Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement

How boots affect the kinematics and kinetics of lower limb joints during walking compared to casual footwear

Boots are widely used by many people for various purposes, but their impact on gait biomechanics and injury risk is not well understood. This study investigated the effects of boots on walking biomechanics, compared to casual footwear. The lower limb joint kinematics and kinetics of 20 healthy male participants aged 20 to 30 years old were compared during self-paced walking with boots and shoes. The results showed that walking with boots is associated with greater hip extensor (P = 0.009) and ankle dorsiflexor (P < 0.001) moments in early stance, hip power generation (P < 0.001) and knee power absorption (P < 0.001) in early swing phase, hip abductor (P < 0.001) and knee adduction (P < 0.001) moments in the entire stance, net concentric work for the hip joint in sagittal (13.9%, P = 0.001) and frontal (21.7%, P = 0.002) planes. In contrast, the subtalar supinator moment in the entire stance (P < 0.001), ankle angular velocity in late stance (P < 0.001), and net concentric (- 42.7%, P < 0.001) and eccentric (- 44.6%, P = 0.004) works of subtalar joint were significantly lower in the boot condition. The compensatory adjustments in the hip and knee joints may result from ankle restrictions. While boots may aid those with ankle disorders, lower limb loading and the risk of musculoskeletal injuries and osteoarthritis could be increased. This study offers new perspectives on the biomechanical impact of boots on gait, potential prevention and treatment strategies of related injuries, and advancing footwear design.

Estimation of the forces exerted on the limb long bones of a white rhinoceros (Ceratotherium simum) using musculoskeletal modelling and simulation

Heavy animals incur large forces on their limb bones, due to the transmission of body weight and ground reaction forces, and the contractions of the various muscles of the limbs. This is particularly true for rhinoceroses, the heaviest extant animals capable of galloping. Several studies have examined their musculoskeletal system and the forces their bones incur, but no detailed quantification has ever been attempted. Such quantification could help understand better the link between form and function in giant land animals. Here we constructed three-dimensional musculoskeletal models of the forelimb and hindlimb of Ceratotherium simum, the heaviest extant rhino species, and used static optimisation (inverse) simulations to estimate the forces applied on the bones when standing at rest, including magnitudes and directions. Overall, unsurprisingly, the most active muscles were antigravity muscles, which generate moments opposing body weight (thereby incurring the ground reaction force), and thus keep the joints extended, avoiding joint collapse via flexion. Some muscles have an antigravity action around several joints, and thus were found to be highly active, likely specialised in body weight support (ulnaris lateralis; digital flexors). The humerus was subjected to the greatest amount of forces in terms of total magnitude; forces on the humerus furthermore came from a great variety of directions. The radius was mainly subject to high-magnitude compressive joint reaction forces, but to little muscular tension, whereas the opposite pattern was observed for the ulna. The femur had a pattern similar to that of the humerus, and the tibia's pattern was intermediate, being subject to great compression in its caudal side but to great tension in its cranial side (i.e. bending). The fibula was subject to by far the lowest force magnitude. Overall, the forces estimated were consistent with the documented morphofunctional adaptations of C. simum's long bones, which have larger insertion areas for several muscles and a greater robusticity overall than those of lighter rhinos, likely reflecting the intense forces we estimated here. Our estimates of muscle and bone (joint) loading regimes for this giant tetrapod improve the understanding of the links between form and function in supportive tissues and could be extended to other aspects of bone morphology, such as microanatomy.

Predicting Knee Joint Contact Forces During Normal Walking Using Kinematic Inputs With a Long-Short Term Neural Network

Knee joint contact forces are commonly estimated via surrogate measures (i.e., external knee adduction moments or musculoskeletal modeling). Despite its capabilities, modeling is not optimal for clinicians or persons with limited experience. The purpose of this study was to design a novel prediction method for knee joint contact forces that is simplistic in terms of required inputs. This study included marker trajectories and instrumented knee forces during normal walking from the "Grand Challenge" (n = 6) and "CAMS" (n = 2) datasets. Inverse kinematics were used to derive stance phase hip (sagittal, frontal, transverse), knee (sagittal, frontal), ankle (sagittal), and trunk (frontal) kinematics. A long-short term memory network (LSTM) was created using matlab to predict medial and lateral knee force waveforms using combinations of the kinematics. The Grand Challenge and CAMS datasets trained and tested the network, respectively. Musculoskeletal modeling forces were derived using static optimization and joint reaction tools in OpenSim. Waveform accuracy was determined as the proportion of variance and root-mean-square error between network predictions and in vivo data. The LSTM network was highly accurate for medial forces (R2 = 0.77, RMSE = 0.27 BW) and required only frontal hip and knee and sagittal hip and ankle kinematics. Modeled medial force predictions were excellent (R2 = 0.77, RMSE = 0.33 BW). Lateral force predictions were poor for both methods (LSTM R2 = 0.18, RMSE = 0.08 BW; modeling R2 = 0.21, RMSE = 0.54 BW). The designed LSTM network outperformed most reports of musculoskeletal modeling, including those reached in this study, revealing knee joint forces can accurately be predicted by using only kinematic input variables.

Exoskeletons vs. exosuits: A comparative analysis using biological-based computer simulation

BACKGROUND

Interest in the design of gait assistance devices has experienced significant growth in recent years. Among various uses of assistive devices, those aimed at supporting the elderly have gained importance due to the rising population of this age group.

METHODS

This study aims to compare the efficacy of two types of assistive devices through musculoskeletal simulations. One case is an ideal device, simulating the motor actuation as it would be in a rigid exoskeleton, and, cable-assisted devices, simulating the assistance of an exosuit. The simulations were based on data obtained from 9 subjects. OpenSim, an open-source software, was employed to conduct the simulations.

RESULTS

Our findings indicate that the cable-assisted device outperforms the traditional exoskeleton by achieving a more significant reduction in the metabolic cost with relatively lower assistance power.

CONCLUSION

Cable-assisted gait assistance devices have shown comparable results to traditional exoskeletons, with the added advantage of improved performance through reduced power requirements.

Marker-Based Versus IMU-Based Kinematics for Estimates of Lumbar Spine Loads Using a Full-Body Musculoskeletal Model

Musculoskeletal modeling, typically implemented using marker-based systems in laboratory environments, is commonly used for noninvasive estimations of loads. Inertial measurement units (IMUs) have become an alternative for the evaluation of kinematics. However, estimates of spine joint contact forces using IMUs have yet to be thoroughly evaluated. Dynamics tasks and static postures from activities of daily living were captured on 11 healthy subjects using both systems simultaneously. Spine kinematics obtained from IMU- and marker-based systems and L4-L5 joint contact forces were compared. Lateral bending resulted in a weak agreement with significant differences between the 2 systems (P = .02, average root mean-squared error = 4.81), whereas flexion-extension and axial rotation exhibited the highest agreement with no significant differences (P < .05, average root mean-squared error = 5.51 and P < .31, average root mean-squared error = 5.08, respectively). All tasks showed excellent correlations (R2 = .76-.99) in estimated loads between systems. Differences in predicted loads at the L4-L5 were only observed during flexion-extension (1041 N vs 947 N, P = .0004) and walking with weights (814 N vs 727 N, P = .004). Different joint reaction force outcomes were obtained in 2 of the 8 tasks between systems, suggesting that IMUs can be robust tools allowing for convenient and less expensive evaluations and for longitudinal assessments inside and outside the laboratory setting.

The Morphology of the Femur Influences the Fracture Risk during Stumbling and Falls on the Hip-A Computational Biomechanical Study

Proximal femur fracture risk depends on subject-specific factors such as bone mineral density and morphological parameters. Here, we aim to analyze the dependency of the femoral strength on sixteen morphological parameters. Therefore, finite-element analyses of 20 human femurs during stumbling and lateral falls on the hip were conducted. Pearson correlation coefficients were calculated and morphological parameters with significant correlations were examined in principal component analysis and linear regression analysis. The dependency of the fracture strength on morphological parameters was more pronounced during lateral falls on the hip compared to stumbling. Significant correlations were observed between the neck shaft angle (r = -0.474), neck diameter (r = 0.507), the true distance between the femoral head center and femoral shaft axis (r = 0.459), and its projected distance on the frontal plane (r = 0.511), greater trochanter height (r = 0.497), and distance between the femoral head center and a plane parallel to the frontal plane containing the projection of the femoral head center to the femoral neck axis (r = 0.669). Principal component analysis was strongly weighted by parameters defining the lever arm during a lateral fall as well as the loaded cross-section in the femoral neck.

