Simultaneous prediction of muscle and contact forces in the knee during gait

Finite element analysis of meniscus contact mechanical behavior based on kinematic simulation of abnormal gait

The meniscus plays a crucial role in the proper functioning of the knee joint, and when it becomes damaged, partial removal or replacement is necessary to restore proper function. Understanding the stress and deformation of the meniscus during various movements is essential for developing effective materials for meniscus repair. However, accurately estimating the contact mechanics of the knee joint can be challenging due to its complex shape and the dynamic changes it undergoes during movement. To address this issue, the open-source software SCONE can be used to establish a kinematics model that monitors the different states of the knee joint during human motion and obtains relevant gait kinematics data. To evaluate the stress and deformation of the meniscus during normal human movement, values of different states in the movement gait can be selected for finite element analysis (FEA) of the knee joint. This analysis enables researchers to assess changes in the meniscus. To evaluate meniscus damage, it is necessary to obtain changes in its mechanical behavior during abnormal movements. This information can serve as a reference for designing and optimizing the mechanical performance of materials used in meniscus repair and replacement.

Smartphone videos-driven musculoskeletal multibody dynamics modelling workflow to estimate the lower limb joint contact forces and ground reaction forces

The estimation of joint contact forces in musculoskeletal multibody dynamics models typically requires the use of expensive and time-consuming technologies, such as reflective marker-based motion capture (Mocap) system. In this study, we aim to propose a more accessible and cost-effective solution that utilizes the dual smartphone videos (SPV)-driven musculoskeletal multibody dynamics modeling workflow to estimate the lower limb mechanics. Twelve participants were recruited to collect marker trajectory data, force plate data, and motion videos during walking and running. The smartphone videos were initially analyzed using the OpenCap platform to identify key joint points and anatomical markers. The markers were used as inputs for the musculoskeletal multibody dynamics model to calculate the lower limb joint kinematics, joint contact forces, and ground reaction forces, which were then evaluated by the Mocap-based workflow. The root mean square error (RMSE), mean absolute deviation (MAD), and Pearson correlation coefficient (ρ) were adopted to evaluate the results. Excellent or strong Pearson correlations were observed in most lower limb joint angles (ρ = 0.74 ~ 0.94). The averaged MADs and RMSEs for the joint angles were 1.93 ~ 6.56° and 2.14 ~ 7.08°, respectively. Excellent or strong Pearson correlations were observed in most lower limb joint contact forces and ground reaction forces (ρ = 0.78 ~ 0.92). The averaged MADs and RMSEs for the joint lower limb joint contact forces were 0.18 ~ 1.07 bodyweight (BW) and 0.28 ~ 1.32 BW, respectively. Overall, the proposed smartphone video-driven musculoskeletal multibody dynamics simulation workflow demonstrated reliable accuracy in predicting lower limb mechanics and ground reaction forces, which has the potential to expedite gait dynamics analysis in a clinical setting.

Development of a three-dimensional muscle-driven lower limb model developed using an improved CFD-FE method

Analysis of the musculoskeletal movements (gait analysis) is needed in many scenarios. The in vivo method has some difficulties. For example, recruiting human subjects for the gait analysis is challenging due to many issues. In addition, when plenty of subjects are required, the follow-up experiments take a long period and the dropout of subjects always occurs. An efficient and reliable in silico simulation platform for gait analysis has been desired for a long time. Therefore, a technique using three-dimensional (3D) muscle modeling to drive the 3D musculoskeletal model was developed and the application of the technique in the simulation of lower limb movements was demonstrated. A finite element model of the lower limb with anatomically high fidelity was developed from the MRI data, where the main muscles, the bones, the subcutaneous tissues, and the skin were reconstructed. To simulate the active behavior of 3D muscles, an active, fiber-reinforced hyperelastic muscle model was developed using the user-defined material (VUMAT) model. Two typical movements, that is, hip abduction and knee lifting, were simulated by activating the responsible muscles. The results show that it is reasonable to use the improved CFD-FE method proposed in the present study to simulate the active contraction of the muscle, and it is feasible to simulate the movements by activating the relevant muscles. The results from the present technique closely match the physiological scenario and thus the technique developed has a great potential to be used in the in silico human simulation platform for many purposes.

Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

Can a Musculoskeletal Model Adapted to Knee Implant Geometry Improve Prediction of 3D Contact Forces and Moments?

Tibiofemoral contact loads are crucial parameters in the onset and progression of osteoarthrosis. While contact loads are frequently estimated from musculoskeletal models, their customization is often limited to scaling musculoskeletal geometry or adapting muscle lines. Moreover, studies have usually focused on superior-inferior contact force without investigating three-dimensional contact loads. Using experimental data from six patients with instrumented total knee arthroplasty (TKA), this study customized a lower limb musculoskeletal model to consider the positioning and the geometry of the implant at knee level. Static optimization was performed to estimate tibiofemoral contact forces and contact moments as well as musculotendinous forces. Predictions from both a generic and a customized model were compared to the instrumented implant measurements. Both models accurately predict superior-inferior (SI) force and abduction-adduction (AA) moment. Notably, the customization improves prediction of medial-lateral (ML) force and flexion-extension (FE) moments. However, there is subject-dependent variability in the prediction of anterior-posterior (AP) force. The customized models presented here predict loads on all joint axes and in most cases improve prediction. Unexpectedly, this improvement was more limited for patients with more rotated implants, suggesting a need for further model adaptations such as muscle wrapping or redefinition of hip and ankle joint centers and axes.

Visual programming for accessible interactive musculoskeletal models

Objective

Musculoskeletal modeling and simulation are powerful research and education tools in engineering, neuroscience, and rehabilitation. Interactive musculoskeletal models (IMMs) can be controlled by muscle activity recorded with electromyography (EMG). IMMs are typically coded using textual programming languages that present barriers to understanding for non-experts. The goal of this project was to use a visual programming language (Simulink) to create and test an IMM that is accessible to non-specialists for research and educational purposes.

Results

The developed IMM allows users to practice a goal-directed task with different control modes (keyboard, mouse, and EMG) and actuator types (muscle model, force generator, and torque generator). Example data were collected using both keyboard and EMG control. One male participant in his early 40’s performed a goal-directed task for four sequential trials using each control mode. For EMG control, the participant used a low-cost EMG system with consumer-grade EMG sensors and an Arduino microprocessor. The participant successfully performed the task with both control modes, but the inability to grade muscle model excitation and co-activate antagonist muscles limited performance with keyboard control. The IMM developed for this project serves as a foundation that can be further tailored to specific research and education needs.

