studies investigating the effects of SLIL injury and repair, both acutely and chronically.

Deep vein thrombosis (DVT) is a prevalent vascular condition in which venous anatomy and flow disturbances contribute to the risk of thrombosis, but the mechanistic links between vessel shape and haemodynamics remain poorly quantified. Although computational fluid dynamics (CFD) can estimate flow-related risk metrics such as low wall shear stress (WSS), the influence of anatomical fidelity on these predictions is not well understood. Statistical shape modelling (SSM) offers a principled framework for characterising geometric variability, but its integration with CFD in venous applications is still emerging. This study investigates how different levels of anatomical representation--2D projections, simplified 3D extrusions, and full 3D reconstructions of the common iliac veins--influence both the statistical structure of venous shape variability and the haemodynamic metrics derived from CFD. Using patient-specific MRI/CT data from twelve cases, we constructed SSMs in Deformetrica and performed steady-state CFD simulations in ANSYS Fluent under standardised inflow conditions. We compared the variance structure of the 2D and 3D latent spaces and quantified correlations between principal shape modes and low-WSS burden across three thresholds ([&le;] 0.05, 0.10, 0.15 [Pa]). Idealised 3D geometries consistently produced larger low-WSS areas than patient-specific shapes, with average increases of 118-136% across thresholds. The 2D SSM exhibited a strongly hierarchical variance spectrum with one dominant mode that correlated significantly with WSS, whereas the 3D SSM showed a flatter spectrum with weaker univariate associations. These findings demonstrate that geometric fidelity and alignment strategy critically influence shape-flow relationships, highlighting the need for careful model selection when using CFD-based haemodynamic indicators in DVT research. Author summaryDeep vein thrombosis (DVT) is a common condition in which blood clots form in the deep veins of the leg and can lead to serious long-term complications. Although medical imaging captures important anatomical differences between patients, it remains unclear how these variations in vein shape influence local blood flow and the associated risk of clot formation. To address this challenge, we developed a computational framework that combines statistical shape modelling (SSM) with computational fluid dynamics (CFD) to analyse the relationship between venous geometry and haemodynamic risk factors. We examined the common iliac veins at three levels of anatomical detail: simplified two-dimensional projections, intermediate three-dimensional extrusions, and full three-dimensional reconstructions derived from MRI/CT data. By comparing these representations, we show that geometric fidelity strongly affects both the detected modes of anatomical variation and the resulting flow predictions. Simplified geometries consistently overestimated regions of low wall shear stress, a flow feature associated with thrombosis, compared to full 3D models. We also found that shape-flow associations depend heavily on how shapes are aligned and represented. Our findings highlight the importance of anatomical detail in computational venous modelling and provide a foundation for more personalised, simulation-based tools to support DVT treatment.

