Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces

Pediatric obesity and walking duration increase medial tibiofemoral compartment contact forces

With the high prevalence of pediatric obesity there is a need for structured physical activity during childhood. However, altered tibiofemoral loading during physical activity in obese children likely contribute to their increased risk of orthopedic disorders of the knee. The goal of this study was to determine the effects of pediatric obesity and walking duration on medial and lateral tibiofemoral contact forces. We collected experimental biomechanics data during treadmill walking at 1 m•s(-1) for 20 min in 10 obese and 10 healthy-weight 8-12 year-olds. We created subject-specific musculoskeletal models using radiographic measures of tibiofemoral alignment and centers-of-pressure, and predicted medial and lateral tibiofemoral contact forces at the beginning and end of each trial. Obesity and walking duration affected tibiofemoral loading. At the beginning of the trail, the average percent of the total load passing through the medial compartment during stance was 85% in the obese children and 63% in the healthy-weight children; at the end of the trial, the medial distribution was 90% in the obese children and 72% in the healthy-weight children. Medial compartment loading rates were 1.78 times greater in the obese participants. The medial compartment loading rate increased 17% in both groups at the end compared to the beginning of the trial (p = 0.001). We found a strong linear relationship between body-fat percentage and the medial-lateral load distribution (r(2) = 0.79). Altered tibiofemoral loading during walking in obese children may contribute to their increased risk of knee pain and pathology.

Musculoskeletal Simulation for Assessment of Effect of Movement-Based Structure-Modifying Treatment Strategies

The better understanding of the complex mechanism between neural motor control and its resulting joint kinematics and muscle forces allows a better elucidation of the mechanisms behind body growth, aging progression, and disease development. This study aimed at investigating the impact of movement-based structure-modifying treatment strategies on joint kinematics, muscle forces, and muscle synergies of the gait with instrumented implant. A patient-specific musculoskeletal model was used to quantitatively assess the deviations of joint and muscle behaviors between the normal gait and 4 gait modifications (bouncy, medial thrust, midcrouch, and mtp (i.e., gait with forefoot strike)). Moreover, muscle synergy analysis was performed using EMG-based nonnegative matrix factorization. Large variation of 19 degrees and 190 N was found for knee flexion/extension and lower limb muscle forces, respectively. EMG-based muscle synergy analysis revealed that the activation levels of the vastus lateralis and tibialis anterior are dominant for the midcrouch gait. In addition, an important contribution of semimembranosus to the medial thrust and midcrouch gaits was also observed. In fact, such useful information could allow a better understanding of the joint function and muscle synergy strategies leading to deeper knowledge of joint and muscle mechanisms related to neural voluntary motor commands.

Alterations in knee contact forces and centers in stance phase of gait: A detailed lower extremity musculoskeletal model

Evaluation of contact forces-centers of the tibiofemoral joint in gait has crucial biomechanical and pathological consequences. It involves however difficulties and limitations in in vitro cadaver and in vivo imaging studies. The goal is to estimate total contact forces (CF) and location of contact centers (CC) on the medial and lateral plateaus using results computed by a validated finite element model simulating the stance phase of gait for normal as well as osteoarthritis, varus-valgus and posterior tibial slope altered subjects. Using foregoing contact results, six methods commonly used in the literature are also applied to estimate and compare locations of CC at 6 periods of stance phase (0%, 5%, 25%, 50%, 75% and 100%). TF joint contact forces are greater on the lateral plateau very early in stance and on the medial plateau thereafter during 25-100% stance periods. Large excursions in the location of CC (>17mm), especially on the medial plateau in the mediolateral direction, are computed. Various reported models estimate quite different CCs with much greater variations (~15mm) in the mediolateral direction on both plateaus. Compared to our accurately computed CCs taken as the gold standard, the centroid of contact area algorithm yielded least differences (except in the mediolateral direction on the medial plateau at ~5mm) whereas the contact point and weighted center of proximity algorithms resulted overall in greatest differences. Large movements in the location of CC should be considered when attempting to estimate TF compartmental contact forces in gait.

Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique

A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par.

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 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.