Walking Pole Gait to Reduce Joint Loading post Total Knee Athroplasty: Musculoskeletal modeling Approach

Excessive knee contact loading is precursor to osteoarthritis and related knee ailment leading to knee athroplasty. Reducing contact loading through gait modifications using assisted pole walking offers noninvasive process of medial load offloading at knee joint. In this paper, we evaluate the efficacy of different configuration of pole walking for reducing contact force at the knee joint through musculoskeletal (MSK) modeling. We have developed a musculoskeletal model for a subject with knee athroplasty utilizing in-vivo implant data and computed tibio-femoral contact force for different pole walking conditions to evaluate the best possible configuration for guiding rehabilitation, correlated with different gait phases. Effect of gait speed variation on knee contact force, hip joint dynamics and muscle forces are simulated using the developed MSK model. Results indicate some interesting trend of load reduction, dependent on loading phases pertaining to different pole configuration. Insights gained from the simulation can aid in designing personalized rehabilitation therapy for subjects suffering from Osteoarthritis.

Development and Functional Testing of An Unloading Concept for Knee Osteoarthritis Patients: A Pilot Study

This paper presents a knee brace design that applies an extension moment to unload the muscles in stance phase during gait, and thereby the knee, as alternative to conventional valgus braces for knee osteoarthritis patients. The concept was tested on one healthy subject during normal gait with a prototype, which was designed to activate and deactivate in order to apply the extension moment in the stance phase only and hereby avoid any interference during the swing phase. Electromyography measurements and musculoskeletal models were used to evaluate the brace effects on muscle activation and knee compressive forces respectively. Simulations predicted an ideal reduction of up to 36%, whereas experimental tests revealed a reduction of up to 24% with the current prototype. The prototype brace also reduced the knee joint force impulse up to 9% and EMG peak signal of the vasti muscles with up to 19%. Due to these reductions on a healthy subject, this bracing approach seem promising for reducing knee loads during normal gait. However, further clinical experiments on knee osteoarthritis patients are required to evaluate the effect on both pain and disease progression.

Knee loading in OA subjects is correlated to flexion and adduction moments and to contact point locations

This study evaluated the association of contact point locations with the knee medial and lateral contact force (F_med, F_lat) alterations in OA and healthy subjects. A musculoskeletal model of the lower limb with subject-specific tibiofemoral contact point trajectories was used to estimate the F_med and F_lat in ten healthy and twelve OA subjects during treadmill gait. Regression analyses were performed to evaluate the correlation of the contact point locations, knee adduction moment (KAM), knee flexion moment (KFM), frontal plane alignment, and gait speed with the F_med and F_lat. Medial contact point locations in the medial–lateral direction showed a poor correlation with the F_med in OA (R² = 0.13, p = 0.01) and healthy (R² = 0.24, p = 0.001) subjects. Anterior–posterior location of the contact points also showed a poor correlation with the F_med of OA subjects (R² = 0.32, p < 0.001). Across all subjects, KAM and KFM remained the best predictors of the F_med and F_lat, respectively (R² between 0.62 and 0.69). Results suggest different mechanisms of contact force distribution in OA joints. The variations in the location of the contact points participate partially to explains the F_med variations in OA subjects together with the KFM and KAM.

ReadySim: A computational framework for building explicit finite element musculoskeletal simulations directly from motion laboratory data

Musculoskeletal modeling allows researchers insight into joint mechanics which might not otherwise be obtainable through in vivo or in vitro studies. Common musculoskeletal modeling techniques involve rigid body dynamics software which often employ simplified joint representations. These representations have proven useful but are limited in performing single-framework deformable analyzes in structures of interest. Musculoskeletal finite element (MSFE) analysis allows for representation of structures in sufficient detail to obtain accurate solutions of the internal stresses and strains including complex contact conditions and material representations. Studies which performed muscle force optimization directly in a finite element framework were often limited in complexity to minimize computational time. Recent advances in computational efficiency and control schemes for muscle force prediction have made these solutions more practical. Yet, the formulation of subject-specific simulations remains a challenging problem. The objectives of this work were to develop an open-source computational framework to build and run simulations which (a) scale the size of MSFE models and efficiently estimate (b) joint kinematics and (c) muscle forces from human motion data collected in a typical gait laboratory. A computational framework was built using MATLAB and Python to interface with model input and output files. The software uses laboratory marker data to scale model segment lengths and estimate joint kinematics. Concurrent muscle force and tissue strain estimations are performed based on the estimated kinematics and ground reaction forces. This software will improve the usability and consistency of single-framework MSFE simulations. Both software and template model are made freely available on SimTK.Novelty Statement Single framework musculoskeletal modeling directly in a finite element environment for muscle force estimation and tissue strain analysis. Open dissemination of unilateral musculoskeletal finite element model and software used in manuscript.

A one-dimensional collagen-based biomechanical model of passive soft tissue with viscoelasticity and failure

INTRODUCTION

Strains and sprains of soft tissues, including tendons and ligaments, are frequently occurring injuries. Musculoskeletal models show great promise in prediction and prevention of these injuries. However, these models rarely account for the viscoelastic properties of ligaments and tendons, much less their failure properties. The purpose of this project was to develop, simplify, and analyze a collagen-distribution model to address these limitations.

MODEL DEVELOPMENT

A distribution-moment approximation was applied to an existing partial differential equation model to reduce its computational complexity. The resulting model was equipped with a Voigt model in series, which endowed it with viscoelastic properties in addition to failure properties.

RESULTS

The model was able to reproduce the characteristic toe, linear, and failure regions ubiquitous throughout in-vitro tests on tissue specimens. In addition, it was able to reproduce a tri-phasic creep test consisting of an initial deformation, a steady-state, and failure. Stress-relaxation and hysteresis were also reproducible by the model.

DISCUSSION AND CONCLUSION

The ability to reproduce so many characteristics of biological tissues suggests more bio-fidelity was achieved by the reduced model was other currently available models. Future work to further improve its bio-fidelity is proposed for specific tendons and ligaments.

