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

Effect of Muscle Forces on Femur During Level Walking Using a Virtual Population of Older Women

Aging is associated with a greater risk of muscle and bone disorders such as sarcopenia and osteoporosis. These conditions substantially affect one's mobility and quality of life. In the past, muscles and bones are often studied separately using generic or scaled information that are not personal-specific, nor are they representative of the large variations seen in the elderly population. Consequently, the mechanical interaction between the aged muscle and bone is not well understood, especially when carrying out daily activities. This study presents a coupling approach across the body and the organ level, using fully personal-specific musculoskeletal and finite element models in order to study femoral loading during level walking. Variations in lower limb muscle volume/force were examined using a virtual population. These muscle forces were then applied to the finite element model of the femur to study the variations in predicted strains. The study shows that effective coupling across two scales can be carried out to study the muscle-bone interaction in elderly women. The generation of a virtual population is a feasible approach to augment anatomical variations based on a small population that could mimic variations seen in a larger cohort. This is a valuable alternative to overcome the limitation or the need to collect dataset from a large population, which is both time and resource consuming.

Muscle-driven simulations and experimental data of cycling

Muscle-driven simulations have provided valuable insights in studies of walking and running, but a set of freely available simulations and corresponding experimental data for cycling do not exist. The aim of this work was to develop a set of muscle-driven simulations of cycling and to validate them by comparison with experimental data. We used direct collocation to generate simulations of 16 participants cycling over a range of powers (40-216 W) and cadences (75-99 RPM) using two optimization objectives: a baseline objective that minimized muscle effort and a second objective that additionally minimized tibiofemoral joint forces. We tested the accuracy of the simulations by comparing the timing of active muscle forces in our baseline simulation to timing in experimental electromyography data. Adding a term in the objective function to minimize tibiofemoral forces preserved cycling power and kinematics, improved similarity between active muscle force timing and experimental electromyography, and decreased tibiofemoral joint reaction forces, which better matched previously reported in vivo measurements. The musculoskeletal models, muscle-driven simulations, simulation software, and experimental data are freely shared at https://simtk.org/projects/cycling_sim for others to reproduce these results and build upon this research.

Reproducibility in modeling and simulation of the knee: Academic, industry, and regulatory perspectives

Stakeholders in the modeling and simulation (M&S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled "Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives." The goal was to discuss efforts among these stakeholders to address irreproducibility in M&S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&S.

Model-Based Upper-Limb Gravity Compensation Strategies for Active Dynamic Arm Supports

NeuroMuscular Disorders (NMDs) may induce difficulties to perform daily life activities in autonomy. For people with NMDs affecting the upper-limb mobility, Dynamic Arm Supports (DASs) turn out to be relevant assistive devices. In particular, active DASs benefit from an external power source to support severely impaired people. However, commercially available active devices are controlled with push buttons, which add cognitive load and discomfort. To alleviate this issue, we propose a new force-based assistive control framework. In this preliminary work, we focus on the computation of a feedforward force to compensate upper-limb gravity. Four strategies based on a biomechanical model of the upper limb, tuned using anthropometric measurements, are proposed and evaluated. The first one is based on the potential energy of the upper-limb, the second one makes a compromise between the shoulder and elbow torques, the third one minimizes the sum of the squared user joint torques and the last one uses a probabilistic approach to minimize the expected torque norm in the presence of model uncertainties. These strategies have been evaluated quantitatively through an experiment including nine participants with an active DAS prototype. The activity of six muscles was measured and used to compute the Mean Effort Index (MEI) which represents the global effort required to maintain the pose. A statistical analysis shows that the four strategies significantly lower the MEI (p-value < 0.001).