A Biomechanical Comparison Between a High and Low Barbell Placement on Net Joint Moments, Kinematics, Muscle Forces, and Muscle-Specific Moments in 3 Repetition Maximum Back Squats

ABSTRACT

Larsen, S, de Zee, M, Kristiansen, EL, and van den Tillaar, R. A biomechanical comparison between a high and low barbell placement on net joint moments, kinematics, muscle forces, and muscle-specific moments in 3 repetition maximum back squats. J Strength Cond Res 38(7): 1221-1230, 2024-This study aimed to investigate the impact of a high barbell vs. low barbell placement on net joint moments, muscle forces, and muscle-specific moments in the lower extremity joints and muscles during maximum back squats. Twelve recreationally trained men (age = 25.3 ± 2.9 years, height = 1.79 ± 7.7 m, and body mass = 82.8 ± 6.9 kg) volunteered for the study. A marker-based motion capture system and force plate data were used to calculate the net joint moments, and individual muscle forces were estimated using static optimization. Muscle forces were multiplied by their corresponding internal moment arms to determine muscle-specific moments. Statistical parametric mapping was used to analyze the effect of barbell placement as time-series data during the concentric phase. The 3 repetition maximum barbell load lifted by the subjects was 129.1 ± 13.4 kg and 130.2 ± 12.7 kg in the high bar and low bar, which were not significantly different from each other. Moreover, no significant differences were observed in net joint moments, muscle forces, or muscle-specific moments for the hip, knee, or ankle joint between the low- and high bar placements. The findings of this study suggest that barbell placement plays a minor role in lower extremity muscle forces and moment-specific moments when stance width is standardized, and barbell load lifted does not differ between barbell placements among recreationally resistance-trained men during maximal back squats. Therefore, the choice of barbell placement should be based on individual preference and comfort.

An articulated shape model to predict paediatric lower limb bone geometry using sparse landmarks

Creating musculoskeletal models in a paediatric population currently involves either creating an image-based model from medical imaging data or a generic model using linear scaling. Image-based models provide a high level of accuracy but are time-consuming and costly to implement, on the other hand, linear scaling of an adult template musculoskeletal model is faster and common practice, but the output errors are significantly higher. An articulated shape model incorporates pose and shape to predict geometry for use in musculoskeletal models based on existing information from a population to provide both a fast and accurate method. From a population of 333 children aged 4-18 years old, we have developed an articulated shape model of paediatric lower limb bones to predict bone geometry from eight bone landmarks commonly used for motion capture. Bone surface root mean squared errors were found to be 2.63 ± 0.90 mm, 1.97 ± 0.61 mm, and 1.72 ± 0.51 mm for the pelvis, femur, and tibia/fibula, respectively. Linear scaling produced bone surface errors of 4.79 ± 1.39 mm, 4.38 ± 0.72 mm, and 4.39 ± 0.86 mm for the pelvis, femur, and tibia/fibula, respectively. Clinical bone measurement errors were low across all bones predicted using the articulated shape model, which outperformed linear scaling for all measurements. However, the model failed to accurately capture torsional measures (femoral anteversion and tibial torsion). Overall, the articulated shape model was shown to be a fast and accurate method to predict lower limb bone geometry in a paediatric population, superior to linear scaling.

Gait balance recovery after tripping: The influence of walking speed and ground inclination on muscle and joint function

Reactive lower limb muscle function during walking plays a key role in balance recovery following tripping, and ultimately fall prevention. The objective of this study was to evaluate muscle and joint function in the recovery limb during balance recovery after trip-based perturbations during walking. Twenty-four healthy participants underwent gait analysis while walking at slow, moderate and fast speeds over level, uphill and downhill inclines. Trip perturbations were performed randomly during stance, and lower limb kinematics, kinetics, and muscle contribution to the acceleration of the whole-body centre of mass (COM) were computed pre- and post-perturbation in the recovery limb. Ground slope and walking speed had a significant effect on lower limb joint angles, net joint moments and muscle contributions to support and propulsion during trip recovery (p < 0.05). Specifically, increasing walking speed during trip recovery significantly reduced hip extension in the recovery limb and increased knee flexion, particularly when walking uphill and at higher walking speeds (p < 0.05). Gluteus maximus played a critical role in providing support and forward propulsion of the body during trip recovery across all gait speeds and ground inclinations. This study provides a mechanistic link between muscle action, joint motion and COM acceleration during trip recovery, and underscores the potential of increased walking speed and ground inclination to increase fall risk, particularly in individuals prone to falling. The findings of this study may provide guidelines for targeted exercise therapy such as muscle strengthening for fall prevention.

An OpenSim thoracolumbar spine model applying a bottom-up modelling approach is similar to a top-down approach

The kinetic demands of the spine can be assessed using a top-down (TD) or bottom-up (BU) approach, which start calculations from the either the hands or from the feet, respectively. Biomechanists have traditionally favored a BU approach, though existing modeling approaches encourage a TD approach. Regardless of the approach the demands should be similar, provided the external forces and linked segment parameters are equivalently measured and modeled. Demonstrating a level of agreement between the two approaches can help evaluate a model. Further, having both approaches can be advantageous when data is inaccurate or unavailable for one. The purpose of this study was to compare the internal moments and forces at multiple lumbar and thoracic intervertebral joint (IVJ) levels during lifting tasks from an established OpenSim thoracolumbar spine model that applies a TD approach and a similar model modified to adopt a BU approach. Kinematics and external forces were recorded from twelve participants during sagittal and lateral lifts of different lifting speeds and crate masses. For both approaches IVJ kinetics were estimated using a standard OpenSim modeling pipeline. The BU and TD approach IVJ joint moments generally agreed both temporally (R2 = .94 ± .17) and in magnitude (RMSE=6.2 ± 3.5 Nm) of the primary planes of movement. There were however some temporal fit exceptions for off axes moments with low magnitudes (i.e., < 10 Nm). Bland-Altman plots also indicated acceptable agreement for IVJ peak forces (BU-TD difference of 12 ± 111 and 8 ± 31 N in compression and resultant shear, respectfully). These results support the application of the BU approach and the assigned linked segment parameters of the model. The new BU model is available on the SimTK site (https://simtk.org/projects/spine_ribcage).

The effect of including a mobile arch, toe joint, and joint coupling on predictive neuromuscular simulations of human walking

Predictive neuromuscular simulations are a powerful tool for studying the biomechanics of human walking, and deriving design criteria for technical devices like prostheses or biorobots. Good agreement between simulation and human data is essential for transferability to the real world. The human foot is often modeled with a single rigid element, but knowledge of how the foot model affects gait prediction is limited. Standardized procedures for selecting appropriate foot models are lacking. We performed 2D predictive neuromuscular simulations with six different foot models of increasing complexity to answer two questions: What is the effect of a mobile arch, a toe joint, and the coupling of toe and arch motion through the plantar fascia on gait prediction? and How much of the foot's anatomy do we need to model to predict sagittal plane walking kinematics and kinetics in good agreement with human data? We found that the foot model had a significant impact on ankle kinematics during terminal stance, push-off, and toe and arch kinematics. When focusing only on hip and knee kinematics, rigid foot models are sufficient. We hope our findings will help guide the community in modeling the human foot according to specific research goals and improve neuromuscular simulation accuracy.

Experiment-guided tuning of muscle-tendon parameters to estimate muscle fiber lengths and passive forces

The workflow to simulate motion with recorded data usually starts with selecting a generic musculoskeletal model and scaling it to represent subject-specific characteristics. Simulating muscle dynamics with muscle-tendon parameters computed from existing scaling methods in literature, however, yields some inconsistencies compared to measurable outcomes. For instance, simulating fiber lengths and muscle excitations during walking with linearly scaled parameters does not resemble established patterns in the literature. This study presents a tool that leverages reported in vivo experimental observations to tune muscle-tendon parameters and evaluates their influence in estimating muscle excitations and metabolic costs during walking. From a scaled generic musculoskeletal model, we tuned optimal fiber length, tendon slack length, and tendon stiffness to match reported fiber lengths from ultrasound imaging and muscle passive force-length relationships to match reported in vivo joint moment-angle relationships. With tuned parameters, muscle contracted more isometrically, and soleus's operating range was better estimated than with linearly scaled parameters. Also, with tuned parameters, on/off timing of nearly all muscles' excitations in the model agreed with reported electromyographic signals, and metabolic rate trajectories varied significantly throughout the gait cycle compared to linearly scaled parameters. Our tool, freely available online, can customize muscle-tendon parameters easily and be adapted to incorporate more experimental data.