Effects of working posture and roof slope on activation of lower limb muscles during shingle installation

Awkward and extreme kneeling during roofing generates high muscular tension which can lead to knee musculoskeletal disorders (MSDs) among roofers. However, the combined impact of roof slope and kneeling posture on the activation of the knee postural muscles and their association to potential knee MSD risks among roofers have not been studied. The current study evaluated the effects of kneeling posture and roof slope on the activation of major knee postural muscles during shingle installation via a laboratory assessment. Maximum normalized electromyography (EMG) data were collected from knee flexor and extensor muscles of seven subjects, who mimicked the shingle installation process on a slope-configurable wooden platform. The results revealed a significant increase in knee muscle activation during simulated shingle installation on sloped rooftops. Given the fact that increased muscle activation of knee postural muscles has been associated with knee MSDs, roof slope and awkward kneeling posture can be considered as potential knee MSD risk factors. Practitioner Summary: This study demonstrated significant effects of roof slope and kneeling posture on the peak activation of knee postural muscles. The findings of this study suggested that residential roofers could be exposed to a greater risk of developing knee MSDs with the increase of roof slope during shingle installation due to increased muscle loading. Abbreviations: MSDs: musculoskeletal disorders; EMG: electromyography; ANOVA: analysis of variance; MNMA: maximum normalized muscle activation; RF: rectus femoris; VL: vastus lateralis; VM: vastus medialis; BF: biceps femoris; S: semitendinosus.

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge

Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.

Minimising tibial fracture after unicompartmental knee replacement: A probabilistic finite element study

BACKGROUND

Periprosthetic tibial fracture after unicompartmental knee replacement is a challenging post-operative complication. Patients have an increased risk of mortality after fracture, the majority undergo further surgery, and the revision operations are less successful. Inappropriate surgical technique increases the risk of fracture, but it is unclear which technical aspects of the surgery are most problematic and no research has been performed on how surgical factors interact.

METHODS

Firstly, this study quantified the typical variance in surgical cuts made during unicompartmental knee replacement (determined from bones prepared by surgeons during an instructional course). Secondly, these measured distributions were used to create a probabilistic finite element model of the tibia after replacement. A thousand finite element models were created using the Monte Carlo method, representing 1000 virtual operations, and the risk of tibial fracture was assessed.

FINDINGS

Multivariate linear regression of the results showed that excessive resection depth and making the vertical cut too deep posteriorly increased the risk of fracture. These two parameters also had high variability in the prepared synthetic bones. The regression equation calculated the risk of fracture from three cut parameters (resection depth, vertical and horizonal posterior cuts) and fit the model results with 90% correlation.

INTERPRETATION

This study introduces for the first time the application of a probabilistic approach to predict the aetiology of fracture after unicompartmental knee replacement, providing unique insight into the relative importance of surgical saw cut variations. Targeted changes to operative technique can now be considered to seek to reduce the risk of periprosthetic fracture.

Muscle recruitment strategies can reduce joint loading during level walking

Joint inflammation, with consequent cartilage damage and pain, typically reduces functionality and affects activities of daily life in a variety of musculoskeletal diseases. Since mechanical loading is an important determinant of the disease process, a possible conservative treatment is the unloading of joints. In principle, a neuromuscular rehabilitation program aimed to promote alternative muscle recruitments could reduce the loads on the lower-limb joints during walking. The extent of joint load reduction one could expect from this approach remains unknown. Furthermore, assuming significant reductions of the load on the affected joint can be achieved, it is unclear whether, and to what extent, the other joints will be overloaded. Using subject-specific musculoskeletal models of four different participants, we computed the muscle recruitment strategies that minimised the hip, knee and ankle contact force, and predicted the contact forces such strategies induced at the other joints. Significant reductions of the peak force and impulse at the knee and hip were obtained, while only a minimal effect was found at the ankle joint. Adversely, the peak force and the impulse in non-targeted joints increased when aiming to minimize the load in an adjacent joint. These results confirm the potential of alternative muscle recruitment strategies to reduce the loading at the knee and the hip, but not at the ankle. Therefore, neuromuscular rehabilitation can be targeted to reduce the loading at affected joints but must be considered carefully in patients with multiple joints affected due to the potential adverse effects in non-targeted joints.

Implementation of controlling strategy in a biomechanical lower limb model with active muscles for coupling multibody dynamics and finite element analysis

Computational biomechanics for human body modeling has generally been categorized into two separated domains: finite element analysis and multibody dynamics. Combining the advantages of both domains is necessary when tissue stress and physical body motion are both of interest. However, the method for this topic is still in exploration. The aim of this study is to implement unique controlling strategies in finite element model for simultaneously simulating musculoskeletal body dynamics and in vivo stress inside human tissues. A finite element lower limb model with 3D active muscles was selected for the implementation of controlling strategies, which was further validated against in-vivo human motion experiments. A unique feedback control strategy that couples together a basic Proportion-Integration-Differentiation (PID) controller and generic active signals from Computed Muscle Control (CMC) method of the musculoskeletal model or normalized EMG singles was proposed and applied in the present model. The results show that the new proposed controlling strategy show a good correlation with experimental test data of the normal gait considering joint kinematics, while stress distribution of local lower limb tissue can be also detected in real-time with lower limb motion. In summary, the present work is the first step for the application of active controlling strategy in the finite element model for concurrent simulation of both body dynamics and tissue stress. In the future, the present method can be further developed to apply it in various fields for human biomechanical analysis to monitor local stress and strain distribution by simultaneously simulating human locomotion.

Sensitivity of medial-lateral load sharing to changes in adduction moments or angles in an asymptomatic knee joint model during gait

BACKGROUND

Osteoarthritis (OA) of the knee joint is a common disease accompanied by pain and impaired mobility. Despite some recent concerns on the lack of correlation between the medial load and the knee adduction moment (KAM), KAM is routinely considered as a surrogate measure of medial load and hence a marker where its reduction is the main focus of preventive and treatment interventions.

RESEARCH QUESTION

Determine the relative sensitivity of the tibiofemoral medial-lateral contact load partitioning to changes in the knee adduction angle (KAA) versus KAM.

METHODS

Using a lower extremity hybrid musculoskeletal (MS) model driven by gait kinematics and kinetics, we compute here in asymptomatic subjects the sensitivity of the knee joint biomechanical response (muscle and ligament forces) in general and medial/lateral load partitioning in particular to the relative changes in the reported KAA versus changes in reported KAM (both by one standard deviation).

RESULTS

As KAA increased (at constant KAM), so did the passive moment resistance of the knee joint which as a result and at all stance periods substantially reduced forces in lateral hamstrings while increasing those in medial hamstrings. At 25% and 75% stance as two highly loaded periods of gait, the drop in KAA (from + SD to -SD while at constant KAM) drastically reduced the medial contact force by 44% and 30% and the medial over lateral contact load and area ratios by 92% and 79% as well as 64% and 51%, respectively. In contrast, the equivalent alterations in KAM (by ± SD at constant KAA) had lower and less consistent effects (<7%) showing much smaller sensitivity to changes in KAM alone. Ligament forces altered at various stance periods with inconsistent trends; peak values of 418 N in the anterior cruciate ligament (90% carried by the posterolateral bundle) and 1056 N in the patellar tendon were computed both at 25% stance and minimum KAA.

SIGNIFICANCE

These findings indicate a poor correlation between KAM and tibiofemoral load distribution suggesting instead that KAA and knee alignment should be in focus as the primary marker of knee joint load partitioning and associated prevention and treatment interventions.

Computational analysis of knee joint stability following total knee arthroplasty

The overall objective of this study was to introduce knee joint power as a potential measure to investigate knee joint stability following total knee arthroplasty (TKA). Specific aims were to investigate whether weakened knee joint stabilizers cause abnormal kinematics and how it influences the knee joint kinetic (i.e., power) in response to perturbation. Patient-specific musculoskeletal models were simulated with experimental gait data from six TKA patients (baseline models). Muscle strength and ligament force parameter were reduced by up to 30% to simulate weak knee joint stabilizers (weak models). Two different muscle recruitment criteria were tested to examine whether altered muscle recruitment pattern can mask the influence of weakened stabilizers on the knee joint kinematics and kinetics. Level-walking knee joint kinematics and kinetics were calculated though force-dependent kinematic and inverse dynamic analyses. Bode analysis was then recruited to estimate the knee joint power in response to a simulated perturbation. Weak models resulted in larger anterior-posterior (A-P) displacement and internal-external (I-E) rotation compared to baseline (I-E: 18.4 ± 8.5 vs. 11.6 ± 5.7 (deg), A-P: 9.7 ± 5.6 vs. 5.5 ± 4.1 (mm)). Changes in muscle recruitment criterion however altered the results such that A-P and I-E were not notably different from baseline models. In response to the simulated perturbation, weak models versus baseline models generated a delayed power response with unbounded magnitudes. Perturbed power behavior of the knee remained unaltered regardless of the muscle recruitment criteria. In conclusion, impairment at the knee joint stabilizers may or may not lead to excessive joint motions but it notably affects the knee joint power in response to a perturbation. Whether perturbed knee joint power is associated with the patient-reported outcome requires further investigation.

A lower extremity model for muscle-driven simulation of activity using explicit finite element modeling

A key strength of computational modeling is that it can provide estimates of muscle, ligament, and joint loads, stresses, and strains through non-invasive means. However, simulations that can predict the forces in the muscles during activity while maintaining sufficient complexity to realistically represent the muscles and joint structures can be computationally challenging. For this reason, the current state of the art is to apply separate rigid-body dynamic and finite-element (FE) analyses in series. However, the use of two or more disconnected models often fails to capture key interactions between the joint-level and whole-body scales. Single framework MSFE models have the potential to overcome the limitations associated with disconnected models in series. The objectives of the current study were to create a multi-scale FE model of the human lower extremity that combines optimization, dynamic muscle modeling, and structural FE analysis in a single framework and to apply this framework to evaluate the mechanics of healthy knee specimens during two activities. Two subject-specific FE models (Model 1, Model 2) of the lower extremity were developed in ABAQUS/Explicit including detailed representations of the muscles. Muscle forces, knee joint loading, and articular contact were calculated for two activities using an inverse dynamics approach and static optimization. Quadriceps muscle forces peaked at the onset of chair rise (2174 N, 1962 N) and in early stance phase (510 N, 525 N), while gait saw peak forces in the hamstrings (851 N, 868 N) in midstance. Joint forces were similar in magnitude to available telemetric patient data. This study demonstrates the feasibility of detailed quasi-static, muscle-driven simulations in an FE framework.

Impact of antagonistic muscle co-contraction on in vivo knee contact forces

Background

The onset and progression of osteoarthritis, but also the wear and loosening of the components of an artificial joint, are commonly associated with mechanical overloading of the structures. Knowledge of the mechanical forces acting at the joints, together with an understanding of the key factors that can alter them, are critical to develop effective treatments for restoring joint function. While static anatomy is usually the clinical focus, less is known about the impact of dynamic factors, such as individual muscle recruitment, on joint contact forces.

Methods

In this study, instrumented knee implants provided accurate in vivo tibio-femoral contact forces in a unique cohort of 9 patients, which were used as input for subject specific musculoskeletal models, to quantify the individual muscle forces during walking and stair negotiation.

Results

Even between patients with a very similar self-selected gait speed, the total tibio-femoral peak forces varied 1.7-fold, but had only weak correlation with static alignment (varus/valgus). In some patients, muscle co-contraction of quadriceps and gastrocnemii during walking added up to 1 bodyweight (~ 50%) to the peak tibio-femoral contact force during late stance. The greatest impact of co-contraction was observed in the late stance phase of stair ascent, with an increase of the peak tibio-femoral contact force by up to 1.7 bodyweight (66%).

Conclusions

Treatment of diseased and failed joints should therefore not only be restricted to anatomical reconstruction of static limb axes alignment. The dynamic activation of muscles, as a key modifier of lower limb biomechanics, should also be taken into account and thus also represents a promising target for restoring function, patient mobility, and preventing future joint failure.

Trial registration

German Clinical Trials Register: ID: DRKS00000606, date: 05.11.2010.

Electronic supplementary material

The online version of this article (10.1186/s12984-018-0434-3) contains supplementary material, which is available to authorized users.