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

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

Designing and in vitro testing of a novel patient-specific total knee prosthesis using the probabilistic approach

In order to prevent failure as well as ensure comfort, patient-specific modelling for prostheses has been gaining interest. However, deterministic analyses have been widely used in the design process without considering any variation/uncertainties related to the design parameters of such prostheses. Therefore, this study aims to compare the performance of patient-specific anatomic Total Knee Arthroplasty (TKA) with off-the-shelf TKA. In the patient-specific model, the femoral condyle curves were considered in the femoral component's inner and outer surface design. The tibial component was designed to completely cover the tibia cutting surface. In vitro experiments were conducted to compare these two models in terms of loosening of the components. A probabilistic approach based on the finite element method was also used to compute the probability of failure of both models. According to the deterministic analysis results, 103.10 and 21.67 MPa von Mises stress values were obtained for the femoral component and cement in the anatomical model, while these values were 175.86 and 25.76 MPa, respectively, for the conventional model. In order to predict loosening damage due to local osteolysis or stress shield, it was determined that the deformation values in the examined cement structures were 15% lower in the anatomical model. According to probabilistic analysis results, it was observed that the probability of encountering an extreme value for the anatomical model is far less than that of the conventional model. This indicates that the anatomical model is safer than the conventional model, considering the failure scenarios in this study.

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

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

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.

Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA

OBJECTIVE

This study proposes a computationally efficient method to quantify the effect of surgical inaccuracies on ligament strain in total knee arthroplasty (TKA). More specifically, this study describes a framework to determine the implant position and required surgical accuracy that results in a ligament balanced post-operative outcome with a probability of 90%.

METHODS

The response surface method is used to translate uncertainty in the implant position parameters to uncertainty in the ligament strain. The designed uncertainty quantification technique allows for an optimization with feasible computational cost towards the planned implant position and the tolerated surgical error for each of the twelve degrees of freedom of the implant position.

RESULTS

It is shown that the error does not allow for a ligament balanced TKA with a probability of 90% using preoperative planning. Six critical implant position parameters can be identified, namely AP translation, PD translation, VV rotation, IE rotation for the femoral component and PD translation, VV rotation for the tibial component.

CONCLUSION

We introduced an optimization process that allows for the computation of the required surgical accuracy for a ligament balanced postoperative outcome using preoperative planning with feasible computational cost.

SIGNIFICANCE

Towards the research society, the proposed method allows for a computationally efficient uncertainty quantification on a complex model. Towards surgical technique developers, six critical implant position parameters were identified, which should be the focus when refining surgical accuracy of TKA, leveraging better patient satisfaction.

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

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

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

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

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

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

Knee abduction moment is predicted by lower gluteus medius force and larger vertical and lateral ground reaction forces during drop vertical jump in female athletes

Prospective knee abduction moments measured during the drop vertical jump task identify those at increased risk for anterior cruciate ligament injury. The purpose of this study was to determine which muscle forces and frontal plane biomechanical features contribute to large knee abduction moments. Thirteen young female athletes performed three drop vertical jump trials. Subject-specific musculoskeletal models and electromyography-informed simulations were developed to calculate the frontal plane biomechanics and lower limb muscle forces. The relationships between knee abduction moment and frontal plane biomechanics were examined. Knee abduction moment was positively correlated to vertical (R = 0.522, P < 0.001) and lateral ground reaction forces (R = 0.395, P = 0.016), hip adduction angle (R = 0.358, P < 0.023) and lateral pelvic tilt (R = 0.311, P = 0.061). A multiple regression showed that knee abduction moment was predicted by reduced gluteus medius force and increased vertical and lateral ground reaction forces (P < 0.001, R² = 0.640). Hip adduction is indicative of lateral pelvic shift during landing. The coupled hip adduction and lateral pelvic tilt were associated to the increased vertical and lateral ground reaction forces, propagating into higher knee abduction moments. These biomechanical features are associated with ACL injury and may be limited in a landing with increased activation of the gluteus medius. Targeted neuromuscular training to control the frontal pelvic and hip motion may help to avoid injurious ground reaction forces and consequent knee abduction moment and ACL injury risk.

