Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?

Evaluation of 3D Footprint Morphology of Knee-Related Muscle Attachments Based on CT Data Reconstruction: A Feasibility Study

A three-dimensional (3D) understanding of muscle attachment footprints became increasingly relevant for musculoskeletal modeling. The established method to project attachments as points ignores patient-specific individuality. Research focuses on investigating certain muscle groups rather than comprehensively studying all muscles spanning a joint. Therefore, we present a reliable method to study several muscle attachments in order to reconstruct the attachment sites in 3D based on CT imaging for future applications in musculoskeletal modeling. For the present feasibility study, 23 knee-related muscle attachments were CT-scanned postmortem from four nonadipose male specimens. For this, the specific muscle attachments were dissected and marked with a barium sulfate containing paint (60 g BaSO4 in 30 mL water and 10 mL acrylic paint). Subsequently, bone geometries and muscle attachments were reconstructed and evaluated from CT datasets. Bone morphology and footprint variations were studied. Exemplarily, variations were high for pes anserinus insertions (mean 56%) and the origins of M. biceps femoris (mean 54%). In contrast, the origins of the vastus muscles as well as the insertion of the Achilles tendon showed low variation (mean 9% and 13%, respectively). Most attachment sites showed variation exceeding the individuality of bone morphology. In summary, the present data were consistent with the few published studies of specific muscle footprints. Our data shed light on the high variability of muscle attachments, which need to be addressed when studying muscle forces and movements through musculoskeletal modeling. This is the first step to achieving a more profound understanding of muscle morphology to be utilized in numerical simulations.

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.

Accuracy of conventional motion capture in measuring hip joint center location and hip rotations during gait, squat, and step-up activities

Accurate measurements of hip joint kinematics are essential for improving our understanding of the effects of injury, disease, and surgical intervention on long-term hip joint health. This study assessed the accuracy of conventional motion capture (MoCap) for measuring hip joint center (HJC) location and hip joint angles during gait, squat, and step-up activities while using dynamic biplane radiography (DBR) as the reference standard. Twenty-four young adults performed six trials of treadmill walking, six body-weight squats, and six step-ups within a biplane radiography system. Synchronized biplane radiographs were collected at 50 images per second and MoCap was collected simultaneously at 100 images per second. Bone motion during each activity was determined by matching digitally reconstructed radiographs, created from subject-specific CT-based bone models, to the biplane radiographs using a validated registration process. Errors in estimating HJC location and hip angles using MoCap were quantified by the root mean squared error (RMSE) across all frames of available data. The MoCap error in estimating HJC location was larger during step-up (up to 89.3 mm) than during gait (up to 16.6 mm) or squat (up to 31.4 mm) in all three anatomic directions (all p < 0.001). RMSE in hip joint flexion (7.2°) and abduction (4.3°) during gait was less than during squat (23.8° and 8.9°) and step-up (20.1° and 10.6°) (all p < 0.01). Clinical analysis and computational models that rely on skin-mounted markers to estimate hip kinematics should be interpreted with caution, especially during activities that involve deeper hip flexion.

A three-dimensional musculoskeletal model of the pelvis and lower limb of Australopithecus afarensis

OBJECTIVES

Musculoskeletal modeling is a powerful approach for studying the biomechanics and energetics of locomotion. Australopithecus (A.) afarensis is among the best represented fossil hominins and provides critical information about the evolution of musculoskeletal design and locomotion in the hominin lineage. Here, we develop and evaluate a three-dimensional (3-D) musculoskeletal model of the pelvis and lower limb of A. afarensis for predicting muscle-tendon moment arms and moment-generating capacities across lower limb joint positions encompassing a range of locomotor behaviors.

MATERIALS AND METHODS

A 3-D musculoskeletal model of an adult A. afarensis pelvis and lower limb was developed based primarily on the A.L. 288-1 partial skeleton. The model includes geometric representations of bones, joints and 35 muscle-tendon units represented using 43 Hill-type muscle models. Two muscle parameter datasets were created from human and chimpanzee sources. 3-D muscle-tendon moment arms and isometric joint moments were predicted over a wide range of joint positions.

RESULTS

Predicted muscle-tendon moment arms generally agreed with skeletal metrics, and corresponded with human and chimpanzee models. Human and chimpanzee-based muscle parameterizations were similar, with some differences in maximum isometric force-producing capabilities. The model is amenable to size scaling from A.L. 288-1 to the larger KSD-VP-1/1, which subsumes a wide range of size variation in A. afarensis.

DISCUSSION

This model represents an important tool for studying the integrated function of the neuromusculoskeletal systems in A. afarensis. It is similar to current human and chimpanzee models in musculoskeletal detail, and will permit direct, comparative 3-D simulation studies.

Sensitivity Analysis of Upper Limb Musculoskeletal Models During Isometric and Isokinetic Tasks

Sensitivity coefficients are used to understand how errors in subject-specific musculoskeletal model parameters influence model predictions. Previous sensitivity studies in the lower limb calculated sensitivity using perturbations that do not fully represent the diversity of the population. Hence, the present study performs sensitivity analysis in the upper limb using a large synthetic dataset to capture greater physiological diversity. The large dataset (n = 401 synthetic subjects) was created by adjusting maximum isometric force, optimal fiber length, pennation angle, and bone mass to induce atrophy, hypertrophy, osteoporosis, and osteopetrosis in two upper limb musculoskeletal models. Simulations of three isometric and two isokinetic upper limb tasks were performed using each synthetic subject to predict muscle activations. Sensitivity coefficients were calculated using three different methods (two point, linear regression, and sensitivity functions) to understand how changes in Hill-type parameters influenced predicted muscle activations. The sensitivity coefficient methods were then compared by evaluating how well the coefficients accounted for measurement uncertainty. This was done by using the sensitivity coefficients to predict the range of muscle activations given known errors in measuring musculoskeletal parameters from medical imaging. Sensitivity functions were found to best account for measurement uncertainty. Simulated muscle activations were most sensitive to optimal fiber length and maximum isometric force during upper limb tasks. Importantly, the level of sensitivity was muscle and task dependent. These findings provide a foundation for how large synthetic datasets can be applied to capture physiologically diverse populations and understand how model parameters influence predictions.

How mechanics of individual muscle-tendon units define knee and ankle joint function in health and cerebral palsy-a narrative review

This study reviews the relationship between muscle-tendon biomechanics and joint function, with a particular focus on how cerebral palsy (CP) affects this relationship. In healthy individuals, muscle size is a critical determinant of strength, with muscle volume, cross-sectional area, and moment arm correlating with knee and ankle joint torque for different isometric/isokinetic contractions. However, in CP, impaired muscle growth contributes to joint pathophysiology even though only a limited number of studies have investigated the impact of deficits in muscle size on pathological joint function. As muscles are the primary factors determining joint torque, in this review two main approaches used for muscle force quantification are discussed. The direct quantification of individual muscle forces from their relevant tendons through intraoperative approaches holds a high potential for characterizing healthy and diseased muscles but poses challenges due to the invasive nature of the technique. On the other hand, musculoskeletal models, using an inverse dynamic approach, can predict muscle forces, but rely on several assumptions and have inherent limitations. Neither technique has become established in routine clinical practice. Nevertheless, identifying the relative contribution of each muscle to the overall joint moment would be key for diagnosis and formulating efficient treatment strategies for patients with CP. This review emphasizes the necessity of implementing the intraoperative approach into general surgical practice, particularly for joint correction operations in diverse patient groups. Obtaining in vivo data directly would enhance musculoskeletal models, providing more accurate force estimations. This integrated approach can improve the clinicians' decision-making process and advance treatment strategies by predicting changes at the muscle and joint levels before interventions, thus, holding the potential to significantly enhance clinical outcomes.

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

The computational simulation of human voluntary muscle contraction is possible with EMG-driven Hill-type models of whole muscles. Despite impactful applications in numerous fields, the neuromechanical information and the physiological accuracy such models provide remain limited because of multiscale simplifications that limit comprehensive description of muscle internal dynamics during contraction. We addressed this limitation by developing a novel motoneuron-driven neuromuscular model, that describes the force-generating dynamics of a population of individual motor units, each of which was described with a Hill-type actuator and controlled by a dedicated experimentally derived motoneuronal control. In forward simulation of human voluntary muscle contraction, the model transforms a vector of motoneuron spike trains decoded from high-density EMG signals into a vector of motor unit forces that sum into the predicted whole muscle force. The motoneuronal control provides comprehensive and separate descriptions of the dynamics of motor unit recruitment and discharge and decodes the subject's intention. The neuromuscular model is subject-specific, muscle-specific, includes an advanced and physiological description of motor unit activation dynamics, and is validated against an experimental muscle force. Accurate force predictions were obtained when the vector of experimental neural controls was representative of the discharge activity of the complete motor unit pool. This was achieved with large and dense grids of EMG electrodes during medium-force contractions or with computational methods that physiologically estimate the discharge activity of the motor units that were not identified experimentally. This neuromuscular model advances the state-of-the-art of neuromuscular modelling, bringing together the fields of motor control and musculoskeletal modelling, and finding applications in neuromuscular control and human-machine interfacing research.

Comparative validation of two patient-specific modelling pipelines for predicting knee joint forces during level walking

Over the past few years, the use of computer models and simulations tailored to the patient's physiology to assist clinical decision-making has increased enormously.While several pipelines to develop personalized models exist, their adoption on a large scale is still limited due to the required niche computational skillset and the lengthy operations required. Novel toolboxes, such as STAPLE, promise to streamline and expedite the development of image-based skeletal lower limb models. STAPLE-generated models can be rapidly generated, with minimal user input, and present similar joint kinematics and kinetics compared to models developed employing the established INSIGNEO pipeline. Yet, it is unclear how much the observed discrepancies scale up and affect joint contact force predictions. In this study, we compared image-based musculoskeletal models developed (i) with the INSIGNEO pipeline and (ii) with a semi-automated pipeline that combines STAPLE and nmsBuilder, and assessed their accuracy against experimental implant data.Our results showed that both pipelines predicted similar total knee joint contact forces between one another in terms of profiles and average values, characterized by a moderately high level of agreement with the experimental data. Nonetheless, the Student t-test revealed statistically significant differences between both pipelines. Of note, the STAPLE-based pipeline required considerably less time than the INSIGNEO pipeline to generate a musculoskeletal model (i.e., 60 vs 160 min). This is likely to open up opportunities for the use of personalized musculoskeletal models in clinical practice, where time is of the essence.

The History and Future of Neuromusculoskeletal Biomechanics

The Executive Council of the International Society of Biomechanics has initiated and overseen the commemorations of the Society's 50th Anniversary in 2023. This included multiple series of lectures at the ninth World Congress of Biomechanics in 2022 and XXIXth Congress of the International Society of Biomechanics in 2023, all linked to special issues of International Society of Biomechanics' affiliated journals. This special issue of the Journal of Applied Biomechanics is dedicated to the biomechanics of the neuromusculoskeletal system. The reader is encouraged to explore this special issue which comprises 6 papers exploring the current state-of the-art, and future directions and roles for neuromusculoskeletal biomechanics. This editorial presents a very brief history of the science of the neuromusculoskeletal system's 4 main components: the central nervous system, musculotendon units, the musculoskeletal system, and joints, and how they biomechanically integrate to enable an understanding of the generation and control of human movement. This also entails a quick exploration of contemporary neuromusculoskeletal biomechanics and its future with new fields of application.

Comparison of biomechanical analysis results using different musculoskeletal models for children with cerebral palsy

Introduction: Musculoskeletal model-based simulations have gained popularity as a tool for analyzing human movement biomechanics. However, when examining the same gait, different models with varying anatomical data and assumptions may produce inconsistent biomechanical results. This inconsistency is particularly relevant for children with cerebral palsy, who often exhibit multiple pathological gait patterns that can impact model outputs. Methods: The aim of this study was to investigate the effect of selecting musculoskeletal models on the biomechanical analysis results in children with cerebral palsy. Gait data were collected from multiple participants at slow, medium, and fast velocities. Joint kinematics, joint dynamics, and muscle activation were calculated using six popular musculoskeletal models within a biomechanical simulation environment. Results: The degree of inconsistency, measured as the root-mean-square deviation, in kinematic and kinetic results produced by the different models ranged from 4% to 40% joint motion range and 0%-28% joint moment range, respectively. The correlation between the results of the different models (both kinematic and kinetic) was good (R> 0.85, P < 0.01), with a stronger correlation observed in the kinetic results. Four of the six models showed a positive correlation between the simulated muscle activation of rectus femoris and the surface EMG, while all models exhibited a positive correlation between the activation of medial gastrocnemius and the surface EMG (P < 0.01). Discussion: These results provide insights into the consistency of model results, factors influencing consistency, characteristics of each model's outputs, mechanisms underlying these characteristics, and feasible applications for each model. By elucidating the impact of model selection on biomechanical analysis outcomes, this study advances the field's understanding of musculoskeletal modeling and its implications for clinical gait analysis model decision-making in children with cerebral palsy.

Patellofemoral joint load and knee abduction/adduction moment are sensitive to variations in femoral version and individual muscle forces

Torsional profiles of the lower limbs, such as femoral anteversion, can dictate gait and mobility, joint biomechanics and pain, and functional impairment. It currently remains unclear how the interactions between femoral anteversion, kinematics, and muscle activity patterns contribute to joint biomechanics and thus conditions such as knee pain. This study presents a computational modeling approach to investigating the interactions between femoral anteversion, muscle forces, and knee joint loads. We employed an optimal control approach to produce actuator and muscle-driven simulations of the stance phase of gait for femoral anteversion angles ranging from -8° (retroversion) to 52° (anteversion) with a typically developing baseline of 12° of anteversion and implemented a Monte Carlo analysis for variations in lower limb muscle forces. While total patellofemoral joint load decreased with increasing femoral anteversion, patellofemoral joint load alignment worsened, and knee abduction/adduction magnitude increased with both positive and negative changes in femoral anteversion (p < 0.001). The rectus femoris muscle was found to greatly influence patellofemoral joint loads across all femoral anteversion alignments (R > 0.8, p < 0.001), and the medial gastrocnemius was found to greatly influence knee abduction/adduction moments for the extreme version cases (R > 0.74, p < 0.001). Along with the vastus lateralis, which decreased with increasing femoral anteversion (R = 0.89, p < 0.001), these muscles are prime candidates for future experimental and clinical efforts to address joint pain in individuals with extreme femoral version. These findings, along with future modeling efforts, could help clinicians better design treatment strategies for knee joint pain in populations with extreme femoral anteversion or retroversion.

Ankle joint contact force profiles differ between those with and without chronic ankle instability during walking

BACKGROUND

Individuals with chronic ankle instability (CAI) exhibit aberrant gait biomechanics relative to uninjured controls. Altered gait biomechanics likely contribute aberrant joint loading and subsequent early onset ankle joint degeneration. Joint (i.e. cartilage) loading cannot be directly measured without invasive procedures but can be estimated via joint contact forces (JCF) generated from musculoskeletal modeling. However, no investigation has quantified JCF in those with CAI during walking despite the link between ligamentous injury and ankle post-traumatic ankle osteoarthritis.

RESEARCH QUESTION

Do patients with CAI exhibit altered ankle compressive and shear JCF profiles during the stance phase of walking compared to those without CAI?

METHODS

Ten individuals with CAI and 10 individuals without a history of ankle sprain completed a gait assessment at their self-selected speed on an instrumented treadmill. Musculoskeletal modeling was applied to estimate ankle JCF variables within a generic model. Variables included the peak, impulse, and loading rates for compressive, anteroposterior shear, and mediolateral shear JCF.

RESULTS

Those with CAI had significantly different JCF forces, relative to uninjured controls, in all directions. More specifically, lower compressive peak and impulse values were noted while higher anteroposterior shearing forces (1 st peak, impulse, loading late) were observed in those with CAI. Those with CAI also demonstrated higher mediolateral shearing forces (1 st peak and impulse).

SIGNIFICANCE

Our finding suggests that those with CAI exhibit different ankle joint loading patterns than uninjured controls. Directionality of the identified differences depends on the axis of movement.

Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The "virtual stiffness" method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations.

Deformable image registration based on single or multi-atlas methods for automatic muscle segmentation and the generation of augmented imaging datasets

Muscle segmentation is a process relied upon to gather medical image-based muscle characterisation, useful in directly assessing muscle volume and geometry, that can be used as inputs to musculoskeletal modelling pipelines. Manual or semi-automatic techniques are typically employed to segment the muscles and quantify their properties, but they require significant manual labour and incur operator repeatability issues. In this study an automatic process is presented, aiming to segment all lower limb muscles from Magnetic Resonance (MR) imaging data simultaneously using three-dimensional (3D) deformable image registration (single inputs or multi-atlas). Twenty-three of the major lower limb skeletal muscles were segmented from five subjects, with an average Dice similarity coefficient of 0.72, and average absolute relative volume error (RVE) of 12.7% (average relative volume error of -2.2%) considering the optimal subject combinations. The multi-atlas approach showed slightly better accuracy (average DSC: 0.73; average RVE: 1.67%). Segmented MR imaging datasets of the lower limb are not widely available in the literature, limiting the potential of new, probabilistic methods such as deep learning to be used in the context of muscle segmentation. In this work, Non-linear deformable image registration is used to generate 69 manually checked, segmented, 3D, artificial datasets, allowing access for future studies to use these new methods, with a large amount of reliable reference data.

An investigation into the hammer toe effects on the lower extremity mechanics and plantar fascia tension: A case for a vicious cycle and progressive damage

Hammer toes are one of the common deformities of the forefoot that can lead to compensatory changes during walking in individuals with this condition. Predicting the adverse effects of tissue damage on the performance of other limbs is very important in the prevention of progressive damage. Finite element (FE) and musculoskeletal modeling can be helpful by allowing such effects to be studied in a way where the internal stresses in the tissue could be investigated. Hence, this study aims to investigate the effects of the hammer toe deformity on the lower extremity, especially on the plantar fascia functions. To compare the joint reactions of the hammer toe foot (HTF) and healthy foot (HF), two musculoskeletal models (MSM) of the feet of a healthy individual and that of a participant with hammer toe foot were developed based on gait analysis. A previously validated 3D finite element model which was constructed using Magnetic Resonance Imaging (MRI) of the diabetic participant with the hammer toe deformity was processed at five different events during the stance phase of gait. It was found that the hammer toe deformity makes dorsiflexion of the toes and the windlass mechanism less effective during walking. Specifically, the FE analysis results showed that plantar fascia (PF) in HTF compared to HF played a less dominant role in load bearing with both medial and lateral parts of PF loaded. Also, the results indicated that the stored elastic energy in PF was less in HTF than the HF, which can indicate a higher metabolic cost during walking. Internal stress distribution shows that the majority of ground reaction forces are transmitted through the lateral metatarsals in hammer toe foot, and the probability of fifth metatarsal fracture and also progressive deformity was subsequently increased. The MSM results showed that the joint reaction forces and moments in the hammer toe foot have deviated from normal, where the metatarsophalangeal joint reactions in the hammer toe were less than the values in the healthy foot. This can indicate a vicious cycle of foot deformity, leading to changes in body weight force transmission line, and deviation of joint reactions and plantar fascia function from normal. These in turn lead to increased internal stress concentration, which in turn lead to further foot deformities. This vicious cycle cause progressive damage and can lead to an increase in the risk of ulceration in the diabetic foot.

Personalisation of Plantarflexor Musculotendon Model Parameters in Children with Cerebral Palsy

Neuromusculoskeletal models can be used to evaluate aberrant muscle function in cerebral palsy (CP), for example by estimating muscle and joint contact forces during gait. However, to be accurate, models should include representative musculotendon parameters. We aimed to estimate personalised parameters that capture the mechanical behaviour of the plantarflexors in children with CP and typically developing (TD) children. Ankle angle (using motion capture), torque (using a load-cell), and medial gastrocnemius fascicle lengths (using ultrasound) were measured during slow passive ankle dorsiflexion rotation for thirteen children with spastic CP and thirteen TD children. Per subject, the measured rotation was input to a scaled OpenSim model to simulate the torque and fascicle length output. Musculotendon model parameters were personalised by the best match between simulated and experimental torque–angle and fascicle length-angle curves according to a least-squares fit. Personalised tendon slack lengths were significantly longer and optimal fibre lengths significantly shorter in CP than model defaults and than in TD. Personalised tendon compliance was substantially higher in both groups compared to the model default. The presented method to personalise musculotendon parameters will likely yield more accurate simulations of subject-specific muscle mechanics, to help us understand the effects of altered musculotendon properties in CP.

The effects of anatomical errors on shoulder kinematics computed using multi-body models

Joint motion calculated using multi-body models and inverse kinematics presents many advantages over direct marker-based calculations. However, the sensitivity of the computed kinematics is known to be partly caused by the model and could also be influenced by the participants' anthropometry and sex. This study aimed to compare kinematics computed from an anatomical shoulder model based on medical images against a scaled-generic model and quantify the effects of anatomical errors and participants' anthropometry on the calculated joint angles. Twelve participants have had planar shoulder movements experimentally captured in a motion lab, and their shoulder anatomy imaged using an MRI scanner. A shoulder multi-body dynamics model was developed for each participant, using both an image-based approach and a scaled-generic approach. Inverse kinematics have been performed using the two different modelling procedures and the three different experimental motions. Results have been compared using Bland-Altman analysis of agreement and further analysed using multi-linear regressions. Kinematics computed via an anatomical and a scaled-generic shoulder models differed in average from 3.2 to 5.4 degrees depending on the task. The MRI-based model presented smaller limits of agreement to direct kinematics than the scaled-generic model. Finally, the regression model predictors, including anatomical errors, sex, and BMI of the participant, explained from 41 to 80% of the kinematic variability between model types with respect to the task. This study highlighted the consequences of modelling precision, quantified the effects of anatomical errors on the shoulder kinematics, and showed that participants' anthropometry and sex could indirectly affect kinematic outcomes.

Variability and the form-function framework in evolutionary biomechanics and human locomotion

The form-function conceptual framework, which assumes a strong relationship between the structure of a particular trait and its function, has been crucial for understanding morphological variation and locomotion among extant and fossil species across many disciplines. In biological anthropology, it is the lens through which many important questions and hypotheses have been tackled with respect to relationships between morphology and locomotor kinematics, energetics and performance. However, it is becoming increasingly evident that the morphologies of fossil hominins, apes and humans can confer considerable locomotor diversity and flexibility, and can do so with a range of kinematics depending on soft tissue plasticity and environmental and cultural factors. This complexity is not built into traditional biomechanical or mathematical models of relationships between structure and kinematics or energetics, limiting our interpretation of what bone structure is telling us about behaviour in the past. The nine papers presented in this Special Collection together address some of the challenges that variation in the relationship between form and function pose in evolutionary biomechanics, to better characterise the complexity linking structure and function and to provide tools through which we may begin to incorporate some of this complexity into our functional interpretations.

An investigation of the ankle contact forces in a foot with hammer toe deformity. A comparison of patient-specific approaches using finite element modeling and musculoskeletal simulation

The internal forces and stresses in the tissue are important as they are linked to the risk of mechanical trauma and injuries. Despite their value, the internal stresses and forces cannot be directly measured in-vivo. A previously validated 3D finite element model (FEM) was constructed using Magnetic Resonance Imaging (MRI) of a person with diabetes and hammer toe deformity. The foot model simulated at five different instances during the stance phase of gait. The internal stress distribution on the talus that was obtained using the FEM simulation, was used to calculate the joint reaction force at the ankle joint. In addition, the musculoskeletal model (MSM) of the participant with hammer toe foot was developed based on the gait analysis and was used to determine the muscle forces and joint reactions. The result showed that the vertical reaction forces obtained from the FEM and MSM follow a similar trend through the stance phase of gait cycle and are significantly correlated ( R=0.99). The joint reaction forces obtained through the two methods do not differ for the first 25% of the gait cycle, while the maximum difference was ∼0.7 Body weight that was observed at 50% of the stance phase. Clinical Relevance: Finite element modeling and musculoskeletal simulation can shed light on the internal forces at the ankle in pathological conditions such as hammer toe. The similarities and differences observed in the joint reaction forces calculated from the two methods can have implications in assessing the effect of clinical interventions.