A computational framework for simultaneous estimation of muscle and joint contact forces and body motion using optimization and surrogate modeling

Concurrent estimation of muscle activations, joint contact forces, and joint kinematics by means of gradient-based optimization of musculoskeletal models is hindered by computationally expensive and non-smooth joint contact and muscle wrapping algorithms. We present a framework that simultaneously speeds up computation and removes sources of non-smoothness from muscle force optimizations using a combination of parallelization and surrogate modeling, with special emphasis on a novel method for modeling joint contact as a surrogate model of a static analysis. The approach allows one to efficiently introduce elastic joint contact models within static and dynamic optimizations of human motion. We demonstrate the approach by performing two optimizations, one static and one dynamic, using a pelvis-leg musculoskeletal model undergoing a gait cycle. We observed convergence on the order of seconds for a static optimization time frame and on the order of minutes for an entire dynamic optimization. The presented framework may facilitate model-based efforts to predict how planned surgical or rehabilitation interventions will affect post-treatment joint and muscle function.

Dynamic simulation of knee-joint loading during gait using force-feedback control and surrogate contact modelling

The aim of this study was to perform multi-body, muscle-driven, forward-dynamics simulations of human gait using a 6-degree-of-freedom (6-DOF) model of the knee in tandem with a surrogate model of articular contact and force control. A forward-dynamics simulation incorporating position, velocity and contact force-feedback control (FFC) was used to track full-body motion capture data recorded for multiple trials of level walking and stair descent performed by two individuals with instrumented knee implants. Tibiofemoral contact force errors for FFC were compared against those obtained from a standard computed muscle control algorithm (CMC) with a 6-DOF knee contact model (CMC6); CMC with a 1-DOF translating hinge-knee model (CMC1); and static optimization with a 1-DOF translating hinge-knee model (SO). Tibiofemoral joint loads predicted by FFC and CMC6 were comparable for level walking, however FFC produced more accurate results for stair descent. SO yielded reasonable predictions of joint contact loading for level walking but significant differences between model and experiment were observed for stair descent. CMC1 produced the least accurate predictions of tibiofemoral contact loads for both tasks. Our findings suggest that reliable estimates of knee-joint loading may be obtained by incorporating position, velocity and force-feedback control with a multi-DOF model of joint contact in a forward-dynamics simulation of gait.

Introduction to Force-Dependent Kinematics: Theory and Application to Mandible Modeling

Knowledge of the muscle, ligament, and joint forces is important when planning orthopedic surgeries. Since these quantities cannot be measured in vivo under normal circumstances, the best alternative is to estimate them using musculoskeletal models. These models typically assume idealized joints, which are sufficient for general investigations but insufficient if the joint in focus is far from an idealized joint. The purpose of this study was to provide the mathematical details of a novel musculoskeletal modeling approach, called force-dependent kinematics (FDK), capable of simultaneously computing muscle, ligament, and joint forces as well as internal joint displacements governed by contact surfaces and ligament structures. The method was implemented into the anybody modeling system and used to develop a subject-specific mandible model, which was compared to a point-on-plane (POP) model and validated against joint kinematics measured with a custom-built brace during unloaded emulated chewing, open and close, and protrusion movements. Generally, both joint models estimated the joint kinematics well with the POP model performing slightly better (root-mean-square-deviation (RMSD) of less than 0.75 mm for the POP model and 1.7 mm for the FDK model). However, substantial differences were observed when comparing the estimated joint forces (RMSD up to 24.7 N), demonstrating the dependency on the joint model. Although the presented mandible model still contains room for improvements, this study shows the capabilities of the FDK methodology for creating joint models that take the geometry and joint elasticity into account.

Evaluation of a Surrogate Contact Model in Force-Dependent Kinematic Simulations of Total Knee Replacement

Knowing the forces in the human body is of great clinical interest and musculoskeletal (MS) models are the most commonly used tool to estimate them in vivo. Unfortunately, the process of computing muscle, joint contact, and ligament forces simultaneously is computationally highly demanding. The goal of this study was to develop a fast surrogate model of the tibiofemoral (TF) contact in a total knee replacement (TKR) model and apply it to force-dependent kinematic (FDK) simulations of activities of daily living (ADLs). Multiple domains were populated with sample points from the reference TKR contact model, based on reference simulations and design-of-experiments. Artificial neural networks (ANN) learned the relationship between TF pose and loads from the medial and lateral sides of the TKR implant. Normal and right-turn gait, rising-from-a-chair, and a squat were simulated using both surrogate and reference contact models. Compared to the reference contact model, the surrogate contact model predicted TF forces with a root-mean-square error (RMSE) lower than 10 N and TF moments lower than 0.3 N·m over all simulated activities. Secondary knee kinematics were predicted with RMSE lower than 0.2 mm and 0.2 deg. Simulations that used the surrogate contact model ran on average three times faster than those using the reference model, allowing the simulation of a full gait cycle in 4.5 min. This modeling approach proved fast and accurate enough to perform extensive parametric analyses, such as simulating subject-specific variations and surgical-related factors in TKR.

Vacuum level effects on knee contact force for unilateral transtibial amputees with elevated vacuum suspension

The elevated vacuum suspension system (EVSS) has demonstrated unique health benefits for amputees, but the effect of vacuum pressure values on knee contact force (KCF) is still unclear. The objective of this study was to investigate the effect of vacuum levels on KCF for unilateral transtibial amputees (UTA) using the EVSS. Three-dimensional gait was modeled for 9 UTA with five vacuum levels (0-20inHg [67.73kPa], 5inHg [16.93kPa] increments) and 9 non-amputees based on kinematic and ground reaction force data. The results showed that the vacuum level effects were significant for peak axial KCF, which had a relatively large value at 0 and 20inHg (67.73kPa). The intact limb exhibited a comparable peak axial KCF to the non-amputees at 15inHg (50.79kPa). At moderate vacuum levels (5inHg [16.93kPa] to 15inHg [50.79kPa]), co-contraction of quadriceps and hamstrings at peak axial KCF was similar for the intact limb, but was smaller for the residual limb comparing with the non-amputees. The intact limb showed a similar magnitude of quadriceps and hamstrings force at 15inHg (50.79kPa) to the non-amputees, but the muscle coordination patterns varied between the residual and intact limbs. These findings indicate that a proper vacuum level may partially compensate for the lack of ankle plantarflexor and reduce the knee loading. Of the tested vacuum levels, 15inHg (50.79kPa) appears most favorable, although additional analyses with more amputees are suggested to confirm these results prior to establishing clinical guidelines.