The association between periacetabular osteotomy reorientation and hip joint reaction forces in two subgroups of acetabular dysplasia

Acetabular dysplasia is primarily characterized by an altered acetabular geometry that results in deficient coverage of the femoral head, and is a known cause of hip osteoarthritis. Periacetabular osteotomy (PAO) is a surgical reorientation of the acetabulum to normalize coverage, yet its effect on joint loading is unknown. Our objective was to establish how PAO, simulated with a musculoskeletal model and probabilistic analysis, alters hip joint reaction forces (JRF) in two representative patients of two different acetabular dysplasia subgroups: anterolateral and posterolateral coverage deficiencies. PAO reorientation was simulated within the musculoskeletal model by adding three surgical degrees of freedom to the acetabulum relative to the pelvis (acetabular adduction, acetabular extension, medial translation of the hip joint center). Monte Carlo simulations were performed to generate 2000 unique PAO reorientations for each patient; from which 99% confidence bounds and sensitivity factors were calculated to assess the influence of input variability (PAO reorientation) on output (hip JRF) during gait. Our results indicate that reorientation of the acetabulum alters the lines of action of the hip musculature. Specifically, as the hip joint center was medialized, the moment arm of the hip abductor muscles was increased, which in turn increased the mechanical force-generating capacity of these muscles and decreased joint loading. Independent of subgroup, hip JRF was most sensitive to hip joint center medialization. Results from this study improve understanding of how PAO reorientation affects muscle function differently dependent upon acetabular dysplasia subgrouping and can be used to inform more targeted surgical interventions.

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

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

In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging

'Gold standard' reference sets of human muscle architecture are based on elderly cadaveric specimens, which are unlikely to be representative of a large proportion of the human population. This is important for musculoskeletal modeling, where the muscle force-generating properties of generic models are defined by these data but may not be valid when applied to models of young, healthy individuals. Obtaining individualized muscle architecture data in vivo is difficult, however diffusion tensor magnetic resonance imaging (DTI) has recently emerged as a valid method of achieving this. DTI was used here to provide an architecture data set of 20 lower limb muscles from 10 healthy adults, including muscle fiber lengths, which are important inputs for Hill-type muscle models commonly used in musculoskeletal modeling. Maximum isometric force and muscle fiber lengths were found not to scale with subject anthropometry, suggesting that these factors may be difficult to predict using scaling or optimization algorithms. These data also highlight the high level of anatomical variation that exists between individuals in terms of lower limb muscle architecture, which supports the need of incorporating subject-specific force-generating properties into musculoskeletal models to optimize their accuracy for clinical evaluation.

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate model sharing, and there are corresponding initiatives by the scientific journals. Outside the publishing enterprise, infrastructure to facilitate model sharing in biomechanics exists, and simulation software developers are interested in accommodating the community's needs for sharing of modeling resources. Encouragement for the use of standardized markups, concerns related to quality assurance, acknowledgement of increased burden, and importance of stewardship of resources are noted. In the short-term, it is advisable that the community builds upon recent strategies and experiments with new pathways for continued demonstration of model sharing, its promotion, and its utility. Nonetheless, the need for a long-term strategy to unify approaches in sharing computational models and related resources is acknowledged. Development of a sustainable platform supported by a culture of open model sharing will likely evolve through continued and inclusive discussions bringing all stakeholders at the table, e.g., by possibly establishing a consortium.

A Critical Analysis of TKR In Vitro Wear Tests Considering Predicted Knee Joint Loads

Detailed knowledge about loading of the knee joint is essential for preclinical testing of total knee replacement. Direct measurement of joint reaction forces is generally not feasible in a clinical setting; non-invasive methods based on musculoskeletal modelling should therefore be considered as a valid alternative to the standards guidelines. The aim of this paper is to investigate the possibility of using knee joint forces calculated through musculoskeletal modelling software for developing an in vitro wear assessment protocol by using a knee wear simulator. In particular, in this work we preliminarily show a comparison of the predicted knee joint forces (in silico) during the gait with those obtained from the ISO 14243-1/3 and with those measured in vivo by other authors. Subsequently, we compare the wear results obtained from a knee wear joint simulator loaded by calculated forces in correspondence to the “normal gait” kinematics with those obtained in correspondence to the loads imposed by the ISO. The obtained results show that even if the predicted load profiles are not totally in good agreement with the loads deriving from ISO standards and from in vivo measurements, they can be useful for in vitro wear tests, since the results obtained from the simulator in terms of wear are in agreement with the literature data.