Cycling is commonly employed in sports performance, rehabilitation, and clinical contexts, while musculoskeletal (MSK) simulations enable the investigation of internal biomechanics that cannot be measured experimentally. Despite growing use, the application, validation, and standardisation of MSK simulations in cycling remain unclear. This review aimed to systematically characterise the application, validation strategies, modelling assumptions, and reporting practices of musculoskeletal simulations in lower-limb cycling biomechanics. Searches were performed in Scopus, PubMed, IEEE Xplore, and Web of Science on 1 August 2024, covering studies from January 2010 to July 2024. Peer-reviewed English-language journal articles applying MSK simulations to lower-limb cycling were included; inverse kinematics-only was excluded. No protocol was registered, and no formal risk-of-bias assessment was conducted, as there were no intervention effects and no quantitative synthesis. Twenty-eight studies met the inclusion criteria. Most of them investigated bicycle-rider configuration, neuromuscular coordination, or electrical stimulation control, with participant cohorts overwhelmingly composed of young men and minimal female representation (272 total). Model reporting was often incomplete, with wide variation in anatomical scope, inconsistent descriptions of degrees of freedom, and limited sharing of models or code. Use of experimental data was uneven across studies: while all incorporated kinematic measurements, only two-thirds included kinetic data, and only one study reported physiological measures. Model validation was generally based on literature values. Seventy-eight per cent of studies used optimisation, mainly with effort-based cost functions, and parameter variations were exploratory rather than systematic. The evidence base is limited by small, predominantly male cohorts, inconsistent reporting standards, and limited physiological validation. These results consolidate current practices and highlight the need for more transparent and open reporting, sex-balanced and clinically diverse participant representation, stronger validation, and more rigorous sensitivity analysis to enhance reproducibility and practical relevance. This review was funded by AGAUR (Spain), CAPES (Brazil) and FAP-DF (Brazil). Author summaryCycling is widely used in sports training, rehabilitation, and clinical practice, and musculoskeletal simulations are increasingly used to study how muscles and joints work during cycling. These simulations allow us to estimate internal biomechanical variables that cannot be directly measured in experiments, such as muscle forces and joint loading. However, it is currently unclear how consistently these simulations are applied, validated, and reported across the literature. In this study, we systematically reviewed research published over the past 15 years that used musculoskeletal simulations to analyse lower-limb cycling. We identified 28 relevant studies and examined their modelling choices, experimental inputs, optimisation strategies, and validation approaches. We found substantial variability in model complexity, limited transparency in reporting, and a strong reliance on simplified literature-based validation methods. Most studies focused on narrow participant groups and explored modelling parameters in an ad hoc rather than a systematic way. Our findings highlight important gaps in current practice and point to clear opportunities for improvement. We provide an overview of common approaches and their limitations, and outline key recommendations to enhance the transparency, reproducibility, and practical relevance of musculoskeletal simulations in cycling research.

This study investigates closed kinematic chain biomechanics in cycling with a focus on knee joint loading. Data from 16 cyclists collected on a standardized ergometer were analyzed in OpenSim using inverse dynamics, static optimization, and joint reaction analysis. To keep the pipeline consistent across all subjects, the report summarizes right-knee outputs over a steady-state interval between 120 and 124 s. Peak knee joint moments ranged from 15.79 to 44.85 Nm (mean 30.49 {+/-} 7.66 Nm), while peak resultant knee reaction forces ranged from 1187.61 to 3309.04 N (mean 2317.19 {+/-} 728.19 N). Static optimization showed strong contributions from the rectus femoris and vastus lateralis during power production, with additional stabilization from the biceps femoris long head and gastrocnemius medialis. Mean peak muscle activation was highest for the rectus femoris (0.72 {+/-} 0.19), followed by the biceps femoris long head (0.66 {+/-} 0.20). Mean peak muscle force was highest for the vastus lateralis (1078.1 {+/-} 305.8 N) and rectus femoris (994.1 {+/-} 379.2 N). The results confirm substantial inter-subject variability in knee loading and support the use of personalized training or rehabilitation strategies when cycling is used for performance development or joint recovery.

BackgroundQuadriceps weakness may reduce sagittal plane shock absorption during landing, shifting load toward the frontal plane and increasing knee abduction moment (KAM), a biomechanical risk factor for anterior cruciate ligament (ACL) injuries. PurposeThe purpose of this study was to evaluate the association between isokinetic quadriceps strength and peak KAM during drop vertical jump landing in adolescent athletes. Study DesignSecondary analysis of previously collected data. MethodsHealthy adolescent athletes completed quadriceps strength testing using an isokinetic dynamometer and a biomechanical assessment during a drop vertical jump task. Quadriceps strength was quantified as peak concentric torque and the peak external KAM was calculated during the landing phase on the dominant limb. Both strength and KAM were normalized to body mass. Linear regression was used to examine the association between normalized quadriceps strength and peak external KAM on the dominant limb. ResultsThe association between quadriceps strength and peak normalized KAM on the dominant limb was not statistically significant ({beta} = -0.053 (95% CI [-0.137 to 0.030]), F(1,119) = 1.62, R2 = 0.013, p = 0.206). Quadriceps strength explained only 1.3% of the variance in peak KAM, indicating a negligible association between these variables in this cohort. DiscussionQuadriceps strength was not associated with peak normalized KAM during landing, suggesting that frontal-plane knee loading during a drop vertical jump is not meaningfully explained by maximal concentric quadriceps strength alone. KAM appears to be driven more by multi-joint movement strategy and neuromuscular coordination than by the capacity of a single muscle group.