Functional electrical stimulation of gluteus medius reduces the medial joint reaction force of the knee during level walking

Background

By altering muscular activation patterns, internal forces acting on the human body during dynamic activity may be manipulated. The magnitude of one of these forces, the medial knee joint reaction force (JRF), is associated with disease progression in patients with early osteoarthritis (OA), suggesting utility in its targeted reduction. Increased activation of gluteus medius has been suggested as a means to achieve this.

Methods

Motion capture equipment and force plate transducers were used to obtain kinematic and kinetic data for 15 healthy subjects during level walking, with and without the application of functional electrical stimulation (FES) to gluteus medius. Musculoskeletal modelling was employed to determine the medial knee JRF during stance phase for each trial. A further computer simulation of increased gluteus medius activation was performed using data from normal walking trials by a manipulation of modelling parameters. Relationships between changes in the medial knee JRF, kinematics and ground reaction force were evaluated.

Results

In simulations of increased gluteus medius activity, the total impulse of the medial knee JRF was reduced by 4.2 % (p = 0.003) compared to control. With real-world application of FES to the muscle, the magnitude of this reduction increased to 12.5 % (p < 0.001), with significant inter-subject variation. Across subjects, the magnitude of reduction correlated strongly with kinematic (p < 0.001) and kinetic (p < 0.001) correlates of gluteus medius activity.

Conclusions

The results support a major role for gluteus medius in the protection of the knee for patients with OA, establishing the muscle’s central importance to effective therapeutic regimes. FES may be used to achieve increased activation in order to mitigate distal internal loads, and much of the benefit of this increase can be attributed to resulting changes in kinematic parameters and the ground reaction force. The utility of interventions targeting gluteus medius can be assessed in a relatively straightforward way by determination of the magnitude of reduction in pelvic drop, an easily accessed marker of aberrant loading at the knee.

Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis

Musculoskeletal models are powerful tools that allow biomechanical investigations and predictions of muscle forces not accessible with experiments. A core challenge modelers must confront is validation. Measurements of muscle activity and joint loading are used for qualitative and indirect validation of muscle force predictions. Subject-specific models have reached high levels of complexity and can predict contact loads with surprising accuracy. However, every deterministic musculoskeletal model contains an intrinsic uncertainty due to the high number of parameters not identifiable in vivo. The objective of this work is to test the impact of intrinsic uncertainty in a scaled-generic model on estimates of muscle and joint loads. Uncertainties in marker placement, limb coronal alignment, body segment parameters, Hill-type muscle parameters, and muscle geometry were modeled with a global probabilistic approach (multiple uncertainties included in a single analysis). 5-95% confidence bounds and input/output sensitivities of predicted knee compressive loads and varus/valgus contact moments were estimated for a gait activity of three subjects with telemetric knee implants from the "Grand Challenge Competition." Compressive load predicted for the three subjects showed confidence bounds of 333 ± 248 N, 408 ± 333 N, and 379 ± 244 N when all the sources of uncertainty were included. The measured loads lay inside the predicted 5-95% confidence bounds for 77%, 83%, and 76% of the stance phase. Muscle maximum isometric force, muscle geometry, and marker placement uncertainty most impacted the joint load results. This study demonstrated that identification of these parameters is crucial when subject-specific models are developed.

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.

Peak activation of lower limb musculature during high flexion kneeling and transitional movements

Few studies have measured lower limb muscle activation during high knee flexion or investigated the effects of occupational safety footwear. Therefore, our understanding of injury and disease mechanisms, such as knee osteoarthritis, is limited for these high-risk postures. Peak activation was assessed in eight bilateral lower limb muscles for twelve male participants, while shod or barefoot. Transitions between standing and kneeling had peak quadriceps and tibialis anterior (TA) activations above 50% MVC. Static kneeling and simulated tasks performed when kneeling had peak TA activity above 15% MVC but below 10% MVC for remaining muscles. In three cases, peak muscle activity was significantly higher (mean 8.9% MVC) when shod. However, net compressive knee joint forces may not be significantly increased when shod. EMG should be used as a modelling input when estimating joint contact forces for these postures, considering the activation levels in the hamstrings and quadriceps muscles during transitions. Practitioner Summary: Kneeling transitional movements are used in activities of daily living and work but are linked to increased knee osteoarthritis risk. We found peak EMG activity of some lower limb muscles to be over 70% MVC during transitions and minimal influence of wearing safety footwear.

Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and -0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking.

Muscle-tendon unit scaling methods of Hill-type musculoskeletal models: An overview

This article gives an overview of the state of the art in scaling methods of generic Hill-type muscle model parameters in view of different applications and implementation of experimental data. This article establishes the requirements used to alter a generic model toward subject-specific musculoskeletal models. This article aims to improve model transparency by a structured description of scaling methods and the associated limitations in musculoskeletal models and highlight the importance of selecting a scaling method supporting the purpose of the model.

Are unilateral and bilateral knee osteoarthritis patients unique subsets of knee osteoarthritis? A biomechanical perspective

OBJECTIVE

To compare the gait of adults with unilateral and bilateral symptomatic and radiographic knee osteoarthritis (OA) to determine whether these subgroups can be treated similarly in the clinic and when recruiting for randomized clinical trials, and to use these data to generate future hypotheses regarding gait in these subsets of knee OA patients.

METHODS

Cross-sectional investigation of patients with unilateral and bilateral knee OA on gait mechanics using 136 older adults (age ≥55 yrs; 27 kg m(-2) ≥ BMI ≤ 41 kg m(-2); 82% female) with radiographic knee OA. Comparisons were made between the most affected side of the bilateral group (Bi) and the affected side of the unilateral group (Uni), and between symmetry indices of each group.

RESULTS

There were no significant differences in any temporal, kinematic, or kinetic measures between the Uni and Bi cohorts. Comparison of symmetry indices between groups also revealed no significant differences.

CONCLUSION

The similarity in lower extremity mechanics between unilateral and bilateral knee OA patients is sufficiently robust to consider both subsets as a single cohort. We hypothesize that biomechanical adaptations to knee OA are at least partially systemic in origin and not based solely on the physiological characteristics of an affected knee joint.

Prediction of medial and lateral contact force of the knee joint during normal and turning gait after total knee replacement

The computational modeling approach has commonly been used to predict knee joint contact forces, muscle forces, and ligament loads during activities of daily living. Knowledge of these forces has several potential applications, for example, within design of equipment to protect the knee joint from injury and to plan adequate rehabilitation protocols, although clinical applications of computational models are still evolving and one of the limiting factors is model validation. The objective of this study was to extend previous modeling technique and to improve the validity of the model prediction using publicly available data set of the fifth "Grand Challenge Competition to Predict In Vivo Knee Loads." A two-stage modeling approach, which combines conventional inverse dynamic analysis (the first stage) with a multi-body subject-specific lower limb model (the second stage), was used to calculate medial and lateral compartment contact forces. The validation was performed by direct comparison of model predictions and experimental measurement of medial and lateral compartment contact forces during normal and turning gait. The model predictions of both medial and lateral contact forces showed strong correlations with experimental measurements in normal gait (r = 0.75 and 0.71) and in turning gait trials (r = 0.86 and 0.72), even though the current technique over-estimated medial compartment contact forces in swing phase. The correlation coefficient, Sprague and Geers metrics, and root mean squared error indicated that the lateral contact forces were predicted better than medial contact forces in comparison with the experimental measurements during both normal and turning gait trials.

Influence of Ligament Properties on Tibiofemoral Mechanics in Walking

Computational knee models provide a powerful platform to investigate the effects of injury and surgery on functional knee behavior. The objective of this study was to use a multibody knee model to investigate the influence of ligament properties on tibiofemoral kinematics and cartilage contact pressures in the stance phase of walking. The knee model included 14 ligament bundles and articular cartilage contact acting across the tibiofemoral and patellofemoral joints. The knee was incorporated into a lower extremity musculoskeletal model and was used to simulate knee mechanics during the stance phase of normal walking. A Monte Carlo approach was employed to assess the influence of ligament stiffness and reference strain on knee mechanics. The anterior cruciate ligament (ACL), medial collateral ligament (MCL), and posterior capsule properties exhibited significant influence on anterior tibial translation at heel strike, with the ACL acting as the primary restraint to anterior translation in mid-stance. The MCL and lateral collateral ligament (LCL) exhibited the greatest influence on tibial rotation from heel strike through mid-stance. Simulated tibial plateau contact location was dependent on the ACL, MCL, and LCL properties, while pressure magnitudes were most dependent on the ACL. A decrease in ACL stiffness or reference strain significantly increased the average contact pressure in mid-stance, with the pressure migrating posteriorly on the medial tibial plateau. These ligament-dependent shifts in tibiofemoral cartilage contact during walking are potentially relevant to consider when investigating the causes of early-onset osteoarthritis following knee ligament injury and surgical treatment.

Fixation of a split fracture of the lateral tibial plateau with a locking screw plate instead of cannulated screws would allow early weight bearing: a computational exploration

PURPOSE

To assess, with finite element (FE) calculations, whether immediate weight bearing would be possible after surgical stabilization either with cannulated screws or with a locking plate in a split fracture of the lateral tibial plateau (LTP).

METHODS

A split fracture of the LTP was recreated in a FE model of a human tibia. A three-dimensional FE model geometry of a human femur-tibia system was obtained from the VAKHUM project database, and was built from CT images from a subject with normal bone morphologies and normal alignment. The mesh of the tibia was reconverted into a geometry of NURBS surfaces. A split fracture of the lateral tibial plateau was reproduced by using geometrical data from patient radiographs. A locking screw plate (LP) and a cannulated screw (CS) systems were modelled to virtually reduce the fracture and 80 kg static body-weight was simulated.

RESULTS

While the simulated body-weight led to clinically acceptable interfragmentary motion, possible traumatic bone shear stresses were predicted nearby the cannulated screws. With a maximum estimation of about 1.7 MPa maximum bone shear stresses, the Polyax system might ensure more reasonable safety margins.

CONCLUSIONS

Split fractures of the LTP fixed either with locking screw plate or cannulated screws showed no clinically relevant IFM in a FE model. The locking screw plate showed higher mechanical stability than cannulated screw fixation. The locking screw plate might also allow full or at least partial weight bearing under static posture at time zero.

Multi-Joint Compensatory Effects of Unilateral Total Knee Arthroplasty During High-Demand Tasks

Patients with total knee arthroplasty (TKA) demonstrate quadriceps weakness and functional limitations 1 year after surgery during daily tasks such as walking and stair climbing. Most biomechanical analyses of patients after TKA focus on quadriceps function and rarely investigate other lower-extremity muscles or high-demand ambulatory activities of daily living. The purpose of this investigation was to quantify lower-extremity muscle forces in patients with unilateral TKA during high-demand tasks of pivoting and descending stairs. Five patients with unilateral TKA and five age and sex-matched controls performed three bilateral high-demand tasks: (1) step down from an 8-inch platform, (2) inside pivot: 90° direction change toward planted limb, and (3) outside pivot: 90° direction change away from planted limb. Subject-specific musculoskeletal simulations were created in OpenSim to determine joint angles, moments, and lower-extremity muscle forces. The results indicate that patients with TKA adopt compensatory strategies at both the hip and knee. Patients with TKA demonstrated increased hip external rotation, decreased knee flexion, decreased quadriceps force, and decreased hip abductor force in all three tasks. These strategies are likely a result of quadriceps avoidance, which may stem from instability after TKA or a habitual strategy developed during the late stages of osteoarthritis.

Obesity is associated with prolonged activity of the quadriceps and gastrocnemii during gait

PURPOSE

To examine the effect of obesity and its potential interaction with knee OA presence on the electromyography patterns of the major knee joint periarticular muscles during walking.