Force and deformation transmission characteristics of a compliant tendon-sheath actuation system based on Hill-type muscle model

Artificial muscle is a kind of transmission actuator widely used in rehabilitation robots and wearable devices. However, there are some restrictions on the usage of these artificial muscles, including the short stroke length, complex structure, special power sources, and high nonlinear characteristics. Inspired by Hill-type muscle model, in this article, a new kind of artificial muscle using tendon-sheath and compliant springs is proposed to perform muscle-like characteristics. Force and deformation transmission models are proposed and validated by simulations and experiments. The experimental and simulation output results show nice goodness-of-fit and the R-square values are 0.9876 and 0.9046, respectively. Moreover, experiments are carried out in groups to analyze the transmission characteristics using different parameters, including variations of series springs, velocities, tendon diameters, and bending angles. The best R-square value of force-elongation curve and fitness curve could reach 0.9845, which indicates that the transmission model of the compliant artificial muscle can be used to express the transmission characteristics of the skeleton muscles.

Determining Subject-Specific Lower-Limb Muscle Architecture Data for Musculoskeletal Models Using Diffusion Tensor Imaging

Accurate individualized muscle architecture data are crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor imaging (DTI) magnetic resonance (MR) imaging has emerged as a promising method of gathering muscle architecture data in vivo; however, its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here, we provide a validation of the method of using anatomical magnetic resonance imaging (MRI) and DTI to gather muscle architecture data in vivo by directly comparing those data obtained from MR scans of three human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences, respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.

A screening method to analyse the sensitivity of a lower limb multibody kinematic model

The study presents a screening method used to identify the influential parameters of a lower limb model including ligaments, at low numerical cost. Concerning multibody kinematics optimisation, the ligament parameters (isometric length) were found the most influential ones in a previous study. The screening method tested if they remain influential with minimised length variations. The most important parameters for tibiofemoral kinematics were the skin markers, segment lengths and joint parameters, including two ligaments. This was confirmed by a quantitative sensitivity analysis. The screening method has the potential to be used as a stand-alone procedure for a sensitivity analysis.

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

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

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.

A computationally efficient strategy to estimate muscle forces in a finite element musculoskeletal model of the lower limb

Concurrent multiscale simulation strategies are required in computational biomechanics to study the interdependence between body scales. However, detailed finite element models rarely include muscle recruitment due to the computational burden of both the finite element method and the optimization strategies widely used to estimate muscle forces. The aim of this study was twofold: first, to develop a computationally efficient muscle force prediction strategy based on proportional-integral-derivative (PID) controllers to track gait and chair rise experimental joint motion with a finite element musculoskeletal model of the lower limb, including a deformable knee representation with 12 degrees of freedom; and, second, to demonstrate that the inclusion of joint-level deformability affects muscle force estimation by using two different knee models and comparing muscle forces between the two solutions. The PID control strategy tracked experimental hip, knee, and ankle flexion/extension with root mean square errors below 1°, and estimated muscle, contact and ligament forces in good agreement with previous results and electromyography signals. Differences up to 11% and 20% in the vasti and biceps femoris forces, respectively, were observed between the two knee models, which might be attributed to a combination of differing joint contact geometry, ligament behavior, joint kinematics, and muscle moment arms. The tracking strategy developed in this study addressed the inevitable tradeoff between computational cost and model detail in musculoskeletal simulations and can be used with finite element musculoskeletal models to efficiently estimate the interdependence between muscle forces and tissue deformation.

In vivo comparison of medialized dome and anatomic patellofemoral geometries using subject-specific computational modeling

Successful outcome following total knee arthroplasty (TKA) with patella resurfacing is partly determined by the restoration of patellofemoral (PF) function and recovery of the quadriceps mechanism. The current study compared two patellar TKA geometries (medialized dome and anatomic) to determine their impact on PF mechanics and quadriceps function. In-vivo, subject-specific patellar mechanics were evaluated using a sequential experimental and modeling approach. First, stereo radiography, marker-based motion capture, and force plate data were collected for TKA patients (10 dome, 10 anatomic) performing a knee extension and lunge. Second, subject-specific, whole-body, musculoskeletal models, including 6 degrees-of-freedom (DOF) knee joint kinematics, were created for each subject and activity to predict quadriceps forces. Last, finite element models of each subject and activity were created to predict PF kinematics, patellar loading, moment arm, and patellar tendon angle. Differences in mechanics between dome and anatomic patients were highlighted during load-bearing (lunge) activity. Anatomic subjects demonstrated greater PF flexion angles (avg. 11 ± 3°) compared to dome subjects during lunge. Similar to the natural knee, contact locations on the patella migrated inferior to superior as the knee flexed in anatomic subjects, but remained relatively superior in dome subjects. Differences in kinematics and contact location likely contributed to altered mechanics with anatomic subjects presenting greater load transfer from the quadriceps to the patellar tendon in deep flexion (>75°), and dome subjects demonstrating larger contact forces during lunge. Although there was substantial patient variability, evaluations of PF mechanics suggested improved quadriceps function and more natural kinematics in the anatomic design. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1910-1918, 2018.

