Journal of Biomechanics

Markerless motion capture has emerged as a potential substitute for traditional marker-based systems, offering scalable, non-invasive acquisition of human movement. Despite increasing adoption in research and sports applications, its clinical utility for children with complex gait patterns remains an open question. To address this gap, simultaneous marker-based and markerless data were collected in 202 pediatric children (12.1 {+/-} 3.9 years). Marker-based kinematics were processed using the Shriners Childrens Gait Model (SCGM), while markerless outputs were computed using Theia3D with identical Cardan sequences. Agreement between systems was evaluated using statistical parametric mapping (SPM), root-mean-square error (RMSE), and a gait pattern classification based on the plantarflexor-knee extension index. Markerless output systematically underestimated pelvic tilt, hip rotation, and knee rotation and demonstrated reduced between-subject variance in the transverse plane. SPM revealed widespread waveform differences, although most were of negligible effect, especially in the sagittal plane. Mean sagittal-plane RMSEs were < 5{degrees} for the knee and ankle and < 8{degrees} for the pelvis and hip. Coronal-plane deviations were < 7{degrees}, whereas transverse-plane errors exceeded 10{degrees}. RMSE increased significantly with body mass index and use of a walker (p < 0.001). Agreement in sagittal-plane gait classification was moderate between systems ({kappa} = 0.60; 67% overall concordance). These results indicate that markerless motion capture is suitable for analyses emphasizing sagittal deviations but remains limited for applications requiring precise axial or frontal-plane estimation. Future work should address algorithmic underestimation of transverse motion and evaluate markerless performance across increasing severity of gait deviation.

Background and ObjectiveThe foot-ankle complex is a highly articulated and mechanically constrained system, often simplified as a chain of few rigid segments, neglecting many bone-to-bone motions and raising questions about the accurate representation of interaction with ground. This study proposes a new reduced-order multibody formulation that captures intrinsic kinematic constraints of the foot through motion synergies. MethodsBones kinematic coupling, or motion synergies, were experimentally derived from weight-bearing CT scans using principal component analysis. These couplings were embedded in a synergy-based multibody kinematic optimization framework describing the foot-ankle with five degrees of freedom: ankle flexion; foot adduction, pronation, and arching; and toe flexion. Model accuracy was evaluated against bone-level experimental kinematics. The model was applied to gait data from healthy, flat, and diabetic feet and compared with a standard multi-segment foot model, assessing robustness by progressively reducing the number of skin markers. ResultsAverage errors were about 1{degrees} and 0.5 mm when using subject-specific synergies and below 7{degrees} and 4 mm when scaling the generic model, matching or exceeding the accuracy of existing models. Reliable reconstruction was obtained using only four foot markers. In clinical gait analysis, the model showed superior discrimination between populations and enabled assessment of transverse arch deformation, not accessible with conventional models. ConclusionThe proposed synergy-based model provides an accurate, low-complexity framework for reconstructing bone-level foot and ankle kinematics, substantially simplifying gait analysis while improving biomechanical interpretability. This framework supports future integration with dynamic models aimed at studying load transmission in the foot.

Advanced footwear technology (AFT) shoes incorporate increased sole thickness and compliant midsole materials that may alter running biomechanics. While these effects have been widely studied during level running, little is known about how sole thickness influences running style and stability during uphill running. This study examined the effects of two AFT shoes differing in sole thickness (35 mm-AFT35; 50 mm-AFT50) and a traditional control shoe (27 mm-CON27) on running style and stability during uphill running. Seventeen experienced male runners performed treadmill running at a 10% incline at 6.5 and 10 km/h in three shoe conditions. Running style was assessed using duty factor, normalized step frequency, center-of-mass oscillation, vertical and leg stiffness, and lower-limb joint kinematics. Running stability was evaluated using local dynamic stability via the maximum Lyapunov exponent and detrended fluctuation analysis of stride time. Duty factor and normalized step frequency did not differ between shoes. However, AFT shoes showed greater center-of-mass oscillation (p = 0.004), lower vertical stiffness (p = 0.022) compared to CON27. Joint kinematics revealed significant shoe effects at the ankle (p = 0.001), particularly increased dorsiflexion and eversion in AFT conditions. Running stability showed only minor changes. Local dynamic stability differed at the trunk (p = 0.027), with reduced stability in AFT50 compared with CON27 (p = 0.006), while global stability remained unchanged. No shoe x speed interactions were observed for any variable. Overall, uphill running style and stability remained largely preserved across shoe conditions, suggesting that sole thickness alone had limited influence.