[Evaluation of a Bone Coordinate System Constructed Using MR Image Composing]

PURPOSE

To evaluate the accuracy of a bone coordinate system constructed using MR image composing.

METHOD

A femoral coordinate system constructed using image composing of MR images of a whole bovine femur was evaluated using CT images. The MR images were acquired by moving the table and were processed with 3D distortion correction and composing. To evaluate the reproducibility of the measurements, the same operator repeated the construction of the femoral coordinate system. In addition, distortions in the MR images were evaluated in comparison with those in the CT images.

RESULT

The center position of the femoral coordinate system constructed using the MR image composing was 1.6±0.9 mm on the X-axis, 1.5±0.8 mm on the Y-axis, and 0.2±0.3 mm on the Z-axis, and the rotation of each axis was 1° or less. The distortion of the composed MR image was about 0.3%.

CONCLUSION

The femoral coordinate system constructed using MR image composing had the same accuracy as a system constructed with CT images. The effect of MR image composing on the construction of the femoral coordinate system was small.

Uncertainty in Muscle–Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models

Understanding the sources of error is critical before models of the musculoskeletal system can be usefully translated. Using in vivo measured tibiofemoral forces, the impact of uncertainty in muscle–tendon parameters on the accuracy of knee contact force estimates of a generic musculoskeletal model was investigated following a probabilistic approach. Population variability was introduced to the routine musculoskeletal modeling framework by perturbing input parameters of the lower limb muscles around their baseline values. Using ground reaction force and skin marker trajectory data collected from six subjects performing body-weight squat, the knee contact force was calculated for the perturbed models. The combined impact of input uncertainties resulted in a considerable variation in the knee contact force estimates (up to 2.1 BW change in the predicted force), especially at larger knee flexion angles, hence explaining up to 70% of the simulation error. Although individual muscle groups exhibited different contributions to the overall error, variation in the maximum isometric force and pathway of the muscles showed the highest impacts on the model outcomes. Importantly, this study highlights parameters that should be personalized in order to achieve the best possible predictions when using generic musculoskeletal models for activities involving deep knee flexion.

Conclusion or Illusion: Quantifying Uncertainty in Inverse Analyses From Marker-Based Motion Capture due to Errors in Marker Registration and Model Scaling

Estimating kinematics from optical motion capture with skin-mounted markers, referred to as an inverse kinematic (IK) calculation, is the most common experimental technique in human motion analysis. Kinematics are often used to diagnose movement disorders and plan treatment strategies. In many such applications, small differences in joint angles can be clinically significant. Kinematics are also used to estimate joint powers, muscle forces, and other quantities of interest that cannot typically be measured directly. Thus, the accuracy and reproducibility of IK calculations are critical. In this work, we isolate and quantify the uncertainty in joint angles, moments, and powers due to two sources of error during IK analyses: errors in the placement of markers on the model (marker registration) and errors in the dimensions of the model’s body segments (model scaling). We demonstrate that IK solutions are best presented as a distribution of equally probable trajectories when these sources of modeling uncertainty are considered. Notably, a substantial amount of uncertainty exists in the computed kinematics and kinetics even if low marker tracking errors are achieved. For example, considering only 2 cm of marker registration uncertainty, peak ankle plantarflexion angle varied by 15.9°, peak ankle plantarflexion moment varied by 26.6 N⋅m, and peak ankle power at push off varied by 75.9 W during healthy gait. This uncertainty can directly impact the classification of patient movements and the evaluation of training or device effectiveness, such as calculations of push-off power. We provide scripts in OpenSim so that others can reproduce our results and quantify the effect of modeling uncertainty in their own studies.

Maximal lateral ligament strain and loading during functional activities: Model-based insights for ankle sprain prevention and rehabilitation

BACKGROUND

Although it is generally accepted that sports activities present a high risk of lateral ligament injury, the extent to which ligaments are loaded during functional activities is less explored. This is relevant when considering ankle sprain prevention and staged rehabilitation following ligament sprain or reinforcing surgery. Therefore, anterior talofibular ligament, calcaneofibular ligament and posterior talofibular ligament strain and loading were evaluated, based on a newly developed loading index, during movements executed during daily life and rehabilitation.

METHODS

Three-dimensional motion analysis data was acquired in 10 healthy volunteers during eleven different movements and processed using musculoskeletal modelling. Maximal lateral ligament strain and ligament loading, based on an new index accounting for the ankle and subtalar moment magnitude, ligament strain magnitude and duration, were calculated and statistically compared to ligament strain and loading during walking and a reference clinical (talar tilt) test.

FINDINGS

Anterior talofibular, calcaneofibular and posterior talofibular lateral ligament loading were highest during vertical drop jumps, medio-lateral single leg hops and running. Additionally, anterior talofibular loading was high during stair descending, calcaneofibular loading during single leg stance without visual feedback and posterior talofibular loading during anterior single leg hops. During the clinical test, anterior talofibular and calcaneofibular ligament strain were substantially lower than the maximal strain during different movements.

INTERPRETATION

Our results allow classification of exercises according to the ligament loading index and maximal strain, thereby providing objective data to progressively stage ligament loading during rehabilitation.

Using Bayesian inference to estimate plausible muscle forces in musculoskeletal models

Background

Musculoskeletal modeling is currently a preferred method for estimating the muscle forces that underlie observed movements. However, these estimates are sensitive to a variety of assumptions and uncertainties, which creates difficulty when trying to interpret the muscle forces from musculoskeletal simulations. Here, we describe an approach that uses Bayesian inference to identify plausible ranges of muscle forces for a simple motion while representing uncertainty in the measurement of the motion and the objective function used to solve the muscle redundancy problem.

Methods

We generated a reference elbow flexion–extension motion and computed a set of reference forces that would produce the motion while minimizing muscle excitations cubed via OpenSim Moco. We then used a Markov Chain Monte Carlo (MCMC) algorithm to sample from a posterior probability distribution of muscle excitations that would result in the reference elbow motion. We constructed a prior over the excitation parameters which down-weighted regions of the parameter space with greater muscle excitations. We used muscle excitations to find the corresponding kinematics using OpenSim, where the error in position and velocity trajectories (likelihood function) was combined with the sum of the cubed muscle excitations integrated over time (prior function) to compute the posterior probability density.

Results

We evaluated the muscle forces that resulted from the set of excitations that were visited in the MCMC chain (seven parallel chains, 500,000 iterations per chain). The estimated muscle forces compared favorably with the reference forces generated with OpenSim Moco, while the elbow angle and velocity from MCMC matched closely with the reference (average RMSE for elbow angle = 2°; and angular velocity = 32°/s). However, our rank plot analyses and potential scale reduction statistics, which we used to evaluate convergence of the algorithm, indicated that the chains did not fully mix.

Conclusions

While the results from this process are a promising step towards characterizing uncertainty in muscle force estimation, the computational time required to search the solution space with, and the lack of MCMC convergence indicates that further developments in MCMC algorithms are necessary for this process to become feasible for larger-scale models.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01008-4.

A semiautomated method to quantitatively assess osteolytic lesion volume and bone mineral density within acetabular regions of interest from CT

The objectives of this study were to (1) develop a semiautomated method to obtain lesion volume and bone mineral density (BMD) in terms of Hounsfield units from pelvic computed tomography (CT) scans in three regions of interest, and (2) assess accuracy and reliability of the method based on cadaveric CT scans. Image artefacts due to metal implants reduce CT clarity and are more severe with more than one implant in situ. Therefore, accuracy and reliability tests were performed with varying numbers of total hip arthroplasties implanted. To test the accuracy of lesion size measurements, microcomputed tomography was used as a reference. Mean absolute error ranged from 36 to 284 mm³ after five measurements. Intra- and inter-operator reliability of the entire method was measured for a selection of parameters. All coefficient of variation values were good to excellent for CT scans of the native pelvic anatomy and a CT scans of the same pelvis with one and two implants in situ. Accuracy of quantifying lesion volume decreased with decreasing CT image clarity by 0.6%-3.6% mean absolute relative error. Reliability of lesion volume measurement decreased with decreasing CT clarity. This was also the case for reliability of BMD measurements in the region most disrupted by metal artefact. The presented method proposes an approach for quantifying bone loss which has been proven to be accurate, reliable, and clinically applicable.

Is subject-specific musculoskeletal modelling worth the extra effort or is generic modelling worth the shortcut?

The majority of musculoskeletal modelling studies investigating healthy populations use generic models linearly scaled to roughly match an individual’s anthropometry. Generic models disregard the considerable variation in musculoskeletal geometry and tissue properties between individuals. This study investigated the physiological implications of personalizing musculoskeletal model geometry (body segment mass, inertia, joint center, and maximum isometric muscle force). Nine healthy athletes performed ten repetitions of 15 meter sprints at 75–95% of their maximum sprinting speed and ten repetitions of unanticipated sidestep cut trials with a 4.5–5.5 m/s approach running speed. Structural magnetic resonance imaging was collected on the lower extremities, from which subject-specific musculoskeletal models were developed. A one-dimensional statistical parametric mapping paired t-test was used to compare generic and subject-specific musculoskeletal models for: lower-limb kinematics, kinetics, torque matching, as well as hamstrings, adductors, and quadriceps muscle activations and fiber dynamics. Percentage change of geometric parameters between generic and subject-specific models were determined. Compared to generic models, subject-specific models showed significantly lower ankle dorsi/plantar flexion angle during sprinting and several significantly different net joint moments during sprint and cut tasks. Additionally, subject-specific models demonstrated better torque matching, more physiologically plausible fiber lengths, higher fiber velocities, lower muscle forces, and lower simulated activations in a subset of investigated muscles and motor tasks. Furthermore, subject-specific models identified between-limb differences that were not identified with generic models. Use of subject-specific modeling, even in healthy populations, may result in more physiologically plausible muscle fiber mechanics. Implementing subject-specific models may be especially beneficial when investigating populations with substantial geometric between-limb differences, or unilateral musculoskeletal pathologies, as these are not captured by a generic model.

InverseMuscleNET: Alternative Machine Learning Solution to Static Optimization and Inverse Muscle Modeling

InverseMuscleNET, a machine learning model, is proposed as an alternative to static optimization for resolving the redundancy issue in inverse muscle models. A recurrent neural network (RNN) was optimally configured, trained, and tested to estimate the pattern of muscle activation signals. Five biomechanical variables (joint angle, joint velocity, joint acceleration, joint torque, and activation torque) were used as inputs to the RNN. A set of surface electromyography (EMG) signals, experimentally measured around the shoulder joint for flexion/extension, were used to train and validate the RNN model. The obtained machine learning model yields a normalized regression in the range of 88-91% between experimental data and estimated muscle activation. A sequential backward selection algorithm was used as a sensitivity analysis to discover the less dominant inputs. The order of most essential signals to least dominant ones was as follows: joint angle, activation torque, joint torque, joint velocity, and joint acceleration. The RNN model required 0.06 s of the previous biomechanical input signals and 0.01 s of the predicted feedback EMG signals, demonstrating the dynamic temporal relationships of the muscle activation profiles. The proposed approach permits a fast and direct estimation ability instead of iterative solutions for the inverse muscle model. It raises the possibility of integrating such a model in a real-time device for functional rehabilitation and sports evaluation devices with real-time estimation and tracking. This method provides clinicians with a means of estimating EMG activity without an invasive electrode setup.

Musculoskeletal Modeling and Inverse Dynamic Analysis of Precision Grip in the Japanese Macaque

Toward clarifying the biomechanics and neural mechanisms underlying coordinated control of the complex hand musculoskeletal system, we constructed an anatomically based musculoskeletal model of the Japanese macaque (Macaca fuscata) hand, and then estimated the muscle force of all the hand muscles during a precision grip task using inverse dynamic calculation. The musculoskeletal model was constructed from a computed tomography scan of one adult male macaque cadaver. The hand skeleton was modeled as a chain of rigid links connected by revolute joints. The path of each muscle was defined as a series of points connected by line segments. Using this anatomical model and a model-based matching technique, we constructed 3D hand kinematics during the precision grip task from five simultaneous video recordings. Specifically, we collected electromyographic and kinematic data from one adult male Japanese macaque during the precision grip task and two sequences of the precision grip task were analyzed based on inverse dynamics. Our estimated muscular force patterns were generally in agreement with simultaneously measured electromyographic data. Direct measurement of muscle activations for all the muscles involved in the precision grip task is not feasible, but the present inverse dynamic approach allows estimation for all the hand muscles. Although some methodological limitations certainly exist, the constructed model analysis framework has potential in clarifying the biomechanics and neural control of manual dexterity in macaques and humans.

Acute Vibration Feedback During Gait Reduces Mechanical Ankle Joint Loading in Chronic Ankle Instability Patients

BACKGROUND

Individuals with chronic ankle instability (CAI) exhibit altered vertical ground reaction forces (vGRF), a laterally shifted center of pressure, and an inverted foot position during walking. These neuromechanical alterations are linked with altered ankle joint loading in this population. Vibration-based gait retraining improves center of pressure positioning but effects on neuromechanical variables influencing joint loading remains unknown.

RESEARCH QUESTION

Do patients with CAI exhibit altered vGRF and ankle joint contact forces (JCF) after receiving a single session of vibration-based gait retraining?

METHODS

Ten individuals with CAI underwent a single session of vibration-based gait retraining. Kinematic and kinetic data were collected during walking on an instrumental treadmill with force plates embedded in it. Following a baseline gait assessment without feedback, participants walked at a self-selected speed for 10 minutes while receiving feedback. Data was collected during an early (1 st and 2 nd minute) and late adaptation phase (9 th and 10 th minute) and, compared to baseline values. Impact and propulsive vGRF variables (i.e. peak, time to peak, and loading rate) were obtained. Musculoskeletal modeling was used to calculate ankle JCF variables (peak, impulse, and loading rate) during stance phase.

RESULTS

Propulsive vGRF and ankle JCF outcomes were significantly reduced during the early and late adaptation phases (p ≤ 0.039).

SIGNIFICANCE

These results indicate that vibration-based gait retraining can immediately reduce propulsive vGRF and ankle JCF and may represent a modality that could help restore appropriate ankle joint loading patterns in those with CAI.

Subject-Specific Spino-Pelvic Models Reliably Measure Spinal Kinematics During Seated Forward Bending in Adult Spinal Deformity

Image-based subject-specific models and simulations are recently being introduced to complement current state-of-the-art mostly static insights of the adult spinal deformity (ASD) pathology and improve the often poor surgical outcomes. Although the accuracy of a recently developed subject-specific modeling and simulation framework has already been quantified, its reliability to perform marker-driven kinematic analyses has not yet been investigated. The aim of this work was to evaluate the reliability of this subject-specific framework to measure spine kinematics in ASD patients, in terms of 1) the overall test-retest repeatability; 2) the inter-operator agreement of spine kinematic estimates; and, 3) the uncertainty of those spine kinematics to operator-dependent parameters of the framework. To evaluate the overall repeatability 1], four ASD subjects and one control subject participated in a test-retest study with a 2-week interval. At both time instances, subject-specific spino-pelvic models were created by one operator to simulate a recorded forward trunk flexion motion. Next, to evaluate inter-operator agreement 2], three trained operators each created a model for three ASD subjects to simulate the same forward trunk flexion motion. Intraclass correlation coefficients (ICC's) of the range of motion (ROM) of conventional spino-pelvic parameters [lumbar lordosis (LL), sagittal vertical axis (SVA), thoracic kyphosis (TK), pelvic tilt (PT), T1-and T9-spino-pelvic inclination (T1/T9-SPI)] were used to evaluate kinematic reliability 1] and inter-operator agreement 2]. Lastly, a Monte-Carlo probabilistic simulation was used to evaluate the uncertainty of the intervertebral joint kinematics to operator variability in the framework, for three ASD subjects 3]. LL, SVA, and T1/T9-SPI had an excellent test-retest reliability for the ROM, while TK and PT did not. Inter-operator agreement was excellent, with ICC values higher than test-retest reliability. These results indicate that operator-induced uncertainty has a limited impact on kinematic simulations of spine flexion, while test-retest reliability has a much higher variability. The definition of the intervertebral joints in the framework was identified as the most sensitive operator-dependent parameter. Nevertheless, intervertebral joint estimations had small mean 90% confidence intervals (1.04°-1.75°). This work will contribute to understanding the limitations of kinematic simulations in ASD patients, thus leading to a better evaluation of future hypotheses.