The interaction of muscle moment arm, knee laxity, and torque in a multi-scale musculoskeletal model of the lower limb

INTRODUCTION

Musculoskeletal modeling allows insight into the interaction of muscle force and knee joint kinematics that cannot be measured in the laboratory. However, musculoskeletal models of the lower extremity commonly use simplified representations of the knee that may limit analyses of the interaction between muscle forces and joint kinematics. The goal of this research was to demonstrate how muscle forces alter knee kinematics and consequently muscle moment arms and joint torque in a musculoskeletal model of the lower limb that includes a deformable representation of the knee.

METHODS

Two musculoskeletal models of the lower limb including specimen-specific articular geometries and ligament deformability at the knee were built in a finite element framework and calibrated to match mean isometric torque data collected from 12 healthy subjects. Muscle moment arms were compared between simulations of passive knee flexion and maximum isometric knee extension and flexion. In addition, isometric torque results were compared with predictions using simplified knee models in which the deformability of the knee was removed and the kinematics at the joint were prescribed for all degrees of freedom.

RESULTS

Peak isometric torque estimated with a deformable knee representation occurred between 45° and 60° in extension, and 45° in flexion. The maximum isometric flexion torques generated by the models with deformable ligaments were 14.6% and 17.9% larger than those generated by the models with prescribed kinematics; by contrast, the maximum isometric extension torques generated by the models were similar. The change in hamstrings moment arms during isometric flexion was greater than that of the quadriceps during isometric extension (a mean RMS difference of 9.8 mm compared to 2.9 mm, respectively).

DISCUSSION

The large changes in the moment arms of the hamstrings, when activated in a model with deformable ligaments, resulted in changes to flexion torque. When simulating human motion, the inclusion of a deformable joint in a multi-scale musculoskeletal finite element model of the lower limb may preserve the realistic interaction of muscle force with knee kinematics and torque.

Force Closure Mechanism Modeling for Musculoskeletal Multibody Simulation

OBJECTIVE

Neuro-musculoskeletal multibody simulation (NMBS) seeks to optimize decision-making for patients with neuro-musculoskeletal disorders. In clinical practice, however, the inter-subject variability and the inaccessibility for experimental testing impede the reliable model identification. These limitations motivate the novel modeling approach termed as force closure mechanism modeling (FCM²).

METHODS

FCM ² expresses the dynamics between mutually articulating joint partners with respect to instantaneous screw axes (ISA) automatically reconstructed from their relative velocity state. Thereby, FCM² reduces arbitrary open-chain multibody topologies to force closure n-link pendulums. Within a computational validation study on the human knee joint with implemented contact surfaces, we examine FCM² as an underlying inverse dynamic model for computed muscle control. We evaluate predicted tibiofemoral joint quantities, i.e., kinematics and contact forces along with muscle moment arms, during muscle-induced knee motion against the classic hinge joint model and experimental studies.

RESULTS

Our NMBS study provided the proof-of-principle of the novel modeling approach. FCM² freed us from assuming a certain joint formulation while correctly predicting the joint dynamics in agreement with the established methods. Although experimental results were closely predicted, owing to noise in the ISA estimation, muscle moment arms were overestimated (R_ISA = 0.84 < R_HINGE = 0.97, RMSE_ISA = 13.18 mm > RMSE_HINGE = 6.54 mm), identifying the robust ISA estimation as key to FCM².

CONCLUSION

FCM² automatically derives the equations of motion in closed form. Moreover, it captures subject-specific joint function and, thereby, minimizes modeling and parameterization efforts.