Bridging the sim2real gap. Investigating deviations between experimental motion measurements and musculoskeletal simulation results-a systematic review

Musculoskeletal simulations can be used to estimate biomechanical variables like muscle forces and joint torques from non-invasive experimental data using inverse and forward methods. Inverse kinematics followed by inverse dynamics (ID) uses body motion and external force measurements to compute joint movements and the corresponding joint loads, respectively. ID leads to residual forces and torques (residuals) that are not physically realistic, because of measurement noise and modeling assumptions. Forward dynamic simulations (FD) are found by tracking experimental data. They do not generate residuals but will move away from experimental data to achieve this. Therefore, there is a gap between reality (the experimental measurements) and simulations in both approaches, the sim2real gap. To answer (patho-) physiological research questions, simulation results have to be accurate and reliable; the sim2real gap needs to be handled. Therefore, we reviewed methods to handle the sim2real gap in such musculoskeletal simulations. The review identifies, classifies and analyses existing methods that bridge the sim2real gap, including their strengths and limitations. Using a systematic approach, we conducted an electronic search in the databases Scopus, PubMed and Web of Science. We selected and included 85 relevant papers that were sorted into eight different solution clusters based on three aspects: how the sim2real gap is handled, the mathematical method used, and the parameters/variables of the simulations which were adjusted. Each cluster has a distinctive way of handling the sim2real gap with accompanying strengths and limitations. Ultimately, the method choice largely depends on various factors: available model, input parameters/variables, investigated movement and of course the underlying research aim. Researchers should be aware that the sim2real gap remains for both ID and FD approaches. However, we conclude that multimodal approaches tracking kinematic and dynamic measurements may be one possible solution to handle the sim2real gap as methods tracking multimodal measurements (some combination of sensor position/orientation or EMG measurements), consistently lead to better tracking performances. Initial analyses show that motion analysis performance can be enhanced by using multimodal measurements as different sensor technologies can compensate each other's weaknesses.

Human motion data expansion from arbitrary sparse sensors with shallow recurrent decoders

Advances in deep learning and sparse sensing have emerged as powerful tools for monitoring human motion in natural environments. We develop a deep learning architecture, constructed from a shallow recurrent decoder network, that expands human motion data by mapping a limited (sparse) number of sensors to a comprehensive (dense) configuration, thereby inferring the motion of unmonitored body segments. Even with a single sensor, we reconstruct the comprehensive set of time series measurements, which are important for tracking and informing movement-related health and performance outcomes. Notably, this mapping leverages sensor time histories to inform the transformation from sparse to dense sensor configurations. We apply this mapping architecture to a variety of datasets, including controlled movement tasks, gait pattern exploration, and free-moving environments. Additionally, this mapping can be subject-specific (based on an individual's unique data for deployment at home and in the community) or group-based (where data from a large group are used to learn a general movement model and predict outcomes for unknown subjects). By expanding our datasets to unmeasured or unavailable quantities, this work can impact clinical trials, robotic/device control, and human performance by improving the accuracy and availability of digital biomarker estimates.

Cost function criteria using muscle synergies: Exploring the potential of muscle synergy hypothesis

BACKGROUND AND OBJECTIVE

Solving the redundant optimization problem for human muscles depends on the cost function. Choosing the appropriate cost function helps to address a specific problem. Muscle synergies are currently limited to those obtained by electromyography. Furthermore, debate continues regarding whether muscle synergy is derived or real. This study proposes new cost functions based on the muscle synergy hypothesis for solving the optimal muscle force output problem through musculoskeletal modeling.

METHODS

We propose two new computational cost functions involving muscle synergies, which are extracted from muscle activations predicted by musculoskeletal modelling rather than electromyography. In this study, we constructed a musculoskeletal model for simulation using the "Grand Challenge Competition to Predict In Vivo Knee Loads" dataset. Muscle synergies were obtained using non-negative matrix factorization. Two cost functions with muscle synergies were constructed by integrating the polynomial and min/max criterion. Two new functions were verified and validated in normal, smooth, and bouncy gaits.

RESULTS

The muscle synergies based on normal gaits were classified into four modules. The cosine similarities of the first three modules were all >0.9. In the normal and smooth gaits, the forces in most muscles predicted using the two new functions were within three standard deviations of the root mean square error for electromyographic comparisons. Predicted muscle force curves using the four methods as well as characteristic points (i.e., time points in the gait cycle when the significant difference was observed between normal and bouncy gaits) were obtained to validate their predictive capabilities.

CONCLUSIONS

This study constructed two new cost functions involving muscle synergies, verified and validated the ability, and explored the potential of muscle synergy hypothesis.

Advanced subject-specific neck musculoskeletal modeling unveils sex differences in muscle moment arm and cervical spine loading

Neck pain and injuries are growing healthcare burdens with women having a higher incidence rate and poorer treatment outcomes than males. A better understanding of sex differences in neck biomechanics, foundational for more targeted, effective prevention or treatment strategies, calls for more advanced subject-specific musculoskeletal modeling. Current neck musculoskeletal models are based on generic anatomy, lack subject specificity beyond anthropometric scaling, and are unable to accurately reproduce neck strengths exhibited in vivo without arbitrary muscle force scaling factors or residual torque actuators. In this work, subject-specific neck musculoskeletal models of 23 individuals (11 male, 12 female) were constructed by integrating multi-modality imaging and biomechanical measurements. Each model simulated maximal voluntary neck static exertions in three postures: neck flexion in a neutral posture, flexion in a 40° extended posture, and extension in a 40° flexed posture. Quantitative model validation showed close agreement between model-predicted muscle activation and EMG measurement. The models unveiled that (1) males have greater moment arms in one flexor muscle group and five extensor muscle groups, (2) females exhibited higher cervical spinal compression per unit exertion force in the flexed posture, and (3) the variability of compression force was much greater in females in all three exertions but most notably in the extension with a flexed "dropped head" position. These insights illuminated a plausible pathway from sex differences in neck biomechanics to sex disparities in the risk and prevalence of neck pain.

AST: An OpenSim-based tool for the automatic scaling of generic musculoskeletal models

BACKGROUND AND OBJECTIVES

The paper introduces a tool called Automatic Scaling Tool (AST) designed for improving and expediting musculoskeletal (MSK) simulations based on generic models in OpenSim. Scaling is a crucial initial step in MSK analyses, involving the correction of virtual marker locations on a model to align with actual experimental markers.

METHODS

The AST automates this process by iteratively adjusting virtual markers using scaling and inverse kinematics on a static trial. It evaluates the root mean square error (RMSE) and maximum marker error, implementing corrective actions until achieving the desired accuracy level. The tool determines whether to scale a segment with a marker-based or constant scaling factor based on checks on RMSE and segment scaling factors.

RESULTS

Testing on three generic MSK models demonstrated that the AST significantly outperformed manual scaling by an expert operator. The RMSE for static trials was one order of magnitude lower, and for gait tasks, it was five times lower (8.5 ± 0.76 mm vs. 44.5 ± 7.5 mm). The AST consistently achieved the desired level of accuracy in less than 100 iterations, providing reliable scaled MSK models within a relatively brief timeframe, ranging from minutes to hours depending on model complexity.

CONCLUSIONS

The paper concludes that AST can greatly benefit the biomechanical community by quickly and accurately scaling generic models, a critical first step in MSK analyses. Further validation through additional experimental datasets and generic models is proposed for future tests.

Soft tissue material properties based on human abdominal in vivo macro-indenter measurements

Simulations of human-technology interaction in the context of product development require comprehensive knowledge of biomechanical in vivo behavior. To obtain this knowledge for the abdomen, we measured the continuous mechanical responses of the abdominal soft tissue of ten healthy participants in different lying positions anteriorly, laterally, and posteriorly under local compression depths of up to 30 mm. An experimental setup consisting of a mechatronic indenter with hemispherical tip and two time-of-flight (ToF) sensors for optical 3D displacement measurement of the surface was developed for this purpose. To account for the impact of muscle tone, experiments were conducted with both controlled activation and relaxation of the trunk muscles. Surface electromyography (sEMG) was used to monitor muscle activation levels. The obtained data sets comprise the continuous force-displacement data of six abdominal measurement regions, each synchronized with the local surface displacements resulting from the macro-indentation, and the bipolar sEMG signals at three key trunk muscles. We used inverse finite element analysis (FEA), to derive sets of nonlinear material parameters that numerically approximate the experimentally determined soft tissue behaviors. The physiological standard values obtained for all participants after data processing served as reference data. The mean stiffness of the abdomen was significantly different when the trunk muscles were activated or relaxed. No significant differences were found between the anterior-lateral measurement regions, with exception of those centered on the linea alba and centered on the muscle belly of the rectus abdominis below the intertubercular plane. The shapes and areas of deformation of the skin depended on the region and muscle activity. Using the hyperelastic Ogden model, we identified unique material parameter sets for all regions. Our findings confirmed that, in addition to the indenter force-displacement data, knowledge about tissue deformation is necessary to reliably determine unique material parameter sets using inverse FEA. The presented results can be used for finite element (FE) models of the abdomen, for example, in the context of orthopedic or biomedical product developments.