PurposeQuantification of walking function, including joint motions, ground reactions, and joint loads, outside the lab is a growing research area. Because only joint motions can currently be measured outside the lab, researchers are utilizing tracking optimizations of walking to estimate associated ground reactions and inverse dynamic joint loads. However, foot-ground contact models used in such optimizations have been generic rather than personalized, which may limit the accuracy of estimated ground reactions and joint loads. This study compares the predictive capabilities of generic versus personalized foot-ground contact models. MethodsGeneric and personalized foot-ground contact models were evaluated in calibration and tracking optimizations performed using experimental walking data collected from three subjects in varying states of health. Foot-only calibration optimizations evaluated how well both models could reproduce experimental ground reaction and foot motion data while tracking both types of data simultaneously, while whole-body tracking optimizations evaluated how well both models could reproduce experimental ground reactions, joint motion, and joint load data while tracking only experimental joint motion data and achieving dynamic consistency. ResultsFor all three subjects and both types of optimizations, personalized foot-ground contact models reproduced experimental ground reaction, joint motion, and joint load data more accurately than generic foot-ground contact models. ConclusionPersonalized foot-ground contact models can improve the accuracy with which ground reactions and joint loads can be estimated via tracking optimizations of walking using only experimental motion data as inputs. Personalized models require little time and effort to calibrate using freely available software tools and should improve the accuracy of predictive simulations of walking as well.

AO_SCPLOWBSTRACTC_SCPLOWMuscle fibre type distribution influences both the metabolic and contractile properties of individual muscles. However, as humans tend to self-optimize their gait pattern to minimize cost of transport, these changes in muscle properties may influence gait biomechanics in manners that are difficult to isolate in in vivo experiments. The purpose of this study was to predict the influence of muscle fibre type distribution on the metabolic cost and biomechanics of simulated walking and running. We implemented a muscle model that could predict recruitment of slow and fast twitch muscle fibres in a framework for predictive musculoskeletal simulation. Subsequently, we employed the framework to investigate how metabolic cost of transport, stride length, stride frequency, and mechanical work performed by slow and fast twich muscle fibres were influenced by fibre type distribution across locomotion speeds from 1.0 to 4.5 m {middle dot} s-1. Our results predict that cost of transport increases as slow twitch area fraction decreases, while stride length and frequency was minimally affected by fibre type distribution at speeds resulting in walking. In contrast, fibre type distribution interacts with locomotion speed at speeds resulting in running. Specifically, we predict the existence of a threshold speed below which cost of transport decreases with an increasing proportion of slow twitch fibres, while cost of transport increases with increasing proportions of slow twitch fibres above it. The shift in fibre type distribution was accompanied by an increase in stride frequency and decrease in stride length. These shifts in spatiotemporal characteristics appear to allow the muscles to operate at speeds close to those that achieve peak mechanical efficiency. Taken together, the results of this study predict that muscle fibre type distribution may influence both the energetics and biomechanics of gait, and that this influence is dependent upon the locomotion speed.

Importance: Foot drop impairs mobility for many children globally, causing life-long health issues. Existing treatments are costly, custom-made, and require frequent clinical visits. A new, low-cost, off-the-shelf splint (OrthoPed) could improve access and user experience. Objective: To determine the feasibility of recruiting children (4-17 years) with moderate foot drop and collecting biomechanical, clinical, and patient-reported outcomes to compare OrthoPed with existing treatments. Design: Single-centre cross-sectional feasibility and pilot study informing a future randomised clinical trial. Participants: Twelve children (target=20; mean age=10.6 {+/-} 3.5 years; 2 females) with moderate foot drop and prescribed orthotic support were recruited via physiotherapy. Intervention: The new OrthoPed splint was compared against existing treatments: ankle foot orthoses (AFOs) and Lycra socks. Main outcome measures: Primary outcome: recruitment and retention rates. Secondary outcomes: biomechanical and clinical gait measures, alongside useability and performance questionnaires. Results: Recruitment reached 22% of eligible participants (an "amber" rating for future trials). Despite four dropouts due to treatment burden, all outcome measures were successfully collected. Preliminarily, OrthoPed supported more natural gait mechanics than AFOs and offered better usability and comfort than AFOs and Lycra socks, potentially enhancing adherence. Conclusions: Recruiting children for orthotic trials is feasible, though coordinating gait testing with routine clinical appointments could improve future recruitment. Importantly, low-cost orthotic devices may provide better usability, accessibility and adherence than existing prescribed options.

A passive device that attaches to the feet, called an exotendon, can reduce the energetic cost of running at moderate speeds, but its efficacy and optimal design parameters at higher speeds are unknown. Identifying optimal parameters at new speeds experimentally would require many experimental trials with different exotendon designs, which is challenging for participants at higher running speeds. We developed a muscle-driven simulation framework to predict the effect of various exotendon designs on the energetic cost of running at an experimentally untested speed (4 m/s). We used these predictions to select four designs, which we evaluated experimentally as users ran at this speed. The framework correctly predicted that an exotendon that reduced energetic cost at 2.7 m/s would also reduce energetic cost at 4 m/s (10% predicted vs. 5.7% measured) and that a short, stiff exotendon and a long, compliant exotendon would not significantly reduce energetic cost. However, exotendon parameters predicted by the simulation to maximize energetic savings did not significantly reduce energetic cost when evaluated experimentally. There was variability between participants in both the magnitude of maximum energy savings and the exotendon condition associated with those savings. In a 5-km time trial performed with and without the exotendon condition that elicited the largest energy savings for each participant during the experiment, we observed a lower average heart rate (-3.9 {+/-} 3.8 beats/min; P=0.03; mean {+/-} standard deviation) and increased cadence (15.9 {+/-} 9.6 steps/min; P=0.002) when participants ran with the exotendon but did not observe a statistically significant difference in finishing time (-13.5 {+/-} 24.6 sec; P=0.3). These results demonstrate exotendons can reduce energetic cost across multiple running speeds and that predictive simulations provide a framework for guiding experiments to evaluate assistive device designs. Author summaryDesigning assistive devices that help people move more efficiently usually requires many experimental trials. These studies can be time-consuming and physically demanding, especially when testing multiple device designs. In this study, we explored whether computer simulations could help guide the design of an assistive device for running called an exotendon. The exotendon is a simple elastic band that connects the feet and can help runners use less energy. Previous experiments showed that the device reduces the energy needed to run at moderate speeds, but it was unclear whether it would also work at faster speeds or which design would lead to energetic savings. We first used simulations of human running to test many possible exotendon designs at a faster speed. These simulations allowed us to identify promising designs before conducting experiments. We then tested a small number of these designs with runners. The experiments confirmed that the exotendon can reduce the energy required to run at faster speeds, although the efficacy of different designs varied between individuals. Our results show that computer simulations can help researchers rapidly evaluate a variety of assistive device ideas and focus experimental testing on the most promising designs.

Conventional diagonal stride skiing traditionally includes a glide phase, characterised by a period of relatively passive gliding on one ski. While the glide phase may take advantage of low ski-snow friction, it does not exhibit the same whole-cycle mechanical energy fluctuations seen in running or walking on foot. A new sub-technique, known as running style, substantially reduces the glide phase and may alter the role of elastic tissues, making the movement pattern more similar to uphill running on foot in its temporal organisation. We examined knee extensor and plantar flexor muscle-tendon behaviour in eight competitive skiers performing conventional diagonal and running techniques on a treadmill inclined at 10{degrees}. Using synchronised ultrasonography, 3D kinematics, ski forces and EMG, we quantified gastrocnemius medialis and vastus lateralis fascicle and muscle-tendon unit (MTU) dynamics in both the running (RUN) and conventional (CON) styles. Shorter glide and total cycle durations during RUN shifted MTU peak length and velocity earlier during the kick phase. Fascicles in both muscles operated at similar velocities across techniques, showing MTU-fascicle decoupling. Vastus lateralis fascicles shortened at higher absolute peak velocities than gastrocnemius in both conditions, while normalised velocities were similar. RUN increased preactivation and advanced EMG timing, while integrated EMG during the kick was lower compared to CON. These findings suggest that, despite large shifts in external mechanics between glide-based and more running-like skiing, elastic tissues may help stabilise fascicle behaviour and preserve a similar contractile strategy across muscles and techniques.

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.