SIGNIFICANCE

Model derivation becomes driven by quantitative data available in clinical settings so that FCM² yields a promising framework toward subject-specific NMBS.

The Effects of Prosthesis Inertial Parameters on Inverse Dynamics: A Probabilistic Analysis

Joint kinetic measurement is a fundamental tool used to quantify compensatory movement patterns in participants with transtibial amputation (TTA). Joint kinetics are calculated through inverse dynamics (ID) and depend on segment kinematics, external forces, and both segment and prosthetic inertial parameters (PIPS); yet the individual influence of PIPs on ID is unknown. The objective of this investigation was to assess the importance of parameterizing PIPs when calculating ID using a probabilistic analysis. A series of Monte Carlo simulations were performed to assess the influence of uncertainty in PIPs on ID. Multivariate input distributions were generated from experimentally measured PIPs (foot/shank: mass, center of mass (COM), moment of inertia) of ten prostheses and output distributions were hip and knee joint kinetics. Confidence bounds (2.5–97.5%) and sensitivity of outputs to model input parameters were calculated throughout one gait cycle. Results demonstrated that PIPs had a larger influence on joint kinetics during the swing period than the stance period (e.g., maximum hip flexion/extension moment confidence bound size: stance = 5.6 N·m, swing: 11.4 N·m). Joint kinetics were most sensitive to shank mass during both the stance and swing periods. Accurate measurement of prosthesis shank mass is necessary to calculate joint kinetics with ID in participants with TTA with passive prostheses consisting of total contact carbon fiber sockets and dynamic elastic response feet during walking.

How Can We Use Computational Modeling to Improve Total Knee Arthroplasty? Modeling Stability and Mobility in the Implanted Knee

Validated computational models promise a virtual platform to create optimal articular surfaces that best achieve desired implant characteristics. Today, designers can parametrically define the primary geometric features of an implant, and automatically modify design variables until stability/mobility performance objectives are best achieved. This preclinical, virtual design iteration minimizes the development cycle compared with testing physical prototypes and, by evaluating a broader scope of design concepts, likely improves the clinical performance of the final product. However, the scenario described is not without shortcomings and requires thorough understanding of the capabilities and the limitations of the models used. Although models typically represent the articular interface well, the interaction with the patient and the surgical process includes significant variability and increase in complexity. We present current modeling capabilities for the estimation of implant stability/mobility, with further suggestions for answering the difficult question of how an implant might perform throughout the population.

Subject-specific musculoskeletal modeling in the evaluation of shoulder muscle and joint function

Upper limb muscle force estimation using Hill-type muscle models depends on musculotendon parameter values, which cannot be readily measured non-invasively. Generic and scaled-generic parameters may be quickly and easily employed, but these approaches do not account for an individual subject's joint torque capacity. The objective of the present study was to develop a subject-specific experimental testing and modeling framework to evaluate shoulder muscle and joint function during activities of daily living, and to assess the capacity of generic and scaled-generic musculotendon parameters to predict muscle and joint function. Three-dimensional musculoskeletal models of the shoulders of 6 healthy subjects were developed to calculate muscle and glenohumeral joint loading during abduction, flexion, horizontal flexion, nose touching and reaching using subject-specific, scaled-generic and generic musculotendon parameters. Muscle and glenohumeral joint forces calculated using generic and scaled-generic models were significantly different to those of subject-specific models (p<0.05), and task dependent; however, scaled-generic model calculations of shoulder glenohumeral joint force demonstrated better agreement with those of subject-specific models during abduction and flexion. Muscles in generic musculoskeletal models operated further from the plateau of their force-length curves than those of scaled-generic and subject-specific models, while muscles in subject-specific models operated over a wider region of their force length curves than those of the generic or scaled-generic models, reflecting diversity of subject shoulder strength. The findings of this study suggest that generic and scaled-generic musculotendon parameters may not provide sufficient accuracy in prediction of shoulder muscle and joint loading when compared to models that employ subject-specific parameter-estimation approaches.

Dependence of Muscle Moment Arms on In Vivo Three-Dimensional Kinematics of the Knee

Quantification of muscle moment arms is important for clinical evaluation of muscle pathology and treatment, and for estimating muscle and joint forces in musculoