Subject-specific hip geometry affects predicted hip joint contact forces during gait

Musculoskeletal modeling and movement simulation for structural hip disorder research: A scoping review of methods, validation, and applications

Musculoskeletal modeling is a powerful tool to quantify biomechanical factors typically not feasible to measure in vivo, such as hip contact forces and deep muscle activations. While technological advancements in musculoskeletal modeling have increased accessibility, selecting the appropriate modeling approach for a specific research question, particularly when investigating pathological populations, has become more challenging. The purposes of this review were to summarize current modeling and simulation methods in structural hip disorder research, as well as evaluate model validation and study reproducibility. MEDLINE and Web of Science were searched to identify literature relating to the use of musculoskeletal models to investigate structural hip disorders (i.e., involving a bony abnormality of the pelvis, femur, or both). Forty-seven articles were included for analysis, which either compared multiple modeling methods or applied a single modeling workflow to answer a research question. Findings from studies comparing methods were summarized, such as the effect of generic versus patient-specific modeling techniques on model-estimated hip contact forces or muscle forces. The review also discussed limitations in validation practices, as only 11 of the included studies conducted a validation and used qualitative approaches only. Given the lack of information related to model validation, additional details regarding the development and validation of generic models were retrieved from references and modeling software documentation. To address the wide variability and under-reporting of data collection, data processing, and modeling methods highlighted in this review, we developed a template that researchers can complete and include as a table within the methodology section of their manuscripts. The use of this table will help increase transparency and reporting of essential details related to reproducibility and methods without being limited by word count restrictions. Overall, this review provides a comprehensive synthesis of modeling approaches that can help researchers make modeling decisions and evaluate existing literature.

Shape-model scaling is more robust than linear scaling to marker placement error

When reconstructing bone geometry to calculate joint kinematics, shape-model scaling can be more accurate and repeatable than linear scaling given the same anatomical landmarks. This study perturbed anatomical landmarks from optical motion capture and determined the robustness of shape-model scaling to misplaced markers compared to a traditional approach of linear scaling. We hypothesised that shape-model scaling would be less susceptible to variance in marker positions compared to linear scaling. The positions of hip joint centres and femoral/tibial segment lengths across perturbations were compared to determine each scaling method's range of geometric variation. The standard deviation (SD) of the hip joint centre location from the shape model had a maximum of 1.4 mm, compared to 4.2 mm for linear scaling. Femoral and tibial segments displayed SD's of 5.4 mm and 5.2 mm when shape-model scaled, compared to 9.2 mm and 9.5 mm with linear scaling, respectively, thus supporting our hypothesis. Geometric constraints within a shape model provide robustness to marker misplacement providing potential improvements in repeatability and data exchange.

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.

Peak knee joint moments accurately predict medial and lateral knee contact forces in patients with valgus malalignment

Compressive knee joint contact force during walking is thought to be related to initiation and progression of knee osteoarthritis. However, joint loading is often evaluated with surrogate measures, like the external knee adduction moment, due to the complexity of computing joint contact forces. Statistical models have shown promising correlations between medial knee joint contact forces and knee adduction moments in particularly in individuals with knee osteoarthritis or after total knee replacements (R² = 0.44-0.60). The purpose of this study was to evaluate how accurately model-based predictions of peak medial and lateral knee joint contact forces during walking could be estimated by linear mixed-effects models including joint moments for children and adolescents with and without valgus malalignment. Peak knee joint moments were strongly correlated (R² > 0.85, p < 0.001) with both peak medial and lateral knee joint contact forces. The knee flexion and adduction moments were significant covariates in the models, strengthening the understanding of the statistical relationship between both moments and medial and lateral knee joint contact forces. In the future, these models could be used to evaluate peak knee joint contact forces from musculoskeletal simulations using peak joint moments from motion capture software, obviating the need for time-consuming musculoskeletal simulations.

On the estimation of hip joint loads through musculoskeletal modeling

Noninvasive estimation of joint loads is still an open challenge in biomechanics. Although musculoskeletal modeling represents a solid resource, multiple improvements are still necessary to obtain accurate predictions of joint loads and to translate such potential into practical utility. The present study, focused on the hip joint, is aimed at reviewing the state-of-the-art literature on the estimation of hip joint reaction forces through musculoskeletal modeling. Our literature inspection, based on well-defined selection criteria, returned seventeen works, which were compared in terms of methods and results. Deviations between predicted and in vivo measured hip joint loads, taken from the OrthoLoad database, were assessed through quantitative deviation indices. Despite the numerous modeling and computational improvements made over the last two decades, predicted hip joint loads still deviate from their experimental counterparts and typically overestimate them. Several critical aspects have emerged that affect muscle force estimation, hence joint loads. Among them, the physical fidelity of the musculoskeletal model, with its parameters and geometry, plays a crucial role. Also, predicted joint loads are markedly affected by the selected muscle recruitment strategy, which reflects the underlying motor control policy. Practical guidelines for researchers interested in noninvasive estimation of hip joint loads are also provided.

Assessment methodology for human-exoskeleton interactions: Kinetic analysis based on muscle activation

During the development and assessment of an exoskeleton, many different analyzes need to be performed. The most frequently used evaluate the changes in muscle activations, metabolic consumption, kinematics, and kinetics. Since human-exoskeleton interactions are based on the exchange of forces and torques, the latter of these, kinetic analyzes, are essential and provide indispensable evaluation indices. Kinetic analyzes, however, require access to, and use of, complex experimental apparatus, involving many instruments and implicating lengthy data analysis processes. The proposed methodology in this paper, which is based on data collected via EMG and motion capture systems, considerably reduces this burden by calculating kinetic parameters, such as torque and power, without needing ground reaction force measurements. This considerably reduces the number of instruments used, allows the calculation of kinetic parameters even when the use of force sensors is problematic, does not need any dedicated software, and will be shown to have high statistical validity. The method, in fact, combines data found in the literature with those collected in the laboratory, allowing the analysis to be carried out over a much greater number of cycles than would normally be collected with force plates, thus enabling easy access to statistical analysis. This new approach evaluates the kinetic effects of the exoskeleton with respect to changes induced in the user's kinematics and muscular activation patterns and provides indices that quantify the assistance in terms of torque (AMI) and power (API). Following the User-Center Design approach, which requires driving the development process as feedback from the assessment process, this aspect is critical. Therefore, by enabling easy access to the assessment process, the development of exoskeletons could be positively affected.

Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children

Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models.

Thin patient-specific clavicle fracture fixation plates can mechanically outperform commercial plates: An in silico approach

Current fixation plates used to operatively stabilize clavicular fractures are suboptimal, leading to reoperation rates up to 53%. Plate irritation, which can be caused by a poor geometric fit and plate thickness, has been found to be an important factor for reoperation. Moreover, muscle attachment sites (MAS) have to be detached occasionally. To improve current surgical clavicle fracture treatment with plate osteosynthesis, a change in plate design is required. The goal of this study was to design a patient-specific clavicle fracture fixation plate that includes geometrical optimization and stiffness determination. Its biomechanical performance has been compared with a commercial plate by examining the geometric fit, anatomical outline, stresses and interfragmentary motion using a finite element analysis with physiological loading and boundary conditions. Evaluation showed a better geometrical fit of the patient-specific plate as well as an improved fracture reduction. Displacements between fracture fragments were lower in case of the patient-specific plate, both when a fracture gap and no fracture gap were present. Results indicate a superior mechanical performance in terms of all investigated outcomes of the patient-specific plate compared to the commercial plate, while better aligning with the patient-specific geometry and without the need for MAS release. Due to the patient-specific geometry and reduced thickness, these fixation plates are expected to decrease the operation time, as intraoperative contouring will become irrelevant, and to decrease reoperation rates as implant irritation will be minimized.

A single-surgeon experience in reconstruction of femoro-acetabular offset and implant positioning in direct anterior approach and anterolateral MIS approach with a curved short stem

PURPOSE

Minimally invasive surgery using short stems in total hip arthroplasty gained more popularity. The differences in change of hip offset and implant positioning in minimally invasive approaches are not fully known. Therefore, this study was conducted to evaluate the difference in reconstruction of hip offset and implant positioning in direct anterior approach (DAA) and minimally invasive anterolateral approach (AL MIS).

METHODS

A single surgeon series of 117 hips (117 patients; mean age 65.54 years ± 11.47; index surgery 2014-2018) were included and allocated into two groups: group A (DAA) with 70 hips and Group B (AL MIS) with 47 patients operated. In both groups the same type of cementless curved short hip stem and press fit cup was used.

RESULTS

Both groups showed an equal statistically significant increase of femoral (p < 0.001) and decrease of acetabular offset (p < 0.001). Between both groups no statistically significant difference in offset reconstruction, leg length difference or implant positioning could be found. Leg length increased in both groups significantly and leg length discrepancy showed no difference (group A: - 0.06 mm; group B: 1.11 mm; p < 0.001). A comparable number of cups were positioned outside the target zone regarding cup anteversion.

CONCLUSION

The usage of a curved short stem shows an equal reconstruction of femoro-acetabular offset, leg length and implant positioning in both MIS approaches. The results of this study show comparable results to the existing literature regarding change of offset and restoration of leg length. Malposition of the acetabular component regarding anteversion poses a risk.

Lower-limb Joint Torque Prediction using LSTM Neural Networks and Transfer Learning

Estimation of joint torque during movement provides important information in several settings, such as effect of athletes' training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device. The ability to estimate joint torque during daily activities using wearable sensors is increasingly relevant in such settings. In this study, lower limb joint torques during ten daily activities were predicted by long short-term memory (LSTM) neural networks and transfer learning. LSTM models were trained with muscle electromyography signals and lower limb joint angles. Hip flexion/extension, hip abduction/adduction, knee flexion/extension and ankle dorsiflexion/plantarflexion torques were predicted. The LSTM models' performance in predicting torque was investigated in both intra-subject and inter-subject scenarios. Each scenario was further divided into intra-task and inter-task tests. We observed that LSTM models could predict lower limb joint torques during various activities accurately with relatively low error (root mean square error ≤ 0.14 Nm/kg, normalized root mean square error ≤8.7%) either through a uniform model or through ten separate models in intra-subject tests. Furthermore, a transfer learning technique was adopted in the inter-task and inter-subject tests to further improve the generalizability of LSTM models by pre-training a model on multiple subjects and/or tasks and transferring the learned knowledge to a target task/subject. Particularly in the inter-subject tests, we could predict joint torques accurately in several movements after training from only a few movements from new subjects.

Peri-prosthetic bone remodeling of hydroxyapatite-coated compaction short stem was not affected by stem alignment

Background

To improve implant survival through accelerated early bone remodeling during total hip arthroplasty (THA), hydroxyapatite (HA) is widely used as a bioactive coating, which is believed to enhance initial fixation by osseointegration. We aimed to investigate the relationship between stem insertion alignment and postoperative bone mineral density (BMD) changes in patients with full hydroxyapatite-coated (HA) compaction short stem and short tapered-wedge stem.

Methods

This retrospective cohort study enrolled 115 consecutive patients (115 joints) undergoing THA using the full HA compaction short (n = 59) and short tapered-wedge (n = 56) stems. Stem alignment, including anteversion, valgus, and anterior tilt were measured by a three-dimensional template using computed tomography data. Post-operative peri-prosthetic BMD was measured by dual-energy X-ray absorptiometry. The relationship between stem alignment and BMD changes in the stems was analyzed.

Results

Patterns of peri-prosthetic BMD changes were similar in both groups. Stem insertion alignments of anteversion, valgus, and anterior tilt were different between the two stem types. Stem alignment of valgus and anterior tilt did not affect peri-prosthetic BMD in either of the stem type. An absolute anteversion difference between stem anteversion and original canal anteversion caused significant peri-prosthetic BMD loss in Gruen zones one and seven in the tapered-wedge stem. However, stem alignment of absolute anteversion difference did not affect BMD changes in the HA compaction stem.

Conclusions

Peri-prosthetic bone remodeling remained unaffected by stem alignment after THA with the new short full HA compaction stem.

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.

LIGAMENT PRESERVING TOTAL HIP ARTHROPLASTY PREVENTS DIFFERENT LEG LENGTH AND FEMORAL OFFSET

Objectives:

The leg length (LL) and femoral offset (FO) discrepancy following total hip arthroplasty (THA) are important factors for postoperative outcomes and restoring native hip biomechanics is essential for THA. Hip capsular ligament contributes to joint stability; however, there are few studies about the influence of ligament preservation on LLD and FO following THA.

Methods:

We conducted a retrospective study involving 60 patients who underwent primary THA using a short stem through the anterolateral approach between June 2016 and August 2018. From August 2017, we preserved the vertical band of iliofemoral ligament and the pubofemoral ligament in THA, and the compared pre- and postoperative radiographic LLD and FO difference between the ligament preservation (n = 30) and ligament excision (n = 30) groups.

Results:

Postoperative LLD was significantly smaller in the ligament preservation than in the ligament excision group. The ratio of excessive LLD and FO difference was lower in the ligament preservation group than the ligament excision one.

Conclusion:

The preservation of the hip capsular ligament suppressed the increased LLD and FO difference. Level of Evidence II; Prognostic Study - Investigation of the Effect of a Patient Characteristic on the Outcome of a Disease .

Quantifying Muscle Forces and Joint Loading During Hip Exercises Performed With and Without an Elastic Resistance Band

An increase in hip joint contact forces (HJCFs) is one of the main contributing mechanical causes of hip joint pathologies, such as hip osteoarthritis, and its progression. The strengthening of the surrounding muscles of the joint is a way to increase joint stability, which results in the reduction of HJCF. Most of the exercise recommendations are based on expert opinions instead of evidence-based facts. This study aimed to quantify muscle forces and joint loading during rehabilitative exercises using an elastic resistance band (ERB). Hip exercise movements of 16 healthy volunteers were recorded using a three-dimensional motion capture system and two force plates. All exercises were performed without and with an ERB and two execution velocities. Hip joint kinematics, kinetics, muscle forces, and HJCF were calculated based on the musculoskeletal simulations in OpenSim. Time-normalized waveforms of the different exercise modalities were compared with each other and with reference values found during walking. The results showed that training with an ERB increases both target muscle forces and HJCF. Furthermore, the ERB reduced the hip joint range of motion during the exercises. The type of ERB used (soft vs. stiff ERB) and the execution velocity of the exercise had a minor impact on the peak muscle forces and HJCF. The velocity of exercise execution, however, had an influence on the total required muscle force. Performing hip exercises without an ERB resulted in similar or lower peak HJCF and lower muscle forces than those found during walking. Adding an ERB during hip exercises increased the peak muscle and HJCF but the values remained below those found during walking. Our workflow and findings can be used in conjunction with future studies to support exercise design.

Effect of the underlying cadaver data and patient-specific adaptation of the femur and pelvis on the prediction of the hip joint force estimated using static models

The prediction of the hip joint force (HJF) is a fundamental factor for the prevention of edge loading in total hip arthroplasty. Naturally, the loading of the liner of the acetabular component depends on the HJF acting on the artificial joint. In contrast to dynamic musculoskeletal models, static models for HJF prediction do not require motion analysis of the patient. However, patient-specific adaptability and validity of static models have to be scrutinized. In this study, a modular framework for HJF prediction using static models is introduced to compare the results of different cadaver templates that are the basis of most static and dynamic models, and different scaling laws for the patient-specific adaptation with in vivo HJF of ten patients for one-leg stance and level walking. The results revealed the significant effect of the underlying cadaver template used for the prediction of the HJF (p < 0.01). A higher degree of patient-specific scaling of the cadaver template often did not significantly reduce the prediction error. Three static models with the lowest prediction errors were compared to results of dynamic models from literature. The prediction error of the peak HJF of the static models (median absolute errors below 15% body weight in magnitude and below 5° in direction) was similar in magnitude and even smaller in direction compared to dynamic models. The necessary reduction of a load-based target zone for the prevention of edge loading due to the uncertainty of the HJF prediction has to be considered in the preoperative planning. The framework for HJF prediction is openly accessible at https://github.com/RWTHmediTEC/HipJointForceModel.

Influence of loading direction due to physical activity on proximal femoral growth tendency

Longitudinal bone growth is regulated by mechanical forces arising from physical activity, whose directions and magnitudes depend on activity kinematics and intensity. This study aims to investigate the influence of common physical activities on proximal femoral morphological tendency due to growth at the femoral head growth plate. A subject-specific femur model based on magnetic resonance images of one able-bodied 6-year old child was developed, and the directions of hip contact force were described as load samples at a constant magnitude. Finite element analysis was performed to predict growth rate and growth direction, and expected changes in neck-shaft angle and femoral anteversion were computed corresponding to circa 4 months of growth. For most loading conditions, neck-shaft angle and femoral anteversion decreased during growth, corresponding to the femur's natural course during normal growth. The largest reduction in neck-shaft angle and femoral anteversion was approximately 0.25° and 0.15°. Our results suggest that most common physical activities induce the expected morphological changes in normal growth in able-bodied children. Understanding the influence of contact forces during less common activities on proximal femoral development might provide improved guidelines and treatment planning for children who have or are at risk of developing a femoral deformity.

Real-Time Prediction of Joint Forces by Motion Capture and Machine Learning

Conventional biomechanical modelling approaches involve the solution of large systems of equations that encode the complex mathematical representation of human motion and skeletal structure. To improve stability and computational speed, being a common bottleneck in current approaches, we apply machine learning to train surrogate models and to predict in near real-time, previously calculated medial and lateral knee contact forces (KCFs) of 54 young and elderly participants during treadmill walking in a speed range of 3 to 7 km/h. Predictions are obtained by fusing optical motion capture and musculoskeletal modeling-derived kinematic and force variables, into regression models using artificial neural networks (ANNs) and support vector regression (SVR). Training schemes included either data from all subjects (LeaveTrialsOut) or only from a portion of them (LeaveSubjectsOut), in combination with inclusion of ground reaction forces (GRFs) in the dataset or not. Results identify ANNs as the best-performing predictor of KCFs, both in terms of Pearson R (0.89-0.98 for LeaveTrialsOut and 0.45-0.85 for LeaveSubjectsOut) and percentage normalized root mean square error (0.67-2.35 for LeaveTrialsOut and 1.6-5.39 for LeaveSubjectsOut). When GRFs were omitted from the dataset, no substantial decrease in prediction power of both models was observed. Our findings showcase the strength of ANNs to predict simultaneously multi-component KCF during walking at different speeds-even in the absence of GRFs-particularly applicable in real-time applications that make use of knee loading conditions to guide and treat patients.

In Silico-Enhanced Treatment and Rehabilitation Planning for Patients with Musculoskeletal Disorders: Can Musculoskeletal Modelling and Dynamic Simulations Really Impact Current Clinical Practice?

Over the past decades, the use of computational physics-based models representative of the musculoskeletal (MSK) system has become increasingly popular in many fields of clinically driven research, locomotor rehabilitation in particular. These models have been applied to various functional impairments given their ability to estimate parameters which cannot be readily measured in vivo but are of interest to clinicians. The use of MSK modelling and simulations allows analysis of relevant MSK biomarkers such as muscle and joint contact loading at a number of different stages in the clinical treatment pathway in order to benefit patient functional outcome. Applications of these methods include optimisation of rehabilitation programs, patient stratification, disease characterisation, surgical pre-planning, and assistive device and exoskeleton design and optimisation. This review provides an overview of current approaches, the components of standard MSK models, applications, limitations, and assumptions of these modelling and simulation methods, and finally proposes a future direction.

A multi-scale modelling framework combining musculoskeletal rigid-body simulations with adaptive finite element analyses, to evaluate the impact of femoral geometry on hip joint contact forces and femoral bone growth

Multi-scale simulations, combining muscle and joint contact force (JCF) from musculoskeletal simulations with adaptive mechanobiological finite element analysis, allow to estimate musculoskeletal loading and predict femoral growth in children. Generic linearly scaled musculoskeletal models are commonly used. This approach, however, neglects subject- and age-specific musculoskeletal geometry, e.g. femoral neck-shaft angle (NSA) and anteversion angle (AVA). This study aimed to evaluate the impact of proximal femoral geometry, i.e. altered NSA and AVA, on hip JCF and femoral growth simulations. Musculoskeletal models with NSA ranging from 120° to 150° and AVA ranging from 20° to 50° were created and used to calculate muscle and hip JCF based on the gait analysis data of a typically developing child. A finite element model of a paediatric femur was created from magnetic resonance images. The finite element model was morphed to the geometries of the different musculoskeletal models and used for mechanobiological finite element analysis to predict femoral growth trends. Our findings showed that hip JCF increase with increasing NSA and AVA. Furthermore, the orientation of the hip JCF followed the orientation of the femoral neck axis. Consequently, the osteogenic index, which is a function of cartilage stresses and defines the growth rate, barely changed with altered NSA and AVA. Nevertheless, growth predictions were sensitive to the femoral geometry due to changes in the predicted growth directions. Altered NSA had a bigger impact on the growth results than altered AVA. Growth simulations based on mechanobiological principles were in agreement with reported changes in paediatric populations.

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.

Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models

Musculoskeletal modelling is an important platform on which to study the biomechanics of morphological structures in vertebrates and is widely used in clinical, zoological and palaeontological fields. The popularity of this approach stems from the potential to non-invasively quantify biologically important but difficult-to-measure functional parameters. However, while it is known that model predictions are highly sensitive to input values, it is standard practice to build models by combining musculoskeletal data from different sources resulting in 'generic' models for a given species. At present, there are little quantitative data on how merging disparate anatomical data in models impacts the accuracy of these functional predictions. This issue is addressed herein by quantifying the accuracy of both subject-specific human limb models containing individualised muscle force-generating properties and models built using generic properties from both elderly and young individuals, relative to experimental muscle torques obtained from an isokinetic dynamometer. The results show that subject-specific models predict isokinetic muscle torques to a greater degree of accuracy than generic models at the ankle (root-mean-squared error - 7.9% vs. 49.3% in elderly anatomy-based models), knee (13.2% vs. 57.3%) and hip (21.9% vs. 32.8%). These results have important implications for the choice of musculoskeletal properties in future modelling studies, and the relatively high level of accuracy achieved in the subject-specific models suggests that such models can potentially address questions about inter-subject variations of muscle functions. However, despite relatively high levels of overall accuracy, models built using averaged generic muscle architecture data from young, healthy individuals may lack the resolution and accuracy required to study such differences between individuals, at least in certain circumstances. The results do not wholly discourage the continued use of averaged generic data in musculoskeletal modelling studies but do emphasise the need for to maximise the accuracy of input values if studying intra-species form-function relationships in the musculoskeletal system.

Predicting longitudinal changes in joint contact forces in a juvenile population: scaled generic versus subject-specific musculoskeletal models

Subject-specific musculoskeletal model use in clinical settings is limited due to development-associated time and effort burdens together with potential medical imaging unavailability. As an alternative, this study investigated consistency in estimating longitudinal changes in joint contact forces (JCF) between scaled generic and subject-specific models. For 11 children, joint kinematics and JCF were calculated using subject-specific and scaled generic models. JCF changes estimated by both models were strongly correlated for the hip and knee although JCF estimates varied between models. Findings suggest that within specified limits of accuracy, scaled generic models are sensitive enough to detect JCF changes consistent with subject-specific models.

Linking Joint Impairment and Gait Biomechanics in Patients with Juvenile Idiopathic Arthritis

Juvenile Idiopathic Arthritis (JIA) is a paediatric musculoskeletal disease of unknown aetiology, leading to walking alterations when the lower-limb joints are involved. Diagnosis of JIA is mostly clinical. Imaging can quantify impairments associated to inflammation and joint damage. However, treatment planning could be better supported using dynamic information, such as joint contact forces (JCFs). To this purpose, we used a musculoskeletal model to predict JCFs and investigate how JCFs varied as a result of joint impairment in eighteen children with JIA. Gait analysis data and magnetic resonance images (MRI) were used to develop patient-specific lower-limb musculoskeletal models, which were evaluated for operator-dependent variability (< 3.6°, 0.05 N kg-1 and 0.5 BW for joint angles, moments, and JCFs, respectively). Gait alterations and JCF patterns showed high between-subjects variability reflecting the pathology heterogeneity in the cohort. Higher joint impairment, assessed with MRI-based evaluation, was weakly associated to overall joint overloading. A stronger correlation was observed between impairment of one limb and overload of the contralateral limb, suggesting risky compensatory strategies being adopted, especially at the knee level. This suggests that knee overloading during gait might be a good predictor of disease progression and gait biomechanics should be used to inform treatment planning.

Restoring femoral offset and leg length; the potential of a short curved stem in total hip arthroplasty

Background

Total hip arthroplasty (THA) is a very successful procedure in orthopedics. Still polyethylene wear and gait deficits are limiting the clinical success.It is important to reconstruct leg length (LL) and femoral offset (FO) anatomically in order to have the best possible result of a THA. Gait deficits can arise due to leg length discrepancy as well as changes in the abductor moment arm. In THA, LL and FO are strongly determined by the orientation, size and geometry of the femoral stem.

Methods

This radio-anatomical study used the data of a prospective cases series of 112 patients who underwent 126 primary THAs and had completed a 1-year follow-up examination. FO and LL were compared between the conventional straight stem in vivo and a computed simulated implantation of a short curved stem, using the pre- and postoperative pelvic radiographs of the same patients.

Results

In this simulation of the short curved stem statistically significantly restored native FO (p = 0.010) and LL (p = 0.000) better, compared to the conventional straight stem.

Conclusions

Thus, the short curved stem restores FO and LL better, and could potentially prevent gait deficits.

Model of loadings acting on the femoral bone during gait

An evaluation of the model of loadings acting on the femoral bone during the whole gait cycle was the main aim of the paper. A computer simulation of the musculoskeletal system based on the gait data collected during gait was used to determine the muscle forces as well as the hip joint reaction. Kinematic parameters as well as the ground reaction force for ninety-nine healthy persons of both sexes (18-36 years old) who had no history of musculoskeletal disease were registered during normal gait with preferred speed and used as inputs for musculoskeletal modelling and numerical simulation with the use of the AnyBody software. Time waveforms of the values of force generated by 21 muscles having attachments on the femoral bone as well as the hip joint reaction force were obtained. Directions of particular forces were presented using a femoral coordinate system. Attachment points for all muscle forces were obtained on the basis of the unscaled standard model with the length of the femur equal to 0.41 m. The presented model of loadings acting on the femoral bone element can be useful for the biomechanical analysis of bone development and remodelling as well as for the optimisation of implant or bone stabilizer design and pre-clinical testing.

Numerical predictions of hip joint and muscle forces during daily activities: A comparison of musculoskeletal models

Musculoskeletal loading plays an important role in pre-clinical evaluations of hip implants, in particular, bone ingrowth and bone remodelling. Joint force estimation using musculoskeletal models evolved as a viable alternative to in vivo measurement owing to the development of computational resources. This study investigated the efficiencies of four eminent open-source musculoskeletal models in order to determine the model that predicts the most accurate values of hip joint reaction and muscle forces during daily activities. Seven daily living activities of slow walking, normal walking, fast walking, sitting down, standing up, stair down and stair up were simulated in OpenSim using inverse dynamics method. Model predictions of joint kinematics, kinetics and muscle activation patterns were compared with published results. The estimated values of hip joint reaction force were found to corroborate well with in vivo measurements for each activity. Although the estimated values of hip joint reaction force were within a satisfactory range, overestimation of hip joint reaction force (75% BW of measured value) was observed during the late stance phase of walking cycles for all the models. In case of stair up, stair down, standing up and sitting down activities, the error in estimated values of hip joint reaction force were within ~20% BW of the measured value. Based on the results of our study, the London Lower Extremity Model predicted the most accurate value of hip joint reaction force and therefore can be used for applied musculoskeletal loading conditions for numerical investigations on hip implants.

The effect of joint translation constraint on within-participant variability of kinematics and kinetics during running in cerebral palsy

BACKGROUND

Biomechanical data in cerebral palsy are inherently variable but no optimal model of translational joint constraint has been identified. The primary aim of this study was to determine which model of translational joint constraint resulted in the lowest within-participant variability of lower limb joint angles and moments. The secondary aim was to determine which model best distinguished known functional groups in Cerebral Palsy.

METHODS

Three models (three degrees of freedom, six degrees of freedom and six degrees of freedom with specified joint translation constraint) were applied to data from running trials of 40 children with cerebral palsy.

FINDINGS

Joint angle standard deviations were largest using the six degrees of freedom model and smallest using the constrained six degrees of freedom model (p < 0.050). For all joints in all planes of motion, joint moment standard deviations were largest using the six degrees of freedom model and smallest using the constrained six degrees of freedom model; standard deviations using the constrained model were smaller than the three degrees of freedom model by 10-30% of moment magnitude (0.01-0.03 Nm/kg; p < 0.001). The six degrees of freedom models distinguished functional subgroups with larger effect size than the three degrees of freedom model only for hip power generation in swing.

INTERPRETATION

A model with specified joint constraint minimized within-participant variability during running and was useful for detecting differences in functional capacity in cerebral palsy.

Musculoskeletal models with generic and subject-specific geometry estimate different joint biomechanics in dysplastic hips

Optimizing the geometric complexity of musculoskeletal models is important for reliable yet feasible estimation of joint biomechanics. This study investigated the effects of subject-specific model geometry on hip joint reaction forces (JRFs) and muscle forces in patients with developmental dysplasia of the hip (DDH) and healthy controls. For nine DDH and nine control subjects, three models were created with increasingly subject-specific pelvis geometry, hip joint center locations and muscle attachments. Hip JRFs and muscle forces during a gait cycle were compared among the models. For DDH subjects, resultant JRFs from highly specific models including subject-specific pelvis geometry, joint locations and muscle attachments were not significantly different compared to models using generic geometry in early stance, but were significantly higher in late stance (p = 0.03). Estimates from moderately specific models using CT-informed scaling of generic pelvis geometry were not significantly different from low specificity models using generic geometry scaled with skin markers. For controls, resultant JRFs in early stance from highly specific models were significantly lower than moderate and low specificity models (p ≤ 0.02) with no significant differences in late stance. Inter-model JRF differences were larger for DDH subjects than controls. Inter-model differences for JRF components and muscle forces were similar to resultant JRFs. Incorporating subject-specific pelvis geometry significantly affects JRF and muscle force estimates in both DDH and control groups, which may be especially important for reliable estimation of pathomechanics in dysplastic hips.

Subject-specific and group-based running pattern classification using a single wearable sensor

The objective of this study was to determine whether subject-specific or group-based models provided better classification accuracy to identify changes in biomechanical running gait patterns across different inclination conditions. The classification process was based on measurements from a single wearable sensor using a total of 41,780 strides from eleven recreational runners while running in real-world and uncontrolled environment. Biomechanical variables included pelvic drop, ground contact time, braking, vertical oscillation of pelvis, pelvic rotation, and cadence were recorded during running on three inclination grades: downhill, -2° to -7°; level, -0.2° to +0.2°; and uphill, +2° to +7°. An ensemble and non-linear machine learning algorithm, random forest (RF), was used to classify inclination condition and determine the importance of each of the biomechanical variables. Classification accuracy was determined for subject-specific and group-based RF models. The mean classification accuracy of all subject-specific RF models was 86.29%, while group-based classification accuracy was 76.17%. Braking was identified as the most important variable for all the runners using the group-based model and for most of the runners based on a subject-specific models. In addition, individual runners used different strategies across different inclination conditions and the ranked order of variable importance was unique for each runner. These results demonstrate that subject-specific models can better characterize changes in gait biomechanical patterns compared to a more traditional group-based approach.

Refining muscle geometry and wrapping in the TLEM 2 model for improved hip contact force prediction

Musculoskeletal models represent a powerful tool to gain knowledge on the internal forces acting at the joint level in a non-invasive way. However, these models can present some errors associated with the level of detail in their geometrical representation. For this reason, a thorough validation is necessary to prove the reliability of their predictions. This study documents the development of a generic musculoskeletal model and proposes a working logic and simulation techniques for identifying specific model features in need of refinement; as well as providing a quantitative validation for the prediction of hip contact forces (HCF). The model, implemented in the AnyBody Modeling System and based on the cadaveric dataset TLEM 2.0, was scaled to match the anthropometry of a patient fitted with an instrumented hip implant and to reproduce gait kinematics based on motion capture data. The relative contribution of individual muscle elements to the HCF and joint moments was analyzed to identify critical geometries, which were then compared to muscle magnetic resonance imaging (MRI) scans and, in case of inconsistencies, were modified to better match the volumetric scans. The predicted HCF showed good agreement with the overall trend and timing of the measured HCF from the instrumented prosthesis. The average root mean square error (RMSE), calculated for the total HCF was found to be 0.298*BW. Refining the geometries of the muscles thus identified reduced RMSE on HCF magnitudes by 17% (from 0.359*BW to 0.298*BW) over the whole gait cycle. The detailed study of individual muscle contributions to the HCF succeeded in identifying muscles with incorrect anatomy, which would have been difficult to intuitively identify otherwise. Despite a certain residual over-prediction of the final hip contact forces in the stance phase, a satisfactory level of geometrical accuracy of muscle paths has been achieved with the refinement of this model.

Sensitivity analysis of the estimated muscle forces during gait with respect to the musculoskeletal model parameters and dynamic simulation techniques

The purpose of the current study was to investigate the robustness of dynamic simulation results in the presence of uncertainties resulting from application of a scaled-generic musculoskeletal model instead of a subject-specific model as well as the effect of the choice of simulation method on the obtained muscle forces. The performed sensitivity analysis consisted of the following multibody parameter modifications: maximum isometric muscle forces, number of muscles, the hip joint centre location, segment masses as well as different dynamic simulation methods, namely static optimization with three different criteria and a computed muscle control algorithm (hybrid approach combining forward and inverse dynamics). Twenty-four different models and fifty-five resultant dynamic simulation data sets were analysed. The effects of model perturbation on the magnitude and profile of muscle forces were compared. It has been shown that estimated muscle forces are very sensitive to model parameters. The greatest impact was observed in the case of the force magnitude of the muscles generating high forces during gait (regardless of the modification introduced). However, the force profiles of those muscles were preserved. Relatively large differences in muscle forces were observed for different simulation techniques, which included both magnitude and profile of muscle forces. Personalization of model parameters would affect the resultant muscle forces and seems to be necessary to improve general accuracy of the estimated parameters. However, personalization alone will not ensure high accuracy due to the still unresolved muscle force sharing problem.

Stem anteversion mismatch to the anatomical anteversion causes loss of periprosthetic bone density after THA

The short tapered-wedge stem is popular worldwide because it potentially preserves more bone stock during total hip arthroplasty (THA). However, stem version mismatch may affect physiological stress distribution. In this study, we analyzed the correlations between periprosthetic bone mineral density (BMD) changes and anteversion mismatch in patients who underwent THA using a short tapered-wedge stem. The study included 44 patients (44 joints) who underwent THA with a Tri-Lock stem. At baseline and at 6 and 24 months postoperatively, the BMDs in the seven Gruen zones were evaluated using dual-energy X-ray absorptiometry. BMD changes and stem alignment, that is, anteversion and stem anteversion mismatch to the anatomical canal anteversion, were analyzed. Significant negative correlations were found between BMD changes and absolute anteversion error in Gruen zones 1 and 7 at 6 and 24 months postoperatively (zone 1, 6M; RR= -0.48, p < 0.001) (zone 7, 6M; RR= -0.46, p = 0.002) (zone 1, 24M; RR= -0.47, p = 0.001) (zone 7, 24M; RR= -0.40, p = 0.007). We further demonstrated that excessive stem anteversion mismatch to the anatomical canal anteversion causes stem point contact with the cortical bone in the distal portion and affected proximal periprosthetic BMD loss after THA. We recommend that the native anatomical anteversion angle should be used as a reference for inserting the tapered-wedge stems.

Advancing quantitative techniques to improve understanding of the skeletal structure-function relationship

Although all functional movement arises from the interplay between the neurological, skeletal, and muscular systems, it is the skeletal system that forms the basic framework for functional movement. Central to understanding human neuromuscular development, along with the genesis of musculoskeletal pathologies, is quantifying how the human skeletal system adapts and mal-adapts to its mechanical environment. Advancing this understanding is hampered by an inability to directly and non-invasively measure in vivo strains, stresses, and forces on bone. Thus, we traditionally have turned to animal models to garner such information. These models enable direct in vivo measures that are not available for human subjects, providing information in regards to both skeletal adaptation and the interplay between the skeletal and muscular systems. Recently, there has been an explosion of new imaging and modeling techniques providing non-invasive, in vivo measures and estimates of skeletal form and function that have long been missing. Combining multiple modalities and techniques has proven to be one of our most valuable resources in enhancing our understanding of the form-function relationship of the human skeletal, muscular, and neurological systems. Thus, to continue advancing our knowledge of the structural-functional relationship, validation of current tools is needed, while development is required to limit the deficiencies in these tools and develop new ones.

Sensitivity of a juvenile subject-specific musculoskeletal model of the ankle joint to the variability of operator-dependent input

Subject-specific musculoskeletal modelling is especially useful in the study of juvenile and pathological subjects. However, such methodologies typically require a human operator to identify key landmarks from medical imaging data and are thus affected by unavoidable variability in the parameters defined and subsequent model predictions. The aim of this study was to thus quantify the inter- and intra-operator repeatability of a subject-specific modelling methodology developed for the analysis of subjects with juvenile idiopathic arthritis. Three operators each created subject-specific musculoskeletal foot and ankle models via palpation of bony landmarks, adjustment of geometrical muscle points and definition of joint coordinate systems. These models were then fused to a generic Arnold lower limb model for each of three modelled patients. The repeatability of each modelling operation was found to be comparable to those previously reported for the modelling of healthy, adult subjects. However, the inter-operator repeatability of muscle point definition was significantly greater than intra-operator repeatability (p < 0.05) and predicted ankle joint contact forces ranged by up to 24% and 10% of the peak force for the inter- and intra-operator analyses, respectively. Similarly, the maximum inter- and intra-operator variations in muscle force output were 64% and 23% of peak force, respectively. Our results suggest that subject-specific modelling is operator dependent at the foot and ankle, with the definition of muscle geometry the most significant source of output uncertainty. The development of automated procedures to prevent the misplacement of crucial muscle points should therefore be considered a particular priority for those developing subject-specific models.

Incorporation of CT-based measurements of trunk anatomy into subject-specific musculoskeletal models of the spine influences vertebral loading predictions

We created subject-specific musculoskeletal models of the thoracolumbar spine by incorporating spine curvature and muscle morphology measurements from computed tomography (CT) scans to determine the degree to which vertebral compressive and shear loading estimates are sensitive to variations in trunk anatomy. We measured spine curvature and trunk muscle morphology using spine CT scans of 125 men, and then created four different thoracolumbar spine models for each person: (i) height and weight adjusted (Ht/Wt models); (ii) height, weight, and spine curvature adjusted (+C models); (iii) height, weight, and muscle morphology adjusted (+M models); and (iv) height, weight, spine curvature, and muscle morphology adjusted (+CM models). We determined vertebral compressive and shear loading at three regions of the spine (T8, T12, and L3) for four different activities. Vertebral compressive loads predicted by the subject-specific CT-based musculoskeletal models were between 54% lower to 45% higher from those estimated using musculoskeletal models adjusted only for subject height and weight. The impact of subject-specific information on vertebral loading estimates varied with the activity and spinal region. Vertebral loading estimates were more sensitive to incorporation of subject-specific spinal curvature than subject-specific muscle morphology. Our results indicate that individual variations in spine curvature and trunk muscle morphology can have a major impact on estimated vertebral compressive and shear loads, and thus should be accounted for when estimating subject-specific vertebral loading. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2164-2173, 2017.

Effects of Gait Speed of Femoroacetabular Joint Forces

Alterations in hip joint loading have been associated with diseases such as arthritis and osteoporosis. Understanding the relationship between gait speed and hip joint loading in healthy hips may illuminate changes in gait mechanics as walking speed deviates from preferred. The purpose of this study was to quantify hip joint loading during the gait cycle and identify differences with varying speed using musculoskeletal modeling. Ten, healthy, physically active individuals performed walking trials at their preferred speed, 10% faster, and 10% slower. Kinematic, kinetic, and electromyographic data were collected and used to estimate hip joint force via a musculoskeletal model. Vertical ground reaction forces, hip joint force planar components, and the resultant hip joint force were compared between speeds. There were significant increases in vertical ground reaction forces and hip joint forces as walking speed increased. Furthermore, the musculoskeletal modeling approach employed yielded hip joint forces that were comparable to previous simulation studies and in vivo measurements and was able to detect changes in hip loading due to small deviations in gait speed. Applying this approach to pathological and aging populations could identify specific areas within the gait cycle where force discrepancies may occur which could help focus management of care.

RIGID MUSCULOSKELETAL MODELS OF THE HUMAN BODY SYSTEMS: A REVIEW

Advancing the knowledge of the biomechanics of the human body is essential to improve the clinical decision-makings of musculoskeletal disorders in the framework of in silico medicine. An impressive number of research projects focused on the development of rigid-body musculoskeletal models have been conducted over the world thanks to the new research directives. However, the application of these models in clinical practices remains a challenging issue. The objective of this review paper was to present the most current rigid-body musculoskeletal models of the human body systems and to analyze their trends and weaknesses for clinical applications. Then, recommendations were proposed for future researches toward fully clinical decision support. A systematic review process was performed. Well-selected studies related to the most current rigid-body 3D musculoskeletal models for each body system component (jaw, cervical spine, upper limbs, lumbar spine, and lower limbs) were summarized and explored. Trends in rigid musculoskeletal modeling are highlighted as personalization, new imaging techniques for specific joint kinematics, and computational efficiency. Weaknesses are highlighted as modeling assumptions, use of generic model, lack of modeling consensus, model validation, and parameter and model uncertainties. Future directions related to joint and muscle modeling, neuro-musculoskeletal modeling, model validation, data and model uncertainty quantification are recommended.

Influence of the Level of Muscular Redundancy on the Validity of a Musculoskeletal Model

While recent literature has clearly demonstrated that an extensive personalization of the musculoskeletal models was necessary to reach high accuracy, several components of the generic models may be further investigated before defining subject-specific parameters. Among others, the choice in muscular geometry and thus the level of muscular redundancy in the model may have a noticeable influence on the predicted musculotendon and joint contact forces. In this context, the aim of this study was to investigate if the level of muscular redundancy can contribute or not to reduce inaccuracies in tibiofemoral contact forces predictions. For that, the dataset disseminated through the Sixth Grand Challenge Competition to Predict In Vivo Knee Loads was applied to a versatile 3D lower limb musculoskeletal model in which two muscular geometries (i.e., two different levels of muscular redundancy) were implemented. This dataset provides tibiofemoral implant measurements for both medial and lateral compartments and thus allows evaluation of the validity of the model predictions. The results suggest that an increase of the level of muscular redundancy corresponds to a better accuracy of total tibiofemoral contact force whatever the gait pattern investigated. However, the medial and lateral contact forces ratio and accuracy were not necessarily improved when increasing the level of muscular redundancy and may thus be attributed to other parameters such as the location of contact points. To conclude, the muscular geometry, among other components of the generic model, has a noticeable impact on joint contact forces predictions and may thus be correctly chosen even before trying to personalize the model.

Compressive and shear hip joint contact forces are affected by pediatric obesity during walking

Obese children exhibit altered gait mechanics compared to healthy-weight children and have an increased prevalence of hip pain and pathology. This study sought to determine the relationships between body mass and compressive and shear hip joint contact forces during walking. Kinematic and kinetic data were collected during treadmill walking at 1ms(-1) in 10 obese and 10 healthy-weight 8-12 year-olds. We estimated body composition, segment masses, lower-extremity alignment, and femoral neck angle via radiographic images, created personalized musculoskeletal models in OpenSim, and computed muscle forces and hip joint contact forces. Hip extension at mid-stance was 9° less, on average, in the obese children (p<0.001). Hip abduction, knee flexion, and body-weight normalized peak hip moments were similar between groups. Normalized to body-weight, peak contact forces were similar at the first peak and slightly lower at the second peak between the obese and healthy-weight participants. Total body mass explained a greater proportion of contact force variance compared to lean body mass in the compressive (r(2)=0.89) and vertical shear (perpendicular to the physis acting superior-to-inferior) (r(2)=0.84) directions; lean body mass explained a greater proportion in the posterior shear direction (r(2)=0.54). Stance-average contact forces in the compressive and vertical shear directions increased by 41N and 48N, respectively, for every kilogram of body mass. Age explained less than 27% of the hip loading variance. No effect of sex was found. The proportionality between hip loads and body-weight may be implicated in an obese child׳s increased risk of hip pain and pathology.

Identifying clinically meaningful benchmarks for gait improvement after total hip arthroplasty

There are no established benchmarks for gait mechanics after total hip arthroplasty (THA). This study sought to identify minimum clinically important postoperative (MCIP) or minimum clinically important improvement (MCII) values for self-selected walking speed, sagittal plane dynamic hip range of motion (HROM) (peak flexion-peak extension) and peak hip adduction moments measured during quantitative gait analysis. Preoperative and 1-year postoperative data collected during quantitative gait analysis, along with Harris Hip Scores (HHS), for 145 subjects were collected from a motion analysis data repository. The MCIP (or MCII) was defined as the 75th percentile mark on a plot of the cumulative percent of subjects with HHS ≥ 80 versus the postoperative value (or change) in the respective variable. 95% confidence intervals (CI) were calculated. Logistic regression was used to test the association of age, sex, BMI, and preoperative HHS with benchmarks. The MCIP of speed was 1.34 m/s (95%CI 1.30, 1.37); MCII was 0.32 (0.30, 0.35) m/s. The HROM MCIP was 30.0° (29.4°, 30.7°); MCII was 13.3° (12.1°, 14.8°). The adduction moment MCIP was 4.2% Body Weight × Height (4.0, 4.4); MCII was 0.87 (0.57, 1.17) % Body Weight × Height. Women were more likely to achieve MCII for HROM and MCIP for adduction moment (ORs 2.4-11.6, p ≤ 0.031). Lower BMI predicted HROM and adduction moment MCIPs (ORs 0.85-0.88, p ≤ 0.015). Lower preoperative HHS predicted speed, HROM and adduction moment MCIIs (ORs 0.95-0.97, p ≤ 0.012). With further validation, clinically-relevant gait benchmarks can enhance efforts to improve THA outcomes.

A Novel Approach for Dynamic Testing of Total Hip Dislocation under Physiological Conditions

Constant high rates of dislocation-related complications of total hip replacements (THRs) show that contributing factors like implant position and design, soft tissue condition and dynamics of physiological motions have not yet been fully understood. As in vivo measurements of excessive motions are not possible due to ethical objections, a comprehensive approach is proposed which is capable of testing THR stability under dynamic, reproducible and physiological conditions. The approach is based on a hardware-in-the-loop (HiL) simulation where a robotic physical setup interacts with a computational musculoskeletal model based on inverse dynamics. A major objective of this work was the validation of the HiL test system against in vivo data derived from patients with instrumented THRs. Moreover, the impact of certain test conditions, such as joint lubrication, implant position, load level in terms of body mass and removal of muscle structures, was evaluated within several HiL simulations. The outcomes for a normal sitting down and standing up maneuver revealed good agreement in trend and magnitude compared with in vivo measured hip joint forces. For a deep maneuver with femoral adduction, lubrication was shown to cause less friction torques than under dry conditions. Similarly, it could be demonstrated that less cup anteversion and inclination lead to earlier impingement in flexion motion including pelvic tilt for selected combinations of cup and stem positions. Reducing body mass did not influence impingement-free range of motion and dislocation behavior; however, higher resisting torques were observed under higher loads. Muscle removal emulating a posterior surgical approach indicated alterations in THR loading and the instability process in contrast to a reference case with intact musculature. Based on the presented data, it can be concluded that the HiL test system is able to reproduce comparable joint dynamics as present in THR patients.

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction.

A Patient-Specific Foot Model for the Estimate of Ankle Joint Forces in Patients with Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the leading cause of childhood disability from a musculoskeletal disorder. It generally affects large joints such as the knee and the ankle, often causing structural damage. Different factors contribute to the damage onset, including altered joint loading and other mechanical factors, associated with pain and inflammation. The prediction of patients’ joint loading can hence be a valuable tool in understanding the disease mechanisms involved in structural damage progression. A number of lower-limb musculoskeletal models have been proposed to analyse the hip and knee joints, but juvenile models of the foot are still lacking. This paper presents a modelling pipeline that allows the creation of juvenile patient-specific models starting from lower limb kinematics and foot and ankle MRI data. This pipeline has been applied to data from three children with JIA and the importance of patient-specific parameters and modelling assumptions has been tested in a sensitivity analysis focused on the variation of the joint reaction forces. This analysis highlighted the criticality of patient-specific definition of the ankle joint axes and location of the Achilles tendon insertions. Patient-specific detection of the Tibialis Anterior, Tibialis Posterior, and Peroneus Longus origins and insertions were also shown to be important.