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

No consensus exists on how to model human articulations within MSK models for the analysis of gait dynamics. We propose a method to evaluate joint models and we apply it to three models with different levels of personalization. The method evaluates the joint model’s adherence to the MSK hypothesis of negligible joint work by quantifying ligament and cartilage deformations resulting from joint motion; to be anatomically consistent, these deformations should be minimum. The contrary would require considerable external work to move the joint, violating a strong working hypothesis and raising concerns about the credibility of the MSK outputs. Gait analysis and medical resonance imaging (MRI) from ten participants were combined to build lower limb subject-specific MSK models. MRI-reconstructed anatomy enabled three levels of personalization using different ankle joint models, in which motion corresponded to different ligament elongation and cartilage co-penetration. To estimate the impact of anatomical inconsistency in MSK outputs, joint internal forces resulting from tissue deformations were computed for each joint model and MSK simulations were performed ignoring or considering their contribution. The three models differed considerably for maximum ligament elongation and cartilage co-penetration (between 5.94 and 50.69% and between −0.53 and −5.36 mm, respectively). However, the model dynamic output from the gait simulations were similar. When accounting for the internal forces associated with tissue deformation, outputs changed considerably, the higher the personalization level the smaller the changes. Anatomical consistency provides a solid method to compare different joint models. Results suggest that consistency grows with personalization, which should be tailored according to the research question. A high level of anatomical consistency is recommended when individual specificity and the behavior of articular structures is under investigation.

Subject-Specific Modeling of Femoral Torsion Influences the Prediction of Hip Loading During Gait in Asymptomatic Adults

Hip osteoarthritis may be caused by increased or abnormal intra-articular forces, which are known to be related to structural articular cartilage damage. Femoral torsional deformities have previously been correlated with hip pain and labral damage, and they may contribute to the onset of hip osteoarthritis by exacerbating the effects of existing pathoanatomies, such as cam and pincer morphologies. A comprehensive understanding of the influence of femoral morphotypes on hip joint loading requires subject-specific morphometric and biomechanical data on the movement characteristics of individuals exhibiting varying degrees of femoral torsion. The aim of this study was to evaluate hip kinematics and kinetics as well as muscle and joint loads during gait in a group of adult subjects presenting a heterogeneous range of femoral torsion by means of personalized musculoskeletal models. Thirty-seven healthy volunteers underwent a 3D gait analysis at a self-selected walking speed. Femoral torsion was evaluated with low-dosage biplanar radiography. The collected motion capture data were used as input for an inverse dynamics analysis. Personalized musculoskeletal models were created by including femoral geometries that matched each subject’s radiographically measured femoral torsion. Correlations between femoral torsion and hip kinematics and kinetics, hip contact forces (HCFs), and muscle forces were analyzed. Within the investigated cohort, higher femoral antetorsion led to significantly higher anteromedial HCFs during gait (medial during loaded stance phase and anterior during swing phase). Most of the loads during gait are transmitted through the anterior/superolateral quadrant of the acetabulum. Correlations with hip kinematics and muscle forces were also observed. Femoral antetorsion, through altered kinematic strategies and different muscle activations and forces, may therefore lead to altered joint mechanics and pose a risk for articular damage. The method proposed in this study, which accounts for both morphological and kinematic characteristics, might help in identifying in a clinical setting patients who, as a consequence of altered femoral torsional alignment, present more severe functional impairments and altered joint mechanics and are therefore at a higher risk for cartilage damage and early onset of hip osteoarthritis.

Generic scaled versus subject-specific models for the calculation of musculoskeletal loading in cerebral palsy gait: Effect of personalized musculoskeletal geometry outweighs the effect of personalized neural control

BACKGROUND

Musculoskeletal modelling is used to assess musculoskeletal loading during gait. Linear scaling methods are used to personalize generic models to each participant's anthropometry. This approach introduces simplifications, especially when used in paediatric and/or pathological populations. This study aimed to compare results from musculoskeletal simulations using various models ranging from linear scaled to highly subject-specific models, i.e., including the participant's musculoskeletal geometry and electromyography data.

METHODS

Magnetic resonance images (MRI) and gait data of one typically developing child and three children with cerebral palsy were analysed. Musculoskeletal simulations were performed to calculate joint kinematics, joint kinetics, muscle forces and joint contact forces using four modelling frameworks: 1) Generic-scaled model with static optimization, 2) Generic-scaled model with an electromyography-informed approach, 3) MRI-based model with static optimization, and 4) MRI-based model with an electromyography-informed approach.

FINDINGS

Root-mean-square-differences in joint kinematics and kinetics between generic-scaled and MRI-based models were below 5° and 0.15 Nm/kg, respectively. Root-mean-square-differences over all muscles was below 0.2 body weight for every participant. Root-mean-square-differences in joint contact forces between the different modelling frameworks were up to 2.2 body weight. Comparing the simulation results from the typically developing child with the results from the children with cerebral palsy showed similar root-mean-square-differences for all modelling frameworks.

INTERPRETATION

In our participants, the impact of MRI-based models on joint contact forces was higher than the impact of including electromyography. Clinical reasoning based on overall root-mean-square-differences in musculoskeletal simulation results between healthy and pathological participants are unlikely to be affected by the modelling choice.

The impact of anatomical uncertainties on the predictions of a musculoskeletal hand model - a sensitivity study

Outputs of musculoskeletal models should be considered probabilistic rather than deterministic as they are affected by inaccuracies and estimations associated with the development of the model. One of these uncertainties being critical for modeling arises from the determination of the muscles' line of action and the physiological cross-sectional area. Therefore, the aim of this study was to evaluate the outcome sensitivity of model predictions from a musculoskeletal hand model in comparison to the uncertainty of these input parameters. For this purpose, the kinematics and muscle activities of different hand movements (abduction of the fingers, abduction of the thumb, and flexion of the thumb) were recorded. One thousand simulations were calculated for each movement using the Latin hypercube sampling method with a corresponding variation of the muscle origin/insertion points and the cross-sectional area. Comparing the standard hand to simulations incorporating uncertainties of input parameters shows no major deviations in on- and off-set time point of muscle activities. About 60% of simulations are located within a ± 30% interval around the standard model concerning joint reaction forces. The comparison with the variation of the input data leads to the conclusion that the standard hand model is able to provide not over-scattered outcomes and, therefore, can be considered relatively stable. These results are of practical importance to the personalization of a musculoskeletal model with subject-specific bone geometries and hence changed muscle line of action.

Anthropometric scaling of musculoskeletal models of the hand captures age-dependent differences in lateral pinch force

Musculoskeletal models and computer simulations enable non-invasive study of muscle function and contact forces. Hand models are useful for understanding the complexities of hand strength, precision movement, and the dexterity required during daily activities. Yet, generic models fail to accurately represent the entire scope of the population, while subject-specific models are labor-intensive to create. The objective of this study was to assess the efficacy of scaled generic models to represent the broad spectrum of strength profiles across the lifespan. We examined one hundred lateral pinch simulations using a generic model of the wrist and thumb anthropometrically scaled to represent the full range of heights reported for four ages across childhood, puberty, older adolescence, and adulthood. We evaluated maximum lateral pinch force produced, muscle control strategies, and the effect of linearly scaling the maximum isometric force. Our simulations demonstrated three main concepts. First, anthropometric scaling could capture age-dependent differences in pinch strength. Second, a generic muscle control strategy is not representative of all populations. Lastly, simulations do not employ optimal fiber length to complete a lateral pinch task. These results demonstrate the potential of anthropometrically-scaled models to study hand strength across the lifespan, while also highlighting that muscle control strategies may adapt as we age. The results also provide insight to the force-length relationship of thumb muscles during lateral pinch. We conclude that anthropometric scaling can accurately represent age characteristics of the population, but subject-specific models are still necessary to represent individuals.

An Anatomical Atlas-Based Scaling Study for Quantifying Muscle and Hip Joint Contact Forces in Above and Through-Knee Amputees Using Validated Musculoskeletal Modelling

OBJECTIVE

Customisation of musculoskeletal modelling using magnetic resonance imaging (MRI) significantly improves the model accuracy, but the process is time consuming and computationally intensive. This study hypothesizes that linear scaling to a lower limb amputee model with anthropometric similarity can accurately predict muscle and joint contact forces.

METHODS

An MRI-based anatomical atlas, comprising 18 trans-femoral and through-knee traumatic lower limb amputee models, is developed. Gait data, using a 10-camera motion capture system with two force plates, and surface electromyography (EMG) data were collected. Muscle and hip joint contact forces were quantified using musculoskeletal modelling. The predicted muscle activations from the subject-specific models were validated using EMG recordings. Anthropometry based multiple linear regression models, which minimize errors in force predictions, are presented.

RESULTS

All predictions showed excellent (error interval c = 0-0.15), very good (c = 0.15-0.30) or good (c = 0.30-0.45) similarity to the EMG data, demonstrating accurate computation of muscle activations. The primary predictors of discrepancies in force predictions were differences in pelvis width (p < 0.001), body mass index (BMI, p < 0.001) and stump length to pelvis width ratio (p < 0.001) between the respective individual and underlying dataset.

CONCLUSION

Linear scaling to a model with the most similar pelvis width, BMI and stump length to pelvis width ratio results in modelling outcomes with minimal errors.

SIGNIFICANCE

This study provides robust tools to perform accurate analyses of musculoskeletal mechanics for high-functioning lower limb military amputees, thus facilitating the further understanding and improvement of the amputee's function. The atlas is available in an open source repository.

Development and evaluation of a new methodology for Soft Tissue Artifact compensation in the lower limb

Skin Marker (SM) based motion capture is the most widespread technique used for motion analysis. Yet, the accuracy is often hindered by Soft Tissue Artifact (STA). This is a major issue in clinical gait analysis where kinematic results are used for decision-making. It also has a considerable influence on the results of rigid body and Finite Element (FE) musculoskeletal models that rely on SM-based kinematics to estimate muscle, contact and ligament forces. Current techniques devised to compensate for STA, in particular multi-body optimization methods, often consider simplified joint models. Although joint personalization with anatomical constraints has improved kinematic estimation, these models yet don't represent a fully reliable solution to the STA problem, thus allowing us to envisage an alternative approach. In this perspective, we propose to develop a conceptual FE-based model of the lower limb for STA compensation and evaluate it for 66 healthy subjects under level walking motor task. Both hip and knee joint kinematics were analyzed, considering both rotational and translational joint motion. Results showed that STA caused underestimation of the hip joint kinematics (up to 2.2°) for all rotational DoF, and overestimation of knee joint kinematics (up to 12°) except in flexion/extension. Joint kinematics, in particular the knee joint, appeared to be sensitive to soft tissue stiffness parameters (rotational and translational mean difference up to 1.5° and 3.4 mm). Analysis of the results using alternative joint representations highlighted the versatility of the proposed modeling approach. This work paves the way for using personalized models to compensate for STA in healthy subjects and different activities.

Development of a three-dimensional computer model of the canine pelvic limb including cruciate ligaments to simulate movement

Gait analysis as subjective visual assessment forms the foundation of the veterinarian's lameness examination. Pelvic limb lameness is frequently seen in dogs and the stifle joint with its cruciate ligaments, is a main cause of lameness due to cruciate ligament deficiency. In this study, we developed an open-source three-dimensional musculoskeletal pelvic limb model of a 30 kg Labrador Retriever including cruciate ligaments, simulating the gait cycle of the walking movement with the open-source programs NMSBuilder (Institutio Ortopedico Rizzoli, Bologna, Italy) and OpenSim (National Center for Simulation in Rehabilitation Research (NCSRR), Stanford, CA, USA). The computer model generated muscle activations based on motion data. The computed activations were similar to experimental electromyogram data. Highest joint torque was in extension/flexion in the stifle joint at 54 Nm at 14% of the gait cycle with cruciate ligaments. Highest stifle joint reaction force was 408 N at 16% of the gait cycle and was reduced after adding cruciate ligaments. Especially the cranial cruciate ligament loads up to 102 N (34% body weight). Cranial cruciate ligament forces increase with stifle extension and decrease with stifle flexion. On the contrary, the caudal cruciate ligament loads up to 27 N (9% body weight) during the swing phase with a flexed stifle joint. The model was validated with electromyogram data. The model's predictions are plausible because joint torques and forces match the applied ground reaction forces in curve progression and in timing. This model forms a basis for further investigations into stifle surgery after cruciate ligament deficiency.

Predictions of Anterior Cruciate Ligament Dynamics From Subject-Specific Musculoskeletal Models and Dynamic Biplane Radiography

In vivo knee ligament forces are important to consider for informing rehabilitation or clinical interventions. However, they are difficult to directly measure during functional activities. Musculoskeletal models and simulations have become the primary methods by which to estimate in vivo ligament loading. Previous estimates of anterior cruciate ligament (ACL) forces range widely, suggesting that individualized anatomy may have an impact on these predictions. Using ten subject-specific (SS) lower limb musculoskeletal models, which include individualized musculoskeletal geometry, muscle architecture, and six degree-of-freedom knee joint kinematics from dynamic biplane radiography (DBR), this study provides SS estimates of ACL force (anteromedial-aACL; and posterolateral-pACL bundles) during the full gait cycle of treadmill walking. These forces are compared to estimates from scaled-generic (SG) musculoskeletal models to assess the effect of musculoskeletal knee joint anatomy on predicted forces and the benefit of SS modeling in this context. On average, the SS models demonstrated a double force peak during stance (0.39-0.43 xBW per bundle), while only a single force peak during stance was observed in the SG aACL. No significant differences were observed between continuous SG and SS ACL forces; however, root mean-squared differences between SS and SG predictions ranged from 0.08 xBW to 0.27 xBW, suggesting SG models do not reliably reflect forces predicted by SS models. Force predictions were also found to be highly sensitive to ligament resting length, with ±10% variations resulting in force differences of up to 84%. Overall, this study demonstrates the sensitivity of ACL force predictions to SS anatomy, specifically musculoskeletal joint geometry and ligament resting lengths, as well as the feasibility for generating SS musculoskeletal models for a group of subjects to predict in vivo tissue loading during functional activities.

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.

Paggiosi M, McCloskey EV, Viceconti M, Mazzà C, Li X. Femoral neck strain prediction during level walking using a combined musculoskeletal and finite element model approach

Recently, coupled musculoskeletal-finite element modelling approaches have emerged as a way to investigate femoral neck loading during various daily activities. Combining personalised gait data with finite element models will not only allow us to study changes in motion/movement, but also their effects on critical internal structures, such as the femur. However, previous studies have been hampered by the small sample size and the lack of fully personalised data in order to construct the coupled model. Therefore, the aim of this study was to build a pipeline for a fully personalised multiscale (body-organ level) model to investigate the strain levels at the femoral neck during a normal gait cycle. Five postmenopausal women were included in this study. The CT and MRI scans of the lower limb, and gait data were collected for all participants. Muscle forces derived from the body level musculoskeletal models were used as boundary constraints on the finite element femur models. Principal strains were estimated at the femoral neck region during a full gait cycle. Considerable variation was found in the predicted peak strain among individuals with mean peak first principal strain of 0.24% ± 0.11% and mean third principal strain of -0.29% ± 0.24%. For four individuals, two overall peaks of the maximum strains were found to occur when both feet were in contact with the floor, while one individual had one peak at the toe-off phase. Both the joint contact forces and the muscular forces were found to substantially influence the loading at the femoral neck. A higher correlation was found between the predicted peak strains and the gluteus medius (R² ranged between 0.95 and 0.99) than the hip joint contact forces (R² ranged between 0.63 and 0.96). Therefore, the current findings suggest that personal variations are substantial, and hence it is important to consider multiple subjects before deriving general conclusions for a target population.

A backpack load sharing model to evaluate lumbar and hip joint contact forces during shoulder borne and hip belt assisted load carriage

Musculoskeletal injuries of the lumbar spine occur frequently among military service members and are associated with heavy backpack loads. Musculoskeletal modeling and simulation facilitate biomechanical evaluation to compare different backpack designs. We developed a backpack attachment model that can be tuned to represent various load distributions between the torso and pelvis. We generated walking simulations to estimate muscle and joint contact forces of unloaded walking and while carrying 38 kg using shoulder-borne backpacks and hip belt-assisted backpacks for six U.S. Marines. Three-dimensional peak and average lumbar (L4-L5) and hip joint contact forces over the stance phase were compared between each load condition. Axial L4-L5 and axial and anterior hip joint contact forces were greater during both backpack conditions compared to the unloaded condition. Joint contact forces were similar between backpack conditions. Future studies incorporating additional participants, walking conditions, and backpack load distributions are suggested for further model development and backpack design evaluation.

Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries

The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.

A Systematic Review of the Associations Between Inverse Dynamics and Musculoskeletal Modeling to Investigate Joint Loading in a Clinical Environment

The assessment of knee or hip joint loading by external joint moments is mainly used to draw conclusions on clinical decision making. However, the correlation between internal and external loads has not been systematically analyzed. This systematic review aims, therefore, to clarify the relationship between external and internal joint loading measures during gait. A systematic database search was performed to identify appropriate studies for inclusion. In total, 4,554 articles were identified, while 17 articles were finally included in data extraction. External joint loading parameters were calculated using the inverse dynamics approach and internal joint loading parameters by musculoskeletal modeling or instrumented prosthesis. It was found that the medial and total knee joint contact forces as well as hip joint contact forces in the first half of stance can be well predicted using external joint moments in the frontal plane, which is further improved by including the sagittal joint moment. Worse correlations were found for the peak in the second half of stance as well as for internal lateral knee joint contact forces. The estimation of external joint moments is useful for a general statement about the peak in the first half of stance or for the maximal loading. Nevertheless, when investigating diseases as valgus malalignment, the estimation of lateral knee joint contact forces is necessary for clinical decision making because external joint moments could not predict the lateral knee joint loading sufficient enough. Dependent on the clinical question, either estimating the external joint moments by inverse dynamics or internal joint contact forces by musculoskeletal modeling should be used.

MRI-based anatomical characterisation of lower-limb muscles in older women

The ability of muscles to produce force depends, among others, on their anatomical features and it is altered by ageing-associated weakening. However, a clear characterisation of these features, highly relevant for older individuals, is still lacking. This study hence aimed at characterising muscle volume, length, and physiological cross-sectional area (PCSA) and their variability, between body sides and between individuals, in a group of post-menopausal women. Lower-limb magnetic resonance images were acquired from eleven participants (69 (7) y. o., 66.9 (7.7) kg, 159 (3) cm). Twenty-three muscles were manually segmented from the images and muscle volume, length and PCSA were calculated from this dataset. Personalised maximal isometric force was then calculated using the latter information. The percentage difference between the muscles of the two lower limbs was up to 89% and 22% for volume and length, respectively, and up to 84% for PCSA, with no recognisable pattern associated with limb dominance. Between-subject coefficients of variation reached 36% and 13% for muscle volume and length, respectively. Generally, muscle parameters were similar to previous literature, but volumes were smaller than those from in-vivo young adults and slightly higher than ex-vivo ones. Maximal isometric force was found to be on average smaller than those obtained from estimates based on linear scaling of ex-vivo-based literature values. In conclusion, this study quantified for the first time anatomical asymmetry of lower-limb muscles in older women, suggesting that symmetry should not be assumed in this population. Furthermore, we showed that a scaling approach, widely used in musculoskeletal modelling, leads to an overestimation of the maximal isometric force for most muscles. This heavily questions the validity of this approach for older populations. As a solution, the unique dataset of muscle segmentation made available with this paper could support the development of alternative population-based scaling approaches, together with that of automatic tools for muscle segmentation.

A generic musculoskeletal model of the juvenile lower limb for biomechanical analyses of gait

The aim of this study was to develop a generic musculoskeletal model of a healthy 10-year-old child and examine the effects of geometric scaling on the calculated values of lower-limb muscle forces during gait. Subject-specific musculoskeletal models of five healthy children were developed from in vivo MRI data, and these models were subsequently used to create a generic juvenile (GJ) model. Calculations of lower-limb muscle forces for normal walking obtained from two scaled-generic versions of the juvenile model (SGJ1 and SGJ2) were evaluated against corresponding results derived from an MRI-based model of one subject (SSJ1). The SGJ1 and SGJ2 models were created by scaling the GJ model using gait marker positions and joint centre locations derived from MRI imaging, respectively. Differences in the calculated values of peak isometric muscle forces and muscle moment arms between the scaled-generic models and MRI-based model were relatively small. Peak isometric muscle forces calculated for SGJ1 and SGJ2 were respectively 2.2% and 3.5% lower than those obtained for SSJ1. Model-predicted muscle forces for SGJ2 agreed more closely with calculations obtained from SSJ1 than corresponding results derived from SGJ1. These results suggest that accurate estimates of muscle forces during gait may be obtained by scaling generic juvenile models based on joint centre locations. The generic juvenile model developed in this study may be used as a template for creating subject-specific musculoskeletal models of normally-developing children in studies aimed at describing lower-limb muscle function during gait.

Soft tissue artifact causes underestimation of hip joint kinematics and kinetics in a rigid-body musculoskeletal model

Rigid body musculoskeletal models have been applied to study kinematics, moments, muscle forces, and joint reaction forces in the hip. Most often, models are driven with segment motions calculated through optical tracking of markers adhered to the skin. One limitation of optical tracking is soft tissue artifact (STA), which occurs due to motion of the skin surface relative to the underlying skeleton. The purpose of this study was to quantify differences in musculoskeletal model outputs when tracking body segment positions with skin markers as compared to bony landmarks measured by direct imaging of bone motion with dual fluoroscopy (DF). Eleven asymptomatic participants with normally developed hip anatomy were imaged with DF during level treadmill walking at a self-selected speed. Hip joint kinematics and kinetics were generated using inverse kinematics, inverse dynamics, static optimization and joint reaction force analysis. The effect of STA was assessed by comparing the difference in estimates from simulations based on skin marker positions (SM) versus virtual markers on bony landmarks from DF. While patterns were similar, STA caused underestimation of kinematics, range of motion (ROM), moments, and reaction forces at the hip, including flexion-extension ROM, maximum internal rotation joint moment and peak joint reaction force magnitude. Still, kinetic differences were relatively small, and thus they may not be relevant nor clinically meaningful.

Squeaking and other noises in patients with ceramic-on-ceramic total hip arthroplasty

INTRODUCTION

Noise in ceramic-on-ceramic (CoC) total hip arthroplasty (THA) is a potential symptom of abnormal bearing wear. Squeaking and other prosthetic hip noises are multi-factorial phenomena that can be analysed and may provide prognostic information.

METHODS

46 patients with noisy CoC bearings were investigated using X-ray, computed tomography and joint fluid analysis, and classified into either high or low risk of ceramic liner fracture groups according to previously published guidelines. Noise events from the bearings of 16 high risk cases which were subsequently revised were compared with 30 patients in the low risk control group who did not undergo revision. Noise events were analysed for their physical characteristics using a standardised protocol and classified as either low frequency and short duration 'clicking' or long duration and high frequency 'squeaking'.

RESULTS

The peak frequency of squeaking during forward walking was significantly higher for patients in the case group who were revised, compared with the control group. The patient-reported onset of squeaking (46 months postoperatively) was earlier than short-noise emissions (82 months). In the standardised sequence of movements, short-noise always occurred more frequently than squeaking. Small heads (28 mm) were more likely to develop short-noise, while large heads (⩾32 mm) were more likely to develop squeaking.

DISCUSSION

Noise evaluation may provide additional value for predicting failure of CoC bearings, though some questions should be better investigated in a dedicated prospective trial.