The effects of specific footwear features on biomechanical parameters are often confounded by simultaneous changes in other shoe conditions, making it difficult to identify the isolated effect of material and design properties on relevant biomechanical outcomes. This study aimed to propose a tool, namely the Modular Footwear Setup (MFS), to assess the effects of midsole modifications on lower limb joint kinematics and in-shoe plantar pressure. The MFS uses a micro-hook-and-loop fastening system and a custom alignment device to enable fast, strong, and reliable midsole attachment/detachment to/from the upper. Accuracy and repeatability of the MFS in replicating the biomechanical outcomes of a control shoe featuring the same upper and midsole were tested in 10 healthy participants (5M,5F; age=33.2{+/-}9.2 yrs; BMI=21.5{+/-}2.8 kg/m2). Participants were asked to walk wearing both the MFS and the standard control shoe in three sessions. Kinematics of lower limb joints were measured via inertial measurement units, while capacitive pressure insoles were used to measure in-shoe plantar pressure. Intraclass correlation coefficient (ICC) was used to assess the repeatability of kinematic and pressure measurements between sessions. Statistical Parametric Mapping analysis did not identify significant differences in joint kinematics between conditions. While the MFS exhibited slightly lower peak pressure at the rearfoot, pressure parameters were not statistically different in the other foot regions. The MFS demonstrated good-to-excellent inter-session repeatability (ICC 0.84-0.97) for peak and mean pressure. Participants reported similar levels of comfort and stability in both shoes. The findings of the present study suggest the MFS has the potential to be a reliable and accurate tool for evaluating the effect of midsole features on relevant biomechanical parameters. This modular approach may improve data-driven footwear design by providing a consistent platform for testing the effects of midsole designs and materials across various applications, including therapeutic, safety, and athletic shoes.

ContextACL injury prevention in young athletes has traditionally relied on a dichotomous classification of contact versus noncontact mechanisms; however, this framework may not adequately capture the movement processes underlying many injuries. ObjectiveTo classify ACL injury mechanisms in athletes aged [&le;]22 years with a specific focus on landing-related movements and to examine their associations with sport contact characteristics and age. DesignRetrospective observational study. SettingSingle sports injury clinic. Patients or Other ParticipantsA total of 151 athletes aged [&le;]22 years (mean age, 17.7 {+/-} 2.1 years) diagnosed with ACL injury between January 2017 and November 2025. Main Outcome Measure(s)ACL injury mechanisms were classified as landing-related without contact (L), landing-related with contact (Lc), or direct contact injury (C). Landing-related injuries (L + Lc) were compared with direct contact injuries. Multivariable logistic regression was used to identify factors associated with landing-related injury. ResultsLanding-related injuries accounted for 123 cases (81.5%), including 88 noncontact and 35 contact-related landing injuries, whereas direct contact injuries occurred in 24 cases (15.9%). Athletes with direct contact injuries were significantly older than those with landing-related injuries (19.2 {+/-} 1.7 vs 17.5 {+/-} 2.5 years, p = 0.03). In multivariable analysis, participation in noncollision sports was strongly associated with landing-related injury (odds ratio [OR] = 9.80; 95% confidence interval [CI] = 3.03-31.5; p < 0.001), whereas increasing age was inversely associated with landing-related injury (OR per year = 0.71; 95% CI = 0.56-0.90). Sex was not independently associated with injury mechanism. ConclusionsMost ACL injuries in athletes aged [&le;]22 years occurred through landing-related mechanisms, regardless of contact. These findings highlight insufficient control of landing and foot contact as a fundamental mechanism of ACL injury in young athletes and support prevention strategies focused on movement quality during sport-specific tasks. Key Points{blacksquare} Most ACL injuries in athletes aged [&le;]22 years occurred during landing or foot contact, regardless of whether external contact was present. {blacksquare}Noncollision sports and younger age were strongly associated with landing-related ACL injury mechanisms. {blacksquare}ACL injury prevention in young athletes should prioritize improving landing and foot contact control rather than focusing solely on contact characteristics.

The present study presents a systematic approach for generating data-driven synthetic cerebral aneurysm geometries and evaluating their hemodynamics through computational fluid dynamics. Seven patient-specific aneurysm geometries from the right internal carotid artery were reconstructed from time-of-flight magnetic resonance angiography images and standardized through orientation alignment, followed by non-rigid registration onto a common spherical point cloud as a template. Principal component analysis (PCA) was then applied to the aligned point-cloud data to quantify morphological variability and parameterize shape deformation. The first four principal components captured over 90% of the total variance; however, higher-order components were required to capture the detailed geometrical features of the original geometries. Computational fluid dynamic simulations were performed on the PCA-based synthetic geometries under pulsatile flow conditions to investigate the influence of shape variations on intra-aneurysmal flow patterns, time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI). The first principal component score (PCS1), which was associated with changes in aneurysm height and dome width, had the strongest effects on TAWSS and OSI levels. Lower PCS1 values, which corresponded to taller and more oblique domes, produced slower adjacent flow and elevated OSI, whereas higher PCS1 values increased TAWSS. The second principal component score primarily modulated lateral geometric asymmetry and further influenced OSI distribution for the lower PCS1 values. Collectively, these findings indicate that PCA-based shape parameterization provides a practical approach for generating synthetic aneurysm datasets and systematically assessing how specific morphological features govern hemodynamic behavior. The proposed approach is expected to contribute to the future development of surrogate modeling and data-driven hemodynamic prediction.

AimTo determine the mechanistic relationship between segmental trunk control in the neutral vertical posture (NVP), assessed using the Segmental Assessment of Trunk Control (SATCo), and the Gross Motor Function Classification System (GMFCS); and hence to identify the means to enhance function in children with cerebral palsy (CP). MethodThis cross-sectional study included 101 children with CP (34 female, 10y(3y8m), 1.32(0.27)m, 33.4(18.4)kg) classified across GMFCS Levels I-V and tested with SATCo. Association and variation between GMFCS Levels and SATCo results were examined. ResultsSATCo results differed significantly (p<.05) between GMFCS Levels in static, active and reactive tests of trunk control. As neuro-ability increases through GMFCS Levels V-I, ability to control the head and trunk in NVP increases ({rho}(99)=-0.61 to -1,p<.0001) and variation in head and trunk control increases ({rho}(3)=-0.9 to -1,p<.05). InterpretationSATCo provides mechanistic insights supporting its use following GMFCS. In severe CP, NVP control is minimal across all children. In mild CP, large variation in results shows that SATCo discriminates between the use of full trunk control from compensatory strategies to achieve function. For each GMFCS Level, SATCo identifies the training required to improve trunk control in NVP, thus improving functional performance and reducing long-term risk of deformity. What this paper addsO_LISATCo results are related to GMFCS Levels, and complements GMFCS C_LIO_LISATCo provides the mechanistic explanation for what is observed in GMFCS C_LIO_LISATCo-GMFCS reveals if function is attained with trunk control or compensatory strategies C_LIO_LICompensatory strategies often used in mild CP are not captured by GMFCS C_LIO_LISATCo identifies the training required to improve function and reduce deformity risk C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/26344472v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@3ba4f1org.highwire.dtl.DTLVardef@1c9ce70org.highwire.dtl.DTLVardef@101d01org.highwire.dtl.DTLVardef@1e04861_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIExample above: GMFCS Level I child leaning backwards when tested for lower thoracic NVP trunk control. Same child showing compensatory lordotic lumbar posture while standing. C_LIO_LISATCo can be used in combination with GMFCS to identify specific training targets to improve postural control, enhance function, and reduce deformity risk. C_LI

Neural feedback is important for healthy control of movement, and multiple neurological disorders (e.g., stroke, cerebral palsy, Parkinsons disease, incomplete spinal cord injury) can be described by how they impair healthy feedback or induce unhealthy feedback. Researchers have created numerous computational neuromusculoskeletal models controlled by simulated neural feedback mechanisms, but these models rarely represent actual human subjects and thus have not found practical application in treating patients with movement impairments. As a step toward designing patient-specific treatments for individuals with neurological disorders, this study used the Neuromusculoskeletal Modeling Pipeline to develop and evaluate a novel synergy-based feedforward (FF)+feedback (FB) model using a personalized, three-dimensional neuromusculoskeletal walking model of an actual human subject post-stroke. Experimental walking data collected from the subject were used to create the subjects personalized walking model. This model was used to calculate lower body muscle activations consistent with the subjects electromyographic, joint motion, and ground reaction data for 5 calibration walking cycles. Nominal FF synergy controls were calculated by averaging the muscle synergies that closely reconstructed the 5 cycles of muscle activations and associated joint moments simultaneously. These nominal FF controls were then scaled by 0, 25, 50, 75, 100, and 125%, and the gap in reproducing individual cycle muscle activations was filled by fitting FB synergy controls as a function of joint positions, velocities, and moments as surrogates for muscle lengths, muscle velocities, and tendon forces. Finally, the six synergy-based FF+FB models controlled the subjects personalized walking model in predictive simulations performed for 3 testing walking cycles withheld from calibration. The 100% FF model (which still had minimal FB) reproduced the testing walking cycles the most closely, and only the 75%, 100%, and 125% FF models generated near-periodic walking motions using initial conditions consistent with experimental values. The 0, 25, and 50% FF models could generate near-periodic walking motions only when the initial conditions were allowed to diverge substantially from experimental values. Our findings suggest that predictive simulations of walking using real experimental data may require a minimum level of feedforward control and sufficient fitting data to predict a subjects actual dynamically consistent motion.

Background and PurposeWalking speed is the dominant clinical metric used to classify post-stroke hemiparetic gait severity. However, speed does not describe how mechanical energy is generated and redistributed. We tested whether whole-body center-of-mass (COM) work patterns provide a biomechanically grounded supplement to speed-based severity classification. MethodsLimb-specific COM power and work were computed from ground reaction forces using the individual-limbs method across five walking speeds (0.2-0.7 m/s). We quantified net COM work index of asymmetry (IA_Wnet), positive COM work asymmetry (IA_Wpos), and the Propulsion-Support Ratio (PSR = impFy/impFz). Piecewise and quadratic regressions were used to assess speed-dependent trends. ResultsIA_Wnet remained elevated across speeds and showed no significant high-speed association. IA_Wpos demonstrated a significant quadratic relationship with speed (p=0.023, R{superscript 2}=0.23), decreasing near 0.5 m/s before rising again. Paretic limb PSR remained constrained and exhibited a quadratic association (p=0.012, R{superscript 2}=0.14), while unaffected limb PSR declined significantly at higher speeds (p=0.019, R{superscript 2}=0.38). Below 0.5 m/s, COM power profiles collapsed to a two-phase pattern without paretic limb push-off; at [&ge;]0.5 m/s, a four-phase structure emerged. ConclusionIncreasing walking speed did not normalize interlimb mechanical imbalance. COM work organization revealed a biomechanical transition near 0.5 m/s and distinguished compensation from recovery-based restoration. Supplementing speed with COM work and propulsion-support metrics may refine severity stratification and guide mechanism-targeted rehabilitation.

Modelling of hemodynamics in the circle of Willis (CoW) depends on vascular segmentation, which may vary based on imaging modality. Computed tomography angiography (CTA) is commonly used in clinic but involves radiation and injection of contrast agents, whereas magnetic resonance angiography (MRA) offers a non-invasive alternative. This study aims to compare CoW morphology and modelled cerebral perfusion pressure of CTA and MRA segmentations, validating if MRA can replace CTA in modelling workflows. CTA and time-of-flight MRA (TOF-MRA) of the CoW was performed in 19 patients undergoing elective aortic arch surgery (67{+/-}7 years, 8 women). The CoW was semi-automatically segmented based on signal intensity thresholding. A TOF-MRA threshold was optimized against the CTA segmentation, using the CTA as reference standard. Computational fluid dynamics (CFD) modelling with boundary conditions based on subject-specific flow rates from 4D flow MRI simulated cerebral perfusion pressure in the segmented geometries. A baseline simulation and a unilateral brain inflow simulation, i.e., occlusion of a carotid, were carried out. Linear mixed models indicated there was no effect of choice of modality on either average arterial lumen area (CTA - TOF-MRA: -0.2{+/-}1.3 mm2; p=0.762) or baseline pressure drops (0.2{+/-}1.9 mmHg; p=0.257). In the unilateral inflow simulation, we found no difference in pressure laterality (-6.6{+/-}18.4 mmHg; p=0.185) or collateral flow rate (10{+/-}46 ml/min; p=0.421). TOF-MRA geometries can with signal intensity thresholding be matched to produce similar morphology and modelled cerebral perfusion pressure to CTA geometries. The modelled pressure drops over the collateral arteries were sensitive to the segmentation regardless of modality.

PurposeThis work investigates the role of the cancer cell morphology and elasticity on the deformation patterns under shear-flow in a micro-channel. MethodsA novel hybrid continuum-particle framework is developed to simulate cancer-cell dynamics. Cell membrane and nucleus geometries are reconstructed from microscopic images and modeled using Dissipative Particle Dynamics, while the surrounding blood plasma is treated as an incompressible Newtonian fluid. Cell-flow interactions are captured via an immersed boundary method. ResultsAll cancer-cell models exhibited a rapid deformation response within the first 1-2 ms, followed by morphology- and stiffness-dependent shape evolution. The compact morphologies showed strong recovery, whereas the other models evolved toward folded/lobed states with only intermittent partial recovery during shape transitions. Membrane stiffening dominated elongation and compactness loss, while nuclear stiffening modulated deformation excursions and partial recovery. These shape transitions were accompanied by near-field vortex reorganization and traction localization. Similar to deformation response the net membrane force exhibited a common start-up rise within 0-0.5 ms followed by relaxation. Compact morphologies produce lower and steadier forces. They show minimal stiffness dependence. Deformation-prone morphologies show stronger unsteadiness and clearer stiffness modulation. Cross-sectional velocity and vorticity fields showed a dominant x-directed hydrodynamic imbalance and lateral migration. ConclusionOur results demonstrate that morphology sets the stiffness modulated deformation patterns which effects the extracellular flow dynamics and traction. In turn, the resulting flow field and traction distribution feed back to influence subsequent deformation and migration. This mechanistic link provides a framework for interpreting circulating tumor cell transport in shear-dominated metastatic environments.

Falls among older adults can result in hip fractures that requires x-ray based assessment at emergency department (ED). Only 25.7% of patients presenting to EDs are diagnosed with a hip fracture, as such improved diagnosis prior to transportation to hospital could result in fewer hospital visits and improved triaging. Patient with hip fracture could be immediately directed to centres with orthopaedic surgeons, allowing for reduced time-to-surgery, particularly in rural communities. Ultrasound (US) imaging is portable and can identify fractures but requires expertise, particularly related to image interpretation. Deep learning may reduce operator dependence by automating image interpretation. This study aims to develop HipSAFE, a hip fracture detection tool on US, to support triaging by nurses and paramedics. We hypothesize that diagnostic accuracy will be comparable to pelvic x-ray diagnostic performance in a preclinical study. Bilateral hind limbs of 15 porcine cadavers were imaged by US-naive operators before and after an iatrogenic hip fracture. The limbs were divided into training, validation, and test (8 femurs) sets. The training data were augmented (geometric and photometric transformations). The models included MobileNetV3 (S/L), EfficientNet-Lite (0-2), and ResNet (18/50). Using a moving average aggregation on the operator cine clips, EfficientNet-Lite0 achieved the highest performance (F1=0.944 [95% CI:0.880-0.987]; sensitivity=89.5% [78.6-97.5%]; specificity = 100.0% [100.0-100.0]). The majority voting ensemble model ranked second (F1=0.932 [0.857-0.984]). Naive operators and radiologists had lower performance (F1=0.667 [0.596-0.758] and 0.685 [0.597-0.729]). This pre-clinical study demonstrated that HipSAFE has excellent diagnostic accuracy and there may be a role for US in improving hip trauma triaging, especially for rural and resource-constrained environments.