A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions

Humans can efficiently walk across a large variety of terrains and locomotion conditions with little or no mental effort. It has been hypothesized that the nervous system simplifies neuromuscular control by using muscle synergies, thus organizing multi-muscle activity into a small number of coordinative co-activation modules. In the present study we investigated how muscle modularity is structured across a large repertoire of locomotion conditions including five different speeds and five different ground elevations. For this we have used the non-negative matrix factorization technique in order to explain EMG experimental data with a low-dimensional set of four motor components. In this context each motor components is composed of a non-negative factor and the associated muscle weightings. Furthermore, we have investigated if the proposed descriptive analysis of muscle modularity could be translated into a predictive model that could: (1) Estimate how motor components modulate across locomotion speeds and ground elevations. This implies not only estimating the non-negative factors temporal characteristics, but also the associated muscle weighting variations. (2) Estimate how the resulting muscle excitations modulate across novel locomotion conditions and subjects. The results showed three major distinctive features of muscle modularity: (1) the number of motor components was preserved across all locomotion conditions, (2) the non-negative factors were consistent in shape and timing across all locomotion conditions, and (3) the muscle weightings were modulated as distinctive functions of locomotion speed and ground elevation. Results also showed that the developed predictive model was able to reproduce well the muscle modularity of un-modeled data, i.e., novel subjects and conditions. Muscle weightings were reconstructed with a cross-correlation factor greater than 70% and a root mean square error less than 0.10. Furthermore, the generated muscle excitations matched well the experimental excitation with a cross-correlation factor greater than 85% and a root mean square error less than 0.09. The ability of synthetizing the neuromuscular mechanisms underlying human locomotion across a variety of locomotion conditions will enable solutions in the field of neurorehabilitation technologies and control of bipedal artificial systems. Open-access of the model implementation is provided for further analysis at https://simtk.org/home/p-mep/.

Peak loading during walking is not associated with fracture migration following tibial plateau fracture: A preliminary case series

Tibial plateau fractures are common, but little evidence exists for their postoperative management, especially when recommending if patients should weight bear at all, partially, or as tolerated. In this study, we describe the loads passing through the fracture construct and the associated fracture migration over the first year following surgery. Nine patients were treated with open reduction and internal fixation and instructed to weight bear as tolerated. Fracture loading and migration were assessed at 2, 12, 26, and 52 weeks postoperative. Fracture loading was calculated as the knee joint reaction force (peak, average, the angle of the force vector, and the point of force application) using gait analysis and an inverse dynamics musculoskeletal model. Fracture migration was assessed using radiostereometric analysis. The fractures were progressively loaded during the rehabilitation phase. The point of application of the load shifted from neutral to medial by week 26 for all patients. Migration during the first postoperative year was within current clinical acceptable limits. The peak load during walking at each time point was not associated with fracture fragment migration and does not appear to exceed the elastic limit of the fracture construct.

The mobilize center: an NIH big data to knowledge center to advance human movement research and improve mobility

Regular physical activity helps prevent heart disease, stroke, diabetes, and other chronic diseases, yet a broad range of conditions impair mobility at great personal and societal cost. Vast amounts of data characterizing human movement are available from research labs, clinics, and millions of smartphones and wearable sensors, but integration and analysis of this large quantity of mobility data are extremely challenging. The authors have established the Mobilize Center (http://mobilize.stanford.edu) to harness these data to improve human mobility and help lay the foundation for using data science methods in biomedicine. The Center is organized around 4 data science research cores: biomechanical modeling, statistical learning, behavioral and social modeling, and integrative modeling. Important biomedical applications, such as osteoarthritis and weight management, will focus the development of new data science methods. By developing these new approaches, sharing data and validated software tools, and training thousands of researchers, the Mobilize Center will transform human movement research.

Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion

This work presents an electrophysiologically and dynamically consistent musculoskeletal model to predict stiffness in the human ankle and knee joints as derived from the joints constituent biological tissues (i.e., the spanning musculotendon units). The modeling method we propose uses electromyography (EMG) recordings from 13 muscle groups to drive forward dynamic simulations of the human leg in five healthy subjects during overground walking and running. The EMG-driven musculoskeletal model estimates musculotendon and resulting joint stiffness that is consistent with experimental EMG data as well as with the experimental joint moments. This provides a framework that allows for the first time observing 1) the elastic interplay between the knee and ankle joints, 2) the individual muscle contribution to joint stiffness, and 3) the underlying co-contraction strategies. It provides a theoretical description of how stiffness modulates as a function of muscle activation, fiber contraction, and interacting tendon dynamics. Furthermore, it describes how this differs from currently available stiffness definitions, including quasi-stiffness and short-range stiffness. This work offers a theoretical and computational basis for describing and investigating the neuromuscular mechanisms underlying human locomotion.