This study presents the MMH dataset, a laboratory-collected in vivo dataset comprising whole-body kinematics, three-dimensional ground reaction forces and two-dimensional centres of pressure under both feet, as well as surface electromyography (sEMG) signals of twelve lower-limb muscles (six muscles per leg) during load lifting and lowering tasks. Ten healthy, normal-weight, young male adults each performed 72 trials combining one- and two-handed load (2 kg) lifting and lowering. These trials include multiple initial and final load locations while using three different lifting techniques (stoop, semi-squat, and full-squat). The kinematic and force-plate measurements provide rich input for ergonomic risk assessment tools and optimisation-based musculoskeletal models aimed at quantifying and managing musculoskeletal risk of injury. Also, the sEMG recordings enable the development of EMG-assisted musculoskeletal models and support validation of predictions from optimisation-based models. These makes the multimodal MMH dataset a valuable resource for biomechanics, ergonomics, and human movement research.

AO_SCPLOWBSTRACTC_SCPLOWMuscle efficiency decreases with increasing size, largely due to a relative decrease in its mechanical output. Muscle mechanical output depends on its activation, strain, and strain rate and thus varies between different muscles within a limb during locomotion. Distinct muscle coordination patterns are required for efficient cycling, and so we would expect that the coordination patterns for efficient cycling or indeed locomotion would change across animal sizes. We tested whether muscle coordination would change with muscle size using data derived from human cycling: this paradigm allowed for controlled changes in both crank torque and cadence, allowing the multifactorial problem of muscle power output to be decomposed. We used kinematic and pedal data from 12 cyclists undergoing steady pedalling at cadences from 80 to 140 r.p.m. and generated musculoskeletal simulations of their movements. We introduced novel multisegment muscle models in the simulation that incorporated the internal muscle mass and thus accounted for the scaling effects of muscle tissue inertia. We solved the simulations for the muscle activity that was required to minimise the metabolic cost during cycling for each condition. The masses of the muscle models were scaled across five orders of magnitude. The predicted muscle activations were classified by Principal Component analysis to identify whether the coordination of muscle activity was modulated across models with different sized muscles. Analysis of variance revealed significant changes in coordination at the large-scale factors. This study shows how the coordination of muscle activity during locomotion will likely change across a range of body sizes due to the non-linear effects of the inertial mass within the muscle tissues.

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.

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.

Background: Quadriceps strength and landing mechanics are two modifiable factors associated with anterior cruciate ligament (ACL) injury risk. Collecting detailed biomechanical data is an arduous task. Identifying a relationship using more easily measured variables, such as quadriceps strength, would offer value for athlete counseling and injury prevention programs. Although quadriceps weakness has been associated with altered landing strategies in ACL-reconstructed (ACLR) individuals, this relationship is less clear in healthy athletes. Purpose: To investigate the association between isokinetic quadriceps strength and peak knee flexion angle during a vertical drop jump in healthy adolescent athletes. Study Design: Secondary analysis of previously collected data. Methods: Healthy adolescent athletes had their dominant leg quadriceps strength measured using an isokinetic dynamometer at 60{degrees}/s from 0-90{degrees} of knee flexion. Landing mechanics were assessed during a vertical drop jump using three-dimensional motion capture synchronized with force plates. Pearson correlation was used to evaluate the association between quadriceps strength and peak knee flexion angle during landing, with statistical significance defined as p < .05. Results: There was a weak negative correlation between quadriceps strength and peak knee flexion angle (p = .017, R = -.22 [-.04, -.38]), suggesting that stronger athletes achieved greater knee flexion angles. Discussion: Greater quadriceps strength was associated with increased peak knee flexion angles during landing; however, the weak correlation suggests that strength explains only a small portion of the variability in landing mechanics. These findings deviate slightly from prior literature in healthy populations but are consistent with studies demonstrating that greater quadriceps strength is associated with achieving greater peak knee flexion in ACLR patients. Accordingly, quadriceps strengthening should remain a key component of multifactorial ACL injury prevention programs.