SCOPE

One hundred and eighteen asymptomatic adults and 177 adults with moderate knee osteoarthritis were subdivided into categories of healthy weight (n = 77; 20 kg/m(2) < BMI < 25 kg/m(2)), overweight (n = 117; 25 kg/m(2) ⩽ BMI < 30 kg/m(2)), and obese (n = 101; BMI ⩾ 30 kg/m(2) based on their body mass index (BMI). All individuals underwent a three-dimensional gait analysis. Surface electromyograms from the lateral and medial gastrocnemii, lateral and medial hamstrings, vastus lateralis, vastus medialis, and rectus femoris were recorded during self-selected speed walking. Principal component analysis was used to extract major features of amplitude and temporal pattern variability from the electromyograms of each muscle group (gastrocnemii, quadriceps, hamstrings separately). Analysis of variance models tested for main BMI category effects and interaction effects for these features (α = 0.05). Statistically significant BMI category (i.e. obesity) effects were found for features that described more prolonged activations of the gastrocnemii and quadriceps muscles during the stance phase of gait with obesity (P < 0.05).

CONCLUSIONS

Obesity was associated with prolonged activation of quadriceps and gastrocnemii, which can result in prolonged knee joint contact loading, and thereby may contribute to the predisposition of knee OA development and progression in obese individuals.

Knee joint loading in knee osteoarthritis: influence of abdominal and thigh fat

PURPOSE

Using three separate models that included total body mass, total lean and total fat mass, and abdominal and thigh fat as independent measures, we determined their association with knee joint loads in older overweight and obese adults with knee osteoarthritis (OA).

METHODS

Fat depots were quantified using computed tomography, and total lean and fat mass were determined with dual energy x-ray absorptiometry in 176 adults (age, 66.3 yr; body mass index, 33.5 kg·m) with radiographic knee OA. Knee moments and joint bone-on-bone forces were calculated using gait analysis and musculoskeletal modeling.

RESULTS

Higher total body mass was significantly associated (P ≤ 0.0001) with greater knee compressive and shear forces, compressive and shear impulses (P < 0.0001), patellofemoral forces (P < 0.006), and knee extensor moments (P = 0.003). Regression analysis with total lean and total fat mass as independent variables revealed significant positive associations of total fat mass with knee compressive (P = 0.0001), shear (P < 0.001), and patellofemoral forces (P = 0.01) and knee extension moment (P = 0.008). Gastrocnemius and quadriceps forces were positively associated with total fat mass. Total lean mass was associated with knee compressive force (P = 0.002). A regression model that included total thigh and total abdominal fat found that both were significantly associated with knee compressive and shear forces (P ≤ 0.04). Thigh fat was associated with knee abduction (P = 0.03) and knee extension moment (P = 0.02).

CONCLUSIONS

Thigh fat, consisting predominately of subcutaneous fat, had similar significant associations with knee joint forces as abdominal fat despite its much smaller volume and could be an important therapeutic target for people with knee OA.

A Hertzian Integrated Contact Model of the Total Knee Replacement Implant for the Estimation of Joint Contact Forces

The prediction of lower limb muscle and contact forces may provide useful knowledge to assist the clinicians in the diagnosis as well as in the development of appropriate treatment for musculoskeletal disorders. Research studies have commonly estimated joint contact forces using model-based muscle force estimation due to the lack of a reliable contact model and material properties. The objective of this present study was to develop a Hertzian integrated contact model. Then, in vivo elastic properties of the Total Knee Replacement (TKR) implant were identified using in vivo contact forces leading to providing reliable material properties for modeling purposes. First, a patient specific rigid musculoskeletal model was built. Second, a STL-based implant model was designed to compute the contact area evolutions during gait motions. Finally, a Hertzian integrated contact model was defined for the in vivo identification of elastic properties (Young’s modulus and Poisson coefficient) of the instrumented TKR implant. Our study showed a potential use of a new approach to predict the contact forces without knowledge of muscle forces. Thus, the outcomes may lead to accurate and reliable prediction of human joint contact forces for new case study.

Feasible muscle activation ranges based on inverse dynamics analyses of human walking

Although it is possible to produce the same movement using an infinite number of different muscle activation patterns owing to musculoskeletal redundancy, the degree to which observed variations in muscle activity can deviate from optimal solutions computed from biomechanical models is not known. Here, we examined the range of biomechanically permitted activation levels in individual muscles during human walking using a detailed musculoskeletal model and experimentally-measured kinetics and kinematics. Feasible muscle activation ranges define the minimum and maximum possible level of each muscle's activation that satisfy inverse dynamics joint torques assuming that all other muscles can vary their activation as needed. During walking, 73% of the muscles had feasible muscle activation ranges that were greater than 95% of the total muscle activation range over more than 95% of the gait cycle, indicating that, individually, most muscles could be fully active or fully inactive while still satisfying inverse dynamics joint torques. Moreover, the shapes of the feasible muscle activation ranges did not resemble previously-reported muscle activation patterns nor optimal solutions, i.e. static optimization and computed muscle control, that are based on the same biomechanical constraints. Our results demonstrate that joint torque requirements from standard inverse dynamics calculations are insufficient to define the activation of individual muscles during walking in healthy individuals. Identifying feasible muscle activation ranges may be an effective way to evaluate the impact of additional biomechanical and/or neural constraints on possible versus actual muscle activity in both normal and impaired movements.

Surrogate modeling of deformable joint contact using artificial neural networks

Deformable joint contact models can be used to estimate loading conditions for cartilage-cartilage, implant-implant, human-orthotic, and foot-ground interactions. However, contact evaluations are often so expensive computationally that they can be prohibitive for simulations or optimizations requiring thousands or even millions of contact evaluations. To overcome this limitation, we developed a novel surrogate contact modeling method based on artificial neural networks (ANNs). The method uses special sampling techniques to gather input-output data points from an original (slow) contact model in multiple domains of input space, where each domain represents a different physical situation likely to be encountered. For each contact force and torque output by the original contact model, a multi-layer feed-forward ANN is defined, trained, and incorporated into a surrogate contact model. As an evaluation problem, we created an ANN-based surrogate contact model of an artificial tibiofemoral joint using over 75,000 evaluations of a fine-grid elastic foundation (EF) contact model. The surrogate contact model computed contact forces and torques about 1000 times faster than a less accurate coarse grid EF contact model. Furthermore, the surrogate contact model was seven times more accurate than the coarse grid EF contact model within the input domain of a walking motion. For larger input domains, the surrogate contact model showed the expected trend of increasing error with increasing domain size. In addition, the surrogate contact model was able to identify out-of-contact situations with high accuracy. Computational contact models created using our proposed ANN approach may remove an important computational bottleneck from musculoskeletal simulations or optimizations incorporating deformable joint contact models.