Instrumented knee joint implants: innovations and promising concepts

This article focuses on in vivo implementations of instrumented knee implants and recent prototypes with highly innovative potential. An in-depth analysis of the evolution of these systems was conducted, including three architectures developed by two research teams for in vivo operation that were implanted in 13 patients. The specifications of their various subsystems: sensor/transducers, power management, communication and processing/control units are presented, and their features are compared. These systems were designed to measure biomechanical quantities to further assist in rehabilitation and physical therapy, to access proper implant placement and joint function and to help predicting aseptic loosening. Five prototype systems that aim to improve their operation, as well as include new abilities, are also featured. They include technology to assist proper ligament tensioning and ensure self-powering. One can conclude that the concept of instrumented active knee implant seems the most promising trend for improving the outcomes of knee replacements.

Contribution of tibiofemoral joint contact to net loads at the knee in gait

Inverse dynamics analysis is commonly used to estimate the net loads at a joint during human motion. Most lower-limb models of movement represent the knee as a simple hinge joint when calculating muscle forces. This approach is limited because it neglects the contributions from tibiofemoral joint contact forces and may therefore lead to errors in estimated muscle forces. The aim of this study was to quantify the contributions of tibiofemoral joint contact loads to the net knee loads calculated from inverse dynamics for multiple subjects and multiple gait patterns. Tibiofemoral joint contact loads were measured in four subjects with instrumented implants as each subject walked at their preferred speed (normal gait) and performed prescribed gait modifications designed to treat medial knee osteoarthritis. Tibiofemoral contact loads contributed substantially to the net knee extension and knee adduction moments in normal gait with mean values of 16% and 54%, respectively. These findings suggest that knee-contact kinematics and loads should be included in lower-limb models of movement for more accurate determination of muscle forces. The results of this study may be used to guide the development of more realistic lower-limb models that account for the effects of tibiofemoral joint contact at the knee.

The development of a segment-based musculoskeletal model of the lower limb: introducing FreeBody

Traditional approaches to the biomechanical analysis of movement are joint-based; that is the mechanics of the body are described in terms of the forces and moments acting at the joints, and that muscular forces are considered to create moments about the joints. We have recently shown that segment-based approaches, where the mechanics of the body are described by considering the effect of the muscle, ligament and joint contact forces on the segments themselves, can also prove insightful. We have also previously described a simultaneous, optimization-based, musculoskeletal model of the lower limb. However, this prior model incorporates both joint- and segment-based assumptions. The purpose of this study was therefore to develop an entirely segment-based model of the lower limb and to compare its performance to our previous work. The segment-based model was used to estimate the muscle forces found during vertical jumping, which were in turn compared with the muscular activations that have been found in vertical jumping, by using a Geers' metric to quantify the magnitude and phase errors. The segment-based model was shown to have a similar ability to estimate muscle forces as a model based upon our previous work. In the future, we will evaluate the ability of the segment-based model to be used to provide results with clinical relevance, and compare its performance to joint-based approaches. The segment-based model described in this article is publicly available as a GUI-based Matlab® application and in the original source code (at www.msksoftware.org.uk).

Practical approach to subject-specific estimation of knee joint contact force

Compressive forces experienced at the knee can significantly contribute to cartilage degeneration. Musculoskeletal models enable predictions of the internal forces experienced at the knee, but validation is often not possible, as experimental data detailing loading at the knee joint is limited. Recently available data reporting compressive knee force through direct measurement using instrumented total knee replacements offer a unique opportunity to evaluate the accuracy of models. Previous studies have highlighted the importance of subject-specificity in increasing the accuracy of model predictions; however, these techniques may be unrealistic outside of a research setting. Therefore, the goal of our work was to identify a practical approach for accurate prediction of tibiofemoral knee contact force (KCF). Four methods for prediction of knee contact force were compared: (1) standard static optimization, (2) uniform muscle coordination weighting, (3) subject-specific muscle coordination weighting and (4) subject-specific strength adjustments. Walking trials for three subjects with instrumented knee replacements were used to evaluate the accuracy of model predictions. Predictions utilizing subject-specific muscle coordination weighting yielded the best agreement with experimental data; however this method required in vivo data for weighting factor calibration. Including subject-specific strength adjustments improved models' predictions compared to standard static optimization, with errors in peak KCF less than 0.5 body weight for all subjects. Overall, combining clinical assessments of muscle strength with standard tools available in the OpenSim software package, such as inverse kinematics and static optimization, appears to be a practical method for predicting joint contact force that can be implemented for many applications.

How tibiofemoral alignment and contact locations affect predictions of medial and lateral tibiofemoral contact forces

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined through radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r(2)=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r(2)=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment.