An increasing number of studies highlight the role of saccadic remodulation in compensatory mechanisms following vestibular injury, and the reappearance of SHIMP saccades correlates with symptom improvement measured by the Dizziness Handicap Inventory (DHI). To investigate the influence of attentional processes and working memory on visuo-vestibular interaction, three independent but interrelated experiments were conducted. In the first two experiments, healthy subjects and patients with unilateral or bilateral vestibular deficits underwent vHIT in SHIMP mode and the Functional Head Impulse Test (fHIT), performed first separately and subsequently simultaneously. Mean latency and clustering of SHIMP saccades, together with Landolt C recognition rates, were analyzed. Differences between separate and combined protocols were assessed, and, in patients, correlated with symptom severity measured by the DHI, to determine whether the near-simultaneous execution of tasks mediated by shared parietal cortical substrates influenced performance. In the third experiment, vHIT in HIMP mode and fHIT were performed using separate and combined protocols to evaluate whether recognition-related cognitive load affected recovery saccade latency and clustering. Results suggest that visual recognition modulates visuo-vestibular interaction, supporting integrated dual-task protocols for ecological balance assessment and helping explain clinical discrepancies.

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.

Gait asymmetry is a common manifestation of walking impairment among clinical populations. We recently developed a novel treadmill walking approach called dynamic treadmill walking that can provide asymmetric gait training by changing the treadmill speed between fast and slow speeds within a single stride. Here, we studied the energy expenditure associated with a variety of dynamic treadmill walking conditions. We hypothesized that the metabolic power required for dynamic treadmill walking in all conditions would approximate the metabolic power associated with conventional walking at the mean of the fast and slow speeds employed in the task. Eleven young adults without gait impairment walked on an instrumented treadmill and breathed into a metabolic measurement system. During dynamic treadmill walking, the treadmill fluctuated between 0.75m/s and 1.50m/s, each for 50% of an individuals stride time. We used a metronome to synchronize participants right heel-strikes with four different timing conditions. Net metabolic power during dynamic treadmill walking was significantly greater than normal walking at the mean speed of the task (1.125m/s) and generally lower than walking at the fast speed (1.5m/s). We did not observe any significant associations between net metabolic power and several measures of gait asymmetry during dynamic treadmill walking. These findings establish dynamic treadmill walking as a promising technique for improving gait symmetry in individuals who cannot tolerate fast treadmill walking, a common gait rehabilitation approach. Future work will assess the feasibility, metabolic demands, and clinical efficacy of using dynamic treadmill walking to improve gait symmetry in clinical populations. Key Points SummaryO_LIDynamic treadmill walking (i.e., walking with oscillating treadmill speeds) has previously been shown to drive gait asymmetries, but little is known about the energy expenditure required to complete the task. C_LIO_LIOur hypothesis was that dynamic treadmill walking would have similar metabolic power requirements to normal walking at a speed that is intermediate between the two dynamic treadmill walking speeds. C_LIO_LIWe found that dynamic treadmill walking actually requires metabolic power that is greater than the average of the two belt speeds, but less than that used for fast walking. C_LIO_LIDynamic treadmill walking is a promising and clinically translatable technique for rehabilitating populations with gait asymmetries that is not more energetically costly than fast treadmill walking, a common gait rehabilitation approach. C_LI

BackgroundPatients who have undergone Anterior Cruciate Ligament Reconstruction (ACLR) have a 6-24% chance of either re-tearing or having subsequent knee surgery. To date there have been no practical validated risk prediction models that can be easily implemented into clinical workflow for re-injury risk. Micro-Doppler radar (MDR) provides a promising solution. ObjectiveThe purpose of this study was to investigate the predictive ability of MDR to identify persons with a previous ACLR relative to an age and sex matched healthy control. MethodsACLR patients (n=81) and controls (n=100) performed drop box jump, sit to stand (STS), and walking trials as MDR signatures were collected. A 1D Convolutional Neural Network was developed to evaluate each activity individually followed by the development of a fusion model validation using all three activities. ResultsThe STS model individually achieved the highest overall accuracy of 82.3%, with a sensitivity of 71.6% and specificity of 91.0%. The fusion model using all activities achieved a peak overall accuracy to detect ACLR of 86.2%, 80.3% sensitivity, and 91% specificity. ConclusionsCurrently, there is no clinically validated, efficient approach to objectively evaluate human motion at the point of care. When coupled with machine learning, MDR accurately differentiates ACLR from control groups by identifying complex biomechanical asymmetries, with classification performance comparable to or exceeding that of motion capture. Future research is needed to determine if MDR can be used in conjunction with risk prediction modeling. Key pointsMicro-Doppler radar provides a promising new solution to identify important human motion asymmetries in clinical settings. Here we evaluated a group of patients who have a history of Anterior Cruciate Ligament reconstruction versus a control group. Simple movements performed in the presence of the micro-Doppler radar system were used to identify the 2 groups with accuracy comparable or superior to motion capture systems.