New Insights Optimize Landing Strategies to Reduce Lower Limb Injury Risk

Single-leg landing (SL) is often associated with a high injury risk, especially anterior cruciate ligament (ACL) injuries and lateral ankle sprain. This work investigates the relationship between ankle motion patterns (ankle initial contact angle [AICA] and ankle range of motion [AROM]) and the lower limb injury risk during SL, and proposes an optimized landing strategy that can reduce the injury risk. To more realistically revert and simulate the ACL injury mechanics, we developed a knee musculoskeletal model that reverts the ACL ligament to a nonlinear short-term viscoelastic mechanical mechanism (strain rate-dependent) generated by the dense connective tissue as a function of strain. Sixty healthy male subjects were recruited to collect biomechanics data during SL. The correlation analysis was conducted to explore the relationship between AICA, AROM, and peak vertical ground reaction force (PVGRF), joint total energy dissipation (TED), peak ankle knee hip sagittal moment, peak ankle inversion angle (PAIA), and peak ACL force (PAF). AICA exhibits a negative correlation with PVGRF (r = -0.591) and PAF (r = -0.554), and a positive correlation with TED (r = 0.490) and PAIA (r = 0.502). AROM exhibits a positive correlation with TED (r = 0.687) and PAIA (r = 0.600). The results suggested that the appropriate increases in AICA (30° to 40°) and AROM (50° to 70°) may reduce the lower limb injury risk. This study has the potential to offer novel perspectives on the optimized application of landing strategies, thus giving the crucial theoretical basis for decreasing injury risk.

The biomechanical influence of transtibial Bone-Anchored limbs during walking

Individuals with unilateral transtibial amputation (TTA) using socket prostheses demonstrate asymmetric joint biomechanics during walking, which increases the risk of secondary comorbidities (e.g., low back pain (LBP), osteoarthritis (OA)). Bone-anchored limbs are an alternative to socket prostheses, yet it remains unknown how they influence multi-joint loading. Our objective was to determine the influence of bone-anchored limb use on multi-joint biomechanics during walking. Motion capture data (kinematics, ground reaction forces) were collected during overground walking from ten participants with unilateral TTA prior to (using socket prostheses) and 12-months after bone-anchored limb implantation. Within this year, each participant completed a rehabilitation protocol that guided progression of loading based on patient pain response and optimized biomechanics. Musculoskeletal models were developed at each testing timepoint (baseline or 12-months after implantation) and used to calculate joint kinematics, internal joint moments, and joint reaction forces (JRFs). Analyses were performed during three stance periods on each limb. The between-limb normalized symmetry index (NSI) was calculated for joint moments and JRF impulses. Discrete (range of motion (ROM), impulse NSI) dependent variables were compared before and after implantation using paired t-tests with Bonferroni-Holm corrections while continuous (ensemble averages of kinematics, moments, JRFs) were compared using statistical parametric mapping (p < 0.05). When using a bone-anchored limb, frontal plane pelvic (residual: pre = 9.6 ± 3.3°, post = 6.3 ± 2.5°, p = 0.004; intact: pre = 10.2 ± 3.9°, post = 7.9 ± 2.6°, p = 0.006) and lumbar (residual: pre = 15.9 ± 7.0°, post = 10.6 ± 2.5°, p = 0.024, intact: pre = 17.1 ± 7.0°, post = 11.4 ± 2.8°, p = 0.014) ROM was reduced compared to socket prosthesis use. The intact limb hip extension moment impulse increased (pre = -11.0 ± 3.6 Nm*s/kg, post = -16.5 ± 4.4 Nm*s/kg, p = 0.005) and sagittal plane hip moment impulse symmetry improved (flexion: pre = 23.1 ± 16.0 %, post = -3.9 ± 19.5 %, p = 0.004, extension: pre = 29.2 ± 20.3 %, post = 8.7 ± 22.9 %, p = 0.049). Residual limb knee extension moment impulse decreased compared to baseline (pre = 15.7 ± 10.8 Nm*s/kg, post = 7.8 ± 3.9 Nm*s/kg, p = 0.030). These results indicate that bone-anchored limb implantation alters multi-joint biomechanics, which may impact LBP or OA risk factors in the TTA population longitudinally.

Muscle Morphology Does Not Solely Determine Knee Flexion Weakness After Anterior Cruciate Ligament Reconstruction with a Semitendinosus Tendon Graft: A Combined Experimental and Computational Modeling Study

The distal semitendinosus tendon is commonly harvested for anterior cruciate ligament reconstruction, inducing substantial morbidity at the knee. The aim of this study was to probe how morphological changes of the semitendinosus muscle after harvest of its distal tendon for anterior cruciate ligament reconstruction affects knee flexion strength and whether the knee flexor synergists can compensate for the knee flexion weakness. Ten participants 8-18 months after anterior cruciate ligament reconstruction with an ipsilateral distal semitendinosus tendon autograft performed isometric knee flexion strength testing (15°, 45°, 60°, and 90°; 0° = knee extension) positioned prone on an isokinetic dynamometer. Morphological parameters extracted from magnetic resonance images were used to inform a musculoskeletal model. Knee flexion moments estimated by the model were then compared with those measured experimentally at each knee angle position. A statistically significant between-leg difference in experimentally-measured maximal isometric strength was found at 60° and 90°, but not 15° or 45°, of knee flexion. The musculoskeletal model matched the between-leg differences observed in experimental knee flexion moments at 15° and 45° but did not well estimate between-leg differences with a more flexed knee, particularly at 90°. Further, the knee flexor synergists could not physiologically compensate for weakness in deep knee flexion. These results suggest additional factors other than knee flexor muscle morphology play a role in knee flexion weakness following anterior cruciate ligament reconstruction with a distal semitendinosus tendon graft and thus more work at neural and microscopic levels is required for informing treatment and rehabilitation in this demographic.

The quest for dynamic consistency: a comparison of OpenSim tools for residual reduction in simulations of human running

Using synchronous kinematic and kinetic data in simulations of human running typically leads to dynamic inconsistencies. Minimizing residual forces and moments is subsequently important to ensure plausible model outputs. A variety of approaches suitable for residual reduction are available in OpenSim; however, a detailed comparison is yet to be conducted. This study compared OpenSim tools applicable for residual reduction in simulations of human running. Multiple approaches (i.e. Residual Reduction Algorithm, MocoTrack, AddBiomechanics) designed to reduce residual forces and moments were examined using an existing dataset of treadmill running at 5.0 ms-1. The computational time, residual forces and moments, and joint kinematics and kinetics from each approach were compared. A computational cost to residual reduction trade-off was identified, where lower residuals were achieved using approaches with longer computational times. The AddBiomechanics and MocoTrack approaches produced variable lower and upper body kinematics, respectively, versus the remaining approaches. Joint kinetics were similar between approaches; however, MocoTrack generated noisier upper limb joint torque signals. MocoTrack was the best-performing approach for reducing residuals to near-zero levels, at the cost of longer computational times. This study provides OpenSim users with evidence to inform decision-making at the residual reduction step of their workflow.

Psoas force recruitment in full-body musculoskeletal movement simulations is restored with a geometrically informed cost function weighting

Simulations of musculoskeletal models are useful for estimating internal muscle and joint forces. However, predicted forces rely on optimization and modeling formulations. Geometric detail is important to predict muscle forces, and greater geometric complexity is required for muscles that have broad attachments or span many joints, as in the torso. However, the extent to which optimized muscle force recruitment is sensitive to these geometry choices is unclear. We developed level, uphill and downhill sloped walking simulations using a standard (uniformly weighted, "fatigue-like") cost function with lower limb and full-body musculoskeletal models to evaluate hip muscle recruitment with different geometric representations of the psoas muscle under walking conditions with varying hip moment demands. We also tested a novel cost function formulation where muscle activations were weighted according to the modeled geometric detail in the full-body model. Total psoas force was less and iliacus, rectus femoris, and other hip flexors' force was greater when psoas was modeled with greater geometric detail compared to other hip muscles for all slopes. The proposed weighting scheme restored hip muscle force recruitment without sacrificing detailed psoas geometry. In addition, we found that lumbar, but not hip, joint contact forces were influenced by psoas force recruitment. Our results demonstrate that static optimization dependent simulations using models comprised of muscles with different amounts of geometric detail bias force recruitment toward muscles with less geometric detail. Muscle activation weighting that accounts for differences in geometric complexity across muscles corrects for this recruitment bias.

Validity of muscle activation estimated with predicted ground reaction force in inverse dynamics based musculoskeletal simulation during gait

The inverse dynamics based musculoskeletal simulation needs ground reaction forces (GRF) as an external force input. GRF can be predicted from kinematic data. However, the validity of estimated muscle activation using the predicted GRF has remained unclear. Therefore, the purpose of this study was to determine the validity of estimated muscle activation with predicted GRF in the inverse dynamics based musculoskeletal simulation. To perform musculoskeletal simulations, an open-source motion capture dataset that contains gait data from 50 healthy subjects was used. CusToM was used for the musculoskeletal simulations. Two sets of inverse dynamics and static optimization were performed, one used predicted GRF (PRED) and another used experimentally measured GRF (EXP). Pearson's correlation was calculated to evaluate the similarity between EMG and estimated muscle activations for both PRED and EXP. To compare PRED and EXP, paired t-tests were used to compare the trial-wise muscle activation similarity and residuals. Relationships between joint moments and residuals were also tested. The overall muscle activation similarity was comparable in PRED (R = 0.477) and EXP (R = 0.475). The residuals were 2-4 times higher in EXP compared to PRED (P < 0.001). The hip flexion-extension moment was correlated to sagittal plane residual moment (R = 0.467). The muscle activations estimated using predicted GRF were comparable to that with measured GRF in the inverse dynamics based musculoskeletal simulation. Prediction of GRF helps to perform musculoskeletal simulations where the force plates are not available.