Osteoarthritis year in review 2014: mechanics--basic and clinical studies in osteoarthritis

The purpose of this review was to highlight recent research in mechanics and osteoarthritis (OA) by summarizing results from selected studies spanning basic and clinical research methods. Databases were searched from January 2013 through to March 2014. Working in pairs, reviewers selected 67 studies categorized into four themes--mechanobiology, ambulatory mechanics, biomechanical interventions and mechanical risk factors. Novel developments in mechanobiology included the identification of cell signaling pathways that mediated cellular responses to loading of articular cartilage. Studies in ambulatory mechanics included an increased focus on instrumented knee implants and progress in computational models, both emphasizing the importance of muscular contributions to load. Several proposed biomechanical interventions (e.g., shoe insoles and knee braces) produced variable changes in external knee joint moments during walking, while meta-analysis of randomized clinical trials did not support the use of lateral wedge insoles for decreasing pain. Results from high quality randomized trials suggested diet with or without exercise decreased indicators of knee joint load during walking, whereas similar effects from exercise alone were not detected with the measures used. Data from longitudinal cohorts suggested mechanical alignment was a risk factor for incidence and progression of OA, with the mechanism involving damage to the meniscus. In combination, the basic and clinical studies highlight the importance of considering multiple contributors to joint loading that can evoke both protective and damaging responses. Although challenges clearly exist, future studies should strive to integrate basic and clinical research methods to gain a greater understanding of the interactions among mechanical factors in OA and to develop improved preventive and therapeutic strategies.

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

Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur.

Multi-objective optimisation for musculoskeletal modelling: application to a planar elbow model

One of the open issues in musculoskeletal modelling remains the choice of the objective function that is used to solve the muscular redundancy problem. Some authors have recently proposed to introduce joint reaction forces in the objective function, and the question of the weights associated with musculo-tendon forces and joint reaction forces arose. This question typically deals with a multi-objective optimisation problem. The aim of this study is to illustrate, on a planar elbow model, the ensemble of optimal solutions (i.e. Pareto front) and the solution of a global objective method that represent different compromises between musculo-tendon forces, joint compression force, and joint shear force. The solutions of the global objective method, based either on the minimisation of the sum of the squared musculo-tendon forces alone or on the minimisation of the squared joint compression force and shear force together, are in the same range. Minimising either the squared joint compression force or shear force alone leads to extreme force values. The exploration of the compromises between these forces illustrates the existence of major interactions between the muscular and joint structures. Indeed, the joint reaction forces relate to the projection of the sum of the musculo-tendon forces. An illustration of these interactions, due to the projection relation, is that the Pareto front is not a large surface, like in a typical three-objective optimisation, but almost a curve. These interactions, and the possibility to take them into account by a multi-objective optimisation, seem essential for the application of musculoskeletal modelling to joint pathologies.

Prediction of in vivo joint mechanics of an artificial knee implant using rigid multi-body dynamics with elastic contacts

Lower extremity musculoskeletal computational models play an important role in predicting joint forces and muscle activation simultaneously and are valuable for investigating functional outcomes of the implants. However, current computational musculoskeletal models of total knee replacement rarely consider the bearing surface geometry of the implant. Therefore, these models lack detailed information about the contact loading and joint motion which are important factors for evaluating clinical performances. This study extended a rigid multi-body dynamics simulation of a lower extremity musculoskeletal model to incorporate an artificial knee joint, based upon a novel force-dependent kinematics method, and to characterize the in vivo joint contact mechanics during gait. The developed musculoskeletal total knee replacement model integrated the rigid skeleton multi-body dynamics and the flexible contact mechanics of the tibiofemoral and patellofemoral joints. The predicted contact forces and muscle activations are compared against those in vivo measurements obtained from a single patient with good agreements for the medial contact force (root-mean-square error = 215 N, ρ = 0.96) and lateral contact force (root-mean-square error = 179 N, ρ = 0.75). Moreover, the developed model also predicted the motion of the tibiofemoral joint in all degrees of freedom. This new model provides an important step toward the development of a realistic dynamic musculoskeletal total knee replacement model to predict in vivo knee joint motion and loading simultaneously. This could offer a better opportunity to establish a robust virtual modeling platform for future pre-clinical assessment of knee prosthesis designs, surgical procedures and post-operation rehabilitation.

Novel computational approaches characterizing knee physiotherapy

A knee joint's longevity depends on the proper integration of structural components in an axial alignment. If just one of the components is abnormally off-axis, the biomechanical system fails, resulting in arthritis. The complexity of various failures in the knee joint has led orthopedic surgeons to select total knee replacement as a primary treatment. In many cases, this means sacrificing much of an otherwise normal joint. Here, we review novel computational approaches to describe knee physiotherapy by introducing a new dimension of foot loading to the knee axis alignment producing an improved functional status of the patient. New physiotherapeutic applications are then possible by aligning foot loading with the functional axis of the knee joint during the treatment of patients with osteoarthritis.