Optimal fibre length and maximum isometric force are the most influential parameters when modelling muscular adaptations to unloading using Hill-type muscle models

Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

Estimating 3D kinematics and kinetics from virtual inertial sensor data through musculoskeletal movement simulations

Portable measurement systems using inertial sensors enable motion capture outside the lab, facilitating longitudinal and large-scale studies in natural environments. However, estimating 3D kinematics and kinetics from inertial data for a comprehensive biomechanical movement analysis is still challenging. Machine learning models or stepwise approaches performing Kalman filtering, inverse kinematics, and inverse dynamics can lead to inconsistencies between kinematics and kinetics. We investigated the reconstruction of 3D kinematics and kinetics of arbitrary running motions from inertial sensor data using optimal control simulations of full-body musculoskeletal models. To evaluate the feasibility of the proposed method, we used marker tracking simulations created from optical motion capture data as a reference and for computing virtual inertial data such that the desired solution was known exactly. We generated the inertial tracking simulations by formulating optimal control problems that tracked virtual acceleration and angular velocity while minimizing effort without requiring a task constraint or an initial state. To evaluate the proposed approach, we reconstructed three trials each of straight running, curved running, and a v-cut of 10 participants. We compared the estimated inertial signals and biomechanical variables of the marker and inertial tracking simulations. The inertial data was tracked closely, resulting in low mean root mean squared deviations for pelvis translation (≤20.2 mm), angles (≤1.8 deg), ground reaction forces (≤1.1 BW%), joint moments (≤0.1 BWBH%), and muscle forces (≤5.4 BW%) and high mean coefficients of multiple correlation for all biomechanical variables ( ≥ 0.99 ) . Accordingly, our results showed that optimal control simulations tracking 3D inertial data could reconstruct the kinematics and kinetics of individual trials of all running motions. The simulations led to mutually and dynamically consistent kinematics and kinetics, which allows researching causal chains, for example, to analyze anterior cruciate ligament injury prevention. Our work proved the feasibility of the approach using virtual inertial data. When using the approach in the future with measured data, the sensor location and alignment on the segment must be estimated, and soft-tissue artifacts are potential error sources. Nevertheless, we demonstrated that optimal control simulation tracking inertial data is highly promising for estimating 3D kinematics and kinetics for a comprehensive biomechanical analysis.

Estimation of lower back muscle force in a lifting task using wearable IMUs

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

Design and Evaluation of a Bilateral Semi-Rigid Exoskeleton to Assist Hip Motion

This study focused on designing and evaluating a bilateral semi-rigid hip exoskeleton. The exoskeleton assisted the hip joint, capitalizing on its proximity to the body's center of mass. Unlike its rigid counterparts, the semi-rigid design permitted greater freedom of movement. A temporal force-tracking controller allowed us to prescribe torque profiles during walking. We ensured high accuracy by tuning control parameters and series elasticity. The evaluation involved experiments with ten participants across ten force profile conditions with different end-timings and peak magnitudes. Our findings revealed a trend of greater reductions in metabolic cost with assistance provided at later timings in stride and at greater magnitudes. Compared to walking with the exoskeleton powered off, the largest reduction in metabolic cost was 9.1%. This was achieved when providing assistance using an end-timing at 44.6% of the stride cycle and a peak magnitude of 0.11 Nm kg-1. None of the tested conditions reduced the metabolic cost compared to walking without the exoskeleton, highlighting the necessity for further enhancements, such as a lighter and more form-fitting design. The optimal end-timing aligns with findings from other soft hip exosuit devices, indicating a comparable interaction with this prototype to that observed in entirely soft exosuit prototypes.

Influence of posterior cruciate ligament tension on tibiofemoral and patellofemoral joint contact mechanics in cruciate-retaining total knee replacement: a combined musculoskeletal multibody and finite-element simulation

The influence of posterior cruciate ligament (PCL) tension on the clinical outcome of cruciate-retaining total knee replacement (CR-TKR) remains controversial. Various numerical approaches have been used to study this influence systematically, but the models used are limited by certain assumptions and simplifications. Therefore, the objective of this computational study was to develop a combined musculoskeletal multibody and finite-element simulation during a squat motion to 90° knee flexion with a CR-TKR design to overcome previous limitations regarding model inputs. In addition, different PCL tensions (tight, lax, resected) were modeled and the influence on tibiofemoral and resurfaced patellofemoral joint dynamics and contact stresses was evaluated. The effect of the PCL on knee joint dynamics and contact stresses was more pronounced at higher flexion angles. Tibiofemoral joint dynamics were influenced and a tight PCL induced increased posterior femoral translation during flexion. The maximum contact stress in the tibial insert increased from 20.6 MPa to 22.5 MPa for the resected and tightest PCL at 90° knee flexion. Patellofemoral joint dynamics were only slightly affected by PCL tension. However, the maximum contact stress in the patellar component decreased from 58.0 MPa to 53.7 MPa for the resected and tightest PCL at 90° knee flexion. The combination of musculoskeletal multibody and finite-element simulation is a sufficient method to comprehensively investigate knee joint dynamics and contact stresses in CR-TKR. The PCL tension after CR-TKR affects joint dynamics and contact stresses at the articulating implant surfaces.

Inter-trial variability is higher in 3D markerless compared to marker-based motion capture: Implications for data post-processing and analysis

Markerless motion capture has recently attracted significant interest in clinical gait analysis and human movement science. Its ease of use and potential to streamline motion capture recordings bear great potential for out-of-the-laboratory measurements in large cohorts. While previous studies have shown that markerless systems can achieve acceptable accuracy and reliability for kinematic parameters of gait, they also noted higher inter-trial variability of markerless data. Since increased inter-trial variability can have important implications for data post-processing and analysis, this study compared the inter-trial variability of simultaneously recorded markerless and marker-based data. For this purpose, the data of 18 healthy volunteers were used who were instructed to simulate four different gait patterns: physiological, crouch, circumduction, and equinus gait. Gait analysis was performed using the smartphone-based markerless system OpenCap and a marker-based motion capture system. We compared the inter-trial variability of both systems and also evaluated if changes in inter-trial variability may depend on the analyzed gait pattern. Compared to the marker-based data, we observed an increase of inter-trial variability for the markerless system ranging from 6.6% to 22.0% for the different gait patterns. Our findings demonstrate that the markerless pose estimation pipelines can introduce additionally variability in the kinematic data across different gait patterns and levels of natural variability. We recommend using averaged waveforms rather than single ones to mitigate this problem. Further, caution is advised when using variability-based metrics in gait and human movement analysis based on markerless data as increased inter-trial variability can lead to misleading results.

Musculoskeletal model degrees of Freedom: Frontal plane constraints are hindering our understanding of human movement

Induced acceleration analyses have expanded our understanding on the contributions of muscle forces to center of mass and segmental kinematics during a myriad of tasks. While these techniques have identified a subset of major muscle that contribute to locomotion, most analyses have included models with only one frontal plane degree of freedom (dof) actuated by the hip joint. The purpose of this study was to define the impact of including knee and subtalar joint frontal plane dof on model superposition accuracy and muscle specific contributions to mediolateral accelerations. Induced acceleration analyses were performed using OpenSim with the Lai model on a freely available dataset of one subject running at 4 m/s. Analyses were performed on four models (standard, with subtalar joint, with frontal plane knee, and combined frontal plane knee with subtalar) with the kinematic constraint and perturbation analyses. Root mean square error and correlations were computed against experimental kinematics. Adding frontal plane dofs improved mediolateral acceleration correlations on average by > 0.25 while only minimally impacting errors. The constraints method performed better than the perturbation method for mediolateral accelerations. Including frontal plane knee dof resulted in muscle and method specific responses. All muscles presented with a complete flip of polarity for constraint method, imparted by allowing the medial/lateral muscles to contribute according to their anatomical function. Only the gluteus medius flipped for the perturbation method. This study provides significant support for the inclusion of frontal plane knee and subtalar dof and the need for reevaluation of muscle contributions via induced acceleration.

Comparing spinal loads in individuals with unilateral transtibial amputation with and without chronic low back pain: An EMG-informed approach

Chronic low back pain (cLBP) is highly prevalent after lower limb amputation (LLA), likely due in part to biomechanical factors. Here, three-dimensional full-body kinematics and kinetics during level-ground walking, at a self-selected and three controlled speeds (1.0, 1.3, and 1.6 m/s), were collected from twenty-one persons with unilateral transtibial LLA, with (n = 9) and without cLBP (n = 12). Peak compressive, mediolateral, and anteroposterior L5-S1 spinal loads were estimated from a full-body, transtibial amputation-specific OpenSim model and compared between groups. Predicted lumbar joint torques from muscle activations were compared to inverse dynamics and predicted and measured electromyographic muscle activations were compared for model evaluation and verification. There were no group differences in compressive or anterior shear forces (p > 0.466). During intact stance, peak ipsilateral loads increased with speed to a greater extent in the cLBP group vs. no cLBP group (p=0.023), while during prosthetic stance, peak contralateral loads were larger in the no cLBP group (p=0.047) and increased to a greater extent with walking speed compared to the cLBP group (p=0.008). During intact stance, intact side external obliques had higher activations in the no cLBP group (p=0.039), and internal obliques had higher activations in the cLBP group at faster walking speeds compared to the no cLBP group. Predicted muscle activations demonstrated similar activation patterns to electromyographic-measured activations (r = 0.56-0.96), and error between inverse dynamics and simulated spinal moments was low (0.08 Nm RMS error). Persons with transtibial LLA and cLBP may adopt movement strategies during walking to reduce mediolateral shear forces at the L5-S1 joint, particularly as walking speed increases. However, future work is needed to understand the time course from pain onset to chronification and the cumulative influence of increased spinal loads over time.

Hip Contact Forces During Sprinting in Femoroacetabular Impingement Syndrome

PURPOSE

Sprinting often provokes hip pain in individuals with femoroacetabular impingement syndrome (FAIS). Asphericity of the femoral head-neck junction (cam morphology) characteristic of FAIS can increase the risk of anterior-superior acetabular cartilage damage. This study aimed to 1) compare hip contact forces (magnitude and direction) during sprinting between individuals with FAIS, asymptomatic cam morphology (CAM), and controls without cam morphology, and 2) identify the phases of sprinting with high levels of anteriorly directed hip contact forces.

METHODS

Forty-six recreationally active individuals with comparable levels of physical activity were divided into three groups (FAIS, 14; CAM, 15; control, 17) based on their history of hip/groin pain, results of clinical impingement tests, and presence of cam morphology (alpha angle >55°). Three-dimensional marker trajectories, ground reaction forces, and electromyograms from 12 lower-limb muscles were recorded during 10-m overground sprinting trials. A linearly scaled electromyogram-informed neuromusculoskeletal model was used to calculate hip contact force magnitude (resultant, anterior-posterior, inferior-superior, medio-lateral) and angle (sagittal and frontal planes). Between-group comparisons were made using two-sample t -tests via statistical parametric mapping ( P < 0.05).

RESULTS

No significant differences in magnitude or direction of hip contact forces were observed between FAIS and CAM or between FAIS and control groups during any phase of the sprint cycle. The highest anteriorly directed hip contact forces were observed during the initial swing phase of the sprint cycle.

CONCLUSIONS

Hip contact forces during sprinting do not differentiate recreationally active individuals with FAIS from asymptomatic individuals with and without cam morphology. Hip loading during early swing, where peak anterior loading occurs, may be a potential mechanism for cartilage damage during sprinting-related sports in individuals with FAIS and/or asymptomatic cam morphology.

NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

Mechanics of the foot and ankle joints during running using a multi-segment foot model compared with a single-segment model

The primary purpose of this study was to compare the ankle joint mechanics, during the stance phase of running, computed with a multi-segment foot model (MULTI; three segments) with a traditional single segment foot model (SINGLE). Traditional ankle joint models define all bones between the ankle and metatarsophalangeal joints as a single rigid segment (SINGLE). However, this contrasts with the more complex structure and mobility of the human foot, recent studies of walking using more multiple-segment models of the human foot have highlighted the errors arising in ankle kinematics and kinetics by using an oversimplified model of the foot. This study sought to compare whether ankle joint kinematics and kinetics during running are similar when using a single segment foot model (SINGLE) and a multi-segment foot model (MULTI). Seven participants ran at 3.1 m/s while the positions of markers on the shank and foot were tracked and ground reaction forces were measured. Ankle joint kinematics, resultant joint moments, joint work, and instantaneous joint power were determined using both the SINGLE and MULTI models. Differences between the two models across the entire stance phase were tested using statistical parametric mapping. During the stance phase, MULTI produced ankle joint angles that were typically closer to neutral and angular velocities that were reduced compared with SINGLE. Instantaneous joint power (p<0.001) and joint work (p<0.001) during late stance were also reduced in MULTI compared with SINGLE demonstrating the importance of foot model topology in analyses of the ankle joint during running. This study has highlighted that considering the foot as a rigid segment from ankle to MTP joint produces poor estimates of the ankle joint kinematics and kinetics, which has important implications for understanding the role of the ankle joint in running.

A framework based on subject-specific musculoskeletal models and Monte Carlo simulations to personalize muscle coordination retraining

Excessive loads at lower limb joints can lead to pain and degenerative diseases. Altering joint loads with muscle coordination retraining might help to treat or prevent clinical symptoms in a non-invasive way. Knowing how much muscle coordination retraining can reduce joint loads and which muscles have the biggest impact on joint loads is crucial for personalized gait retraining. We introduced a simulation framework to quantify the potential of muscle coordination retraining to reduce joint loads for an individuum. Furthermore, the proposed framework enables to pinpoint muscles, which alterations have the highest likelihood to reduce joint loads. Simulations were performed based on three-dimensional motion capture data of five healthy adolescents (femoral torsion 10°-29°, tibial torsion 19°-38°) and five patients with idiopathic torsional deformities at the femur and/or tibia (femoral torsion 18°-52°, tibial torsion 3°-50°). For each participant, a musculoskeletal model was modified to match the femoral and tibial geometry obtained from magnetic resonance images. Each participant's model and the corresponding motion capture data were used as input for a Monte Carlo analysis to investigate how different muscle coordination strategies influence joint loads. OpenSim was used to run 10,000 simulations for each participant. Root-mean-square of muscle forces and peak joint contact forces were compared between simulations. Depending on the participant, altering muscle coordination led to a maximum reduction in hip, knee, patellofemoral and ankle joint loads between 5 and 18%, 4% and 45%, 16% and 36%, and 2% and 6%, respectively. In some but not all participants reducing joint loads at one joint increased joint loads at other joints. The required alteration in muscle forces to achieve a reduction in joint loads showed a large variability between participants. The potential of muscle coordination retraining to reduce joint loads depends on the person's musculoskeletal geometry and gait pattern and therefore showed a large variability between participants, which highlights the usefulness and importance of the proposed framework to personalize gait retraining.

A novel computational framework for the estimation of internal musculoskeletal loading and muscle adaptation in hypogravity

Introduction: Spaceflight is associated with substantial and variable musculoskeletal (MSK) adaptations. Characterisation of muscle and joint loading profiles can provide key information to better align exercise prescription to astronaut MSK adaptations upon return-to-Earth. A case-study is presented of single-leg hopping in hypogravity to demonstrate the additional benefit computational MSK modelling has when estimating lower-limb MSK loading. Methods: A single male participant performed single-leg vertical hopping whilst attached to a body weight support system to replicate five gravity conditions (0.17, 0.25, 0.37, 0.50, 1 g). Experimental joint kinematics, joint kinetics and ground reaction forces were tracked in a data-tracking direct collocation simulation framework. Ground reaction forces, sagittal plane hip, knee and ankle net joint moments, quadriceps muscle forces (Rectus Femoris and three Vasti muscles), and hip, knee and ankle joint reaction forces were extracted for analysis. Estimated quadriceps muscle forces were input into a muscle adaptation model to predict a meaningful increase in muscle cross-sectional area, defined in (DeFreitas et al., 2011). Results: Two distinct strategies were observed to cope with the increase in ground reaction forces as gravity increased. Hypogravity was associated with an ankle dominant strategy with increased range of motion and net plantarflexor moment that was not seen at the hip or knee, and the Rectus Femoris being the primary contributor to quadriceps muscle force. At 1 g, all three joints had increased range of motion and net extensor moments relative to 0.50 g, with the Vasti muscles becoming the main muscles contributing to quadriceps muscle force. Additionally, hip joint reaction force did not increase substantially as gravity increased, whereas the other two joints increased monotonically with gravity. The predicted volume of exercise needed to counteract muscle adaptations decreased substantially with gravity. Despite the ankle dominant strategy in hypogravity, the loading on the knee muscles and joint also increased, demonstrating this provided more information about MSK loading. Discussion: This approach, supplemented with muscle-adaptation models, can be used to compare MSK loading between exercises to enhance astronaut exercise prescription.

NSF DARE-transforming modeling in neurorehabilitation: perspectives and opportunities from US funding agencies

In recognition of the importance and timeliness of computational models for accelerating progress in neurorehabilitation, the U.S. National Science Foundation (NSF) and the National Institutes of Health (NIH) sponsored a conference in March 2023 at the University of Southern California that drew global participation from engineers, scientists, clinicians, and trainees. This commentary highlights promising applications of computational models to understand neurorehabilitation ("Using computational models to understand complex mechanisms in neurorehabilitation" section), improve rehabilitation care in the context of digital twin frameworks ("Using computational models to improve delivery and implementation of rehabilitation care" section), and empower future interdisciplinary workforces to deliver higher-quality clinical care using computational models ("Using computational models in neurorehabilitation requires an interdisciplinary workforce" section). The authors describe near-term gaps and opportunities, all of which encourage interdisciplinary team science. Four major opportunities were identified including (1) deciphering the relationship between engineering figures of merit-a term commonly used by engineers to objectively quantify the performance of a device, system, method, or material relative to existing state of the art-and clinical outcome measures, (2) validating computational models from engineering and patient perspectives, (3) creating and curating datasets that are made publicly accessible, and (4) developing new transdisciplinary frameworks, theories, and models that incorporate the complexities of the nervous and musculoskeletal systems. This commentary summarizes U.S. funding opportunities by two Federal agencies that support computational research in neurorehabilitation. The NSF has funding programs that support high-risk/high-reward research proposals on computational methods in neurorehabilitation informed by theory- and data-driven approaches. The NIH supports the development of new interventions and therapies for a wide range of nervous system injuries and impairments informed by the field of computational modeling. The conference materials can be found at https://dare2023.usc.edu/ .

Osteoarthritis year in review 2023: Biomechanics

Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.

Applying elastic resistance bands for gait training: A simulation-based study to determine how band configuration affects gait biomechanics and muscle activation

BACKGROUND

Wearable robotic exoskeletons and leg braces are desirable for gait rehabilitation because they can apply loads directly to an affected joint. Yet, they are not widely used in clinics because they are costly and complex to set up. Conversely, tethered devices, such as elastic resistance bands, are widely available in clinics, are low-cost, and are quick to set up. However, resistance bands will affect walking differently based on how they are configured to pull on the leg (e.g., pulling forward or backward).

RESEARCH QUESTION

How can a resistance band be configured to alter muscle activation and gait biomechanics based on the segment it is attached to and the angle with which it attaches?

METHODS

We used an open-source musculoskeletal modeling platform to emulate several configurations of an elastic band pulling on the ankle, calf, and thigh at various angles during non-pathological walking. We evaluated gait biomechanics and simulated muscle activation using computed muscle control (CMC) and identified a subset of four configurations with potential applications for gait training. Eight non-pathological participants then walked on a treadmill under these configurations to verify how these configurations altered muscle activation.

RESULTS

We found that muscle activity greatly varied based on the location where the elastic band is attached and the angle with which the elastic band pulls on the leg. Notably, specific angles can be used to pull on the legs to elicit an increase or decrease in muscle activation.

SIGNIFICANCE

This study provides insight into how tethered devices can be configured to provide assistance or resistance during gait training. This information can be applied when developing low-cost gait training solutions for addressing individuals' impairments.

Selective dorsal rhizotomy and its effect on muscle force during walking: A comprehensive study

Selective dorsal rhizotomy (SDR) is commonly used to permanently reduce spasticity in children with cerebral palsy (CP). However, studies have yielded varying results regarding muscle strength and activity after SDR. Some studies indicate weakness or no changes, while a recent study using NMSK simulations demonstrates improvements in muscle forces during walking. These findings suggest that SDR may alleviate spasticity, reducing dynamic muscle constraints and enhancing muscle force without altering muscle activity during walking in children with CP. In this study, we combined NMSK simulations with physical examinations to assess children with CP who underwent SDR, comparing them to well-matched peers who did not undergo the procedure. Each group (SDR and No-SDR) included 81 children, with pre- and post-SDR assessments. Both groups were well-matched in terms of demographics, clinical characteristics, and gait parameters. The results of the physical examination indicate that SDR significantly reduces spasticity without impacting muscle strength. Furthermore, our findings show no significant differences in gait deviation index improvements and walking speed between the two groups. Additionally, there were no statistically significant changes in muscle activity during walking before and after SDR for both groups. NMSK results demonstrate a significant increase in muscle force in the semimembranosus and calf muscles during walking, compared to children with CP who received other clinical treatments. Our findings confirm that although SDR does not significantly impact muscle strength compared to other treatments, it creates a more favorable dynamic environment for suboptimal muscle force production, which is essential for walking.

Per-step and cumulative load at three common running injury locations: The effect of speed, surface gradient, and cadence

Understanding how loading and damage on common running injury locations changes across speeds, surface gradients, and step frequencies may inform training programs and help guide progression/rehabilitation after injuries. However, research investigating tissue loading and damage in running is limited and fragmented across different studies, thereby impairing comparison between conditions and injury locations. This study examined per-step peak load and impulse, cumulative impulse, and cumulative weighted impulse (hereafter referred to as cumulative damage) on three common injury locations (patellofemoral joint, tibia, and Achilles tendon) across different speeds, surface gradients, and cadences. We also explored how cumulative damage in the different tissues changed across conditions relative to each other. Nineteen runners ran at five speeds (2.78, 3.0, 3.33, 4.0, 5.0 m s-1 ), and four gradients (-6, -3, +3, +6°), and three cadences (preferred, ±10 steps min-1 ) each at one speed. Patellofemoral, tibial, and Achilles tendon loading and damage were estimated from kinematic and kinetic data and compared between conditions using a linear mixed model. Increases in running speed increased patellofemoral cumulative damage, with nonsignificant increases for the tibia and Achilles tendon. Increases in cadence reduced damage to all tissues. Uphill running increased tibial and Achilles tendon, but decreased patellofemoral damage, while downhill running showed the reverse pattern. Per-step and cumulative loading, and cumulative loading and cumulative damage indices diverged across conditions. Moreover, changes in running speed, surface gradient, and step frequency lead to disproportional changes in relative cumulative damage on different structures. Methodological and practical implications for researchers and practitioners are discussed.

Static versus dynamic muscle modelling in extinct species: a biomechanical case study of the Australopithecus afarensis pelvis and lower extremity

The force a muscle generates is dependent on muscle structure, in which fibre length, pennation angle and tendon slack length all influence force production. Muscles are not preserved in the fossil record and these parameters must be estimated when constructing a musculoskeletal model. Here, we test the capability of digitally reconstructed muscles of the Australopithecus afarensis model (specimen AL 288-1) to maintain an upright, single-support limb posture. Our aim was to ascertain the influence that different architectural estimation methods have on muscle specialisation and on the subsequent inferences that can be extrapolated about limb function. Parameters were estimated for 36 muscles in the pelvis and lower limb and seven different musculoskeletal models of AL 288-1 were produced. These parameters represented either a 'static' Hill-type muscle model (n = 4 variants) which only incorporated force, or instead a 'dynamic' Hill-type muscle model with an elastic tendon and fibres that could vary force-length-velocity properties (n = 3 variants). Each muscle's fibre length, pennation angle, tendon slack length and maximal isometric force were calculated based upon different input variables. Static (inverse) simulations were computed in which the vertical and mediolateral ground reaction forces (GRF) were incrementally increased until limb collapse (simulation failure). All AL 288-1 variants produced somewhat similar simulated muscle activation patterns, but the maximum vertical GRF that could be exerted on a single limb was not consistent between models. Three of the four static-muscle models were unable to support >1.8 times body weight and produced models that under-performed. The dynamic-muscle models were stronger. Comparative results with a human model imply that similar muscle group activations between species are needed to sustain single-limb support at maximally applied GRFs in terms of the simplified static simulations (e.g., same walking pose) used here. This approach demonstrated the range of outputs that can be generated for a model of an extinct individual. Despite mostly comparable outputs, the models diverged mostly in terms of strength.

On the prediction of tibiofemoral contact forces for healthy individuals and osteoarthritis patients during gait: a comparative study of regression methods

Knee osteoarthritis (OA) is a public health problem affecting millions of people worldwide. The intensity of the tibiofemoral contact forces is related to cartilage degeneration, and so is the importance of quantifying joint loads during daily activities. Although simulation with musculoskeletal models has been used to calculate joint loads, it demands high-cost equipment and a very time-consuming process. This study aimed to evaluate consolidated machine learning algorithms to predict tibiofemoral forces during gait analysis of healthy individuals and knee OA patients. Also, we evaluated three different datasets to train each model, considering different combinations of primary kinematic and kinetic data, and post-processing data. We evaluated 14 patients with severe unilateral knee OA and 14 healthy individuals during 3-5 gait trials. Data were split into 70% and 30% of the samples as training and test data. Test data was independently evaluated considering a mixture of pathological and healthy individuals, and only OA and Control patients. The main results showed that accurate predictions of the tibiofemoral contact forces were achieved using machine learning methods and that the predictions were sensitive to changes in the input data as training. The present study provided insights into the most promising regressions methods to predict knee contact forces representing an important starting point for the broader application of biomechanical analysis in clinical environments.

The gait1415+2 OpenSim musculoskeletal model of transfemoral amputees with a generic bone-anchored prosthesis

This short communication presents the gait1415+2 musculoskeletal model, that has been developed in OpenSim to describe the lower-extremity of a human subject with transfemoral amputation wearing a generic lower-limb bone-anchored prosthesis. The model has fourteen degrees of freedom, governed by fifteen musculotendon units (placed at the contralateral and residual limbs) and two generic actuators (one placed at the knee joint and one at the ankle joint of the prosthetic leg). Even though the model is a simplified abstraction, it is capable of generating a human-like walking gait and, specifically, it is capable of reproducing both the kinematics and the dynamics of a person with transfemoral amputation wearing a bone-anchored prosthesis during normal level-ground walking. The model is released as support material to this short communication with the final goal of providing the scientific community with a tool for performing forward and inverse dynamics simulations, and for developing computationally-demanding control schemes based on artificial intelligence methods for lower-limb prostheses.

Muscle contributions to reduced ankle joint contact force during drop vertical jumps in patients with chronic ankle instability

Chronic ankle instability is a condition linked to progressive early ankle joint degeneration. Patients with chronic ankle instability exhibit altered biomechanics during gait and jump landings and these alterations are believed to contribute to aberrant joint loading and subsequent joint degeneration. Musculoskeletal modeling has the capacity to estimate joint loads from individual muscle forces. However, the influence of chronic ankle instability on joint contact forces remains largely unknown. The objective of this study was to compare tri-axial (i.e., compressive, anterior-posterior, and medial-lateral) ankle joint contact forces between those with and without chronic ankle instability during the ground contact phase of a drop vertical jump. Fifteen individuals with and 15 individuals without chronic ankle instability completed drop vertical jump maneuvers in a research laboratory. We used those data to drive three-dimensional musculoskeletal simulations and estimate muscle forces and tri-axial joint contact force variables (i.e., peak and impulse). Compared to those without chronic ankle instability, the ankles of patients with chronic ankle instability underwent lower compressive ankle joint contact forces as well as lower anterior-posterior and medial-lateral shearing forces during the weight acceptance phase of landing (p <.05). These findings suggest that patients with chronic ankle instability exhibit lower ankle joint loading patterns than uninjured individuals during a drop vertical jump, which may be considered in rehabilitation to potentially reduce the risk of early onset of ankle joint degeneration.

Individuals with rotator cuff tears unsuccessfully treated with exercise therapy have less inferiorly oriented net muscle forces during scapular plane abduction

Exercise therapy for individuals with rotator cuff tears fails in approximately 25.0 % of cases. One reason for failure of exercise therapy may be the inability to strengthen and balance the muscle forces crossing the glenohumeral joint that act to center the humeral head on the glenoid. The objective of the current study was to compare the magnitude and orientation of the net muscle force pre- and post-exercise therapy between subjects successfully and unsuccessfully (e.g. eventually underwent surgery) treated with a 12-week individualized exercise therapy program. Twelve computational musculoskeletal models (n = 6 successful, n = 6 unsuccessful) were developed in OpenSim (v4.0) that incorporated subject specific tear characteristics, muscle peak isometric force, in-vivo kinematics and bony morphology. The models were driven with experimental kinematics and the magnitude and orientation of the net muscle force was determined during scapular plane abduction at pre- and post-exercise therapy timepoints. Subjects unsuccessfully treated had less inferiorly oriented net muscle forces pre- and post-exercise therapy compared to subjects successfully treated (p = 0.039 & 0.045, respectively). No differences were observed in the magnitude of the net muscle force (p > 0.05). The current study developed novel computational musculoskeletal models with subject specific inputs capable of distinguishing between subjects successfully and unsuccessfully treated with exercise therapy. A less inferiorly oriented net muscle force in subjects unsuccessfully treated may increase the risk of superior migration leading to impingement. Adjustments to exercise therapy programs may be warranted to avoid surgery in subjects at risk of unsuccessful treatment.

Evaluation of an Unloading Concept for Knee Osteoarthritis: A Pilot Study in a Small Patient Group

Joint compressive forces have been identified as a risk factor for osteoarthritis disease progression. Therefore, unloader braces are a common treatment with the aim of relieving pain, but their effects are not clearly documented in the literature. A knee brace concept was tested with the aim of reducing joint loads and pain in knee osteoarthritis patients by applying an extension moment exclusively during the stance phase. The ideal effects were evaluated during gait based on musculoskeletal modeling of six patients, and experimental tests with a prototype brace were conducted on one patient. The effects were evaluated using electromyography measurements and musculoskeletal models to evaluate the muscle activation and knee compressive forces, respectively. The ideal brace simulations revealed a varying reduction of the first peak knee force between 3.5% and 33.8% across six patients whereas the second peak was unaffected. The prototype reduced the peak vasti muscle activation with 7.9% and musculoskeletal models showed a reduction of the first peak knee compressive force of up to 26.3%. However, the prototype brace increased the knee joint force impulse of up to 17.1% and no immediate pain reduction was observed. The reduction of the first peak knee compressive force, using a prototype on a single patient, indicates a promising effect from an applied knee extension moment for reducing knee joint loads during normal gait. However, further clinical experiments with this brace method are required to evaluate the long-term effects on both pain and disease progression in knee osteoarthritis patients.

Predicted vs. measured paraspinal muscle activity in adolescent idiopathic scoliosis patients: EMG validation of optimization-based musculoskeletal simulations

Musculoskeletal (MSK) models offer great potential for predicting the muscle forces required to inform more detailed simulations of vertebral endplate loading in adolescent idiopathic scoliosis (AIS). In this work, simulations based on static optimization were compared with in vivo measurements in two AIS patients to determine whether computational approaches alone are sufficient for accurate prediction of paraspinal muscle activity during functional activities. We used biplanar radiographs and marker-based motion capture, ground reaction force, and electromyography (EMG) data from two patients with mild and moderate thoracolumbar AIS (Cobb angles: 21° and 45°, respectively) during standing while holding two weights in front (reference position), walking, running, and object lifting. Using a fully automated approach, 3D spinal shape was extracted from the radiographs. Geometrically personalized OpenSim-based MSK models were created by deforming the spine of pre-scaled full-body models of children/adolescents. Simulations were performed using an experimentally controlled backward approach. Differences between model predictions and EMG measurements of paraspinal muscle activity (both expressed as a percentage of the reference position values) at three different locations around the scoliotic main curve were quantified by root mean square error (RMSE) and cross-correlation (XCorr). Predicted and measured muscle activity correlated best for mild AIS during object lifting (XCorr's ≥ 0.97), with relatively low RMSE values. For moderate AIS as well as the walking and running activities, agreement was lower, with XCorr reaching values of 0.51 and comparably high RMSE values. This study demonstrates that static optimization alone seems not appropriate for predicting muscle activity in AIS patients, particularly in those with more than mild deformations as well as when performing upright activities such as walking and running.

Concentric and eccentric hip musculotendon work depends on backpack loads and walking slopes

Hip muscle weakness is associated with low back and leg injuries. In addition, hiking with heavy loads is linked to high incidence of overuse injuries. Walking with heavy loads on slopes alters hip biomechanics compared to unloaded walking, but individual muscle mechanical work in these challenging conditions is unknown. Using movement simulations, we quantified hip muscle concentric and eccentric work during walking on 0° and ±10° slopes with, and without 40% bodyweight added loads, and with and without a hip belt. For gluteus maximus, psoas, iliacus, gluteus medius, and biceps femoris long head, both concentric and eccentric work were greatest during uphill walking. For rectus femoris and semimembranosus, concentric work was greatest during uphill and eccentric work was greatest during downhill walking. Loaded walking had greater concentric and eccentric work from rectus femoris, biceps femoris long head, and gluteus maximus. Psoas concentric work was greatest while carrying loads regardless of hip belt usage, but eccentric work was only greater than unloaded walking when using a hip belt. Loaded and uphill walking had high concentric work from gluteus maximus, and high eccentric work from gluteus medius and biceps femoris long head. Carrying heavy loads uphill may lead to excessive hip muscle fatigue and heightened injury risk. Effects of the greater eccentric work from hip flexors when wearing a hip belt on lumbar spine forces and pelvic stability should be investigated. Military and other occupational groups who carry heavy backpacks with hip belts should maintain eccentric strength of hip flexors and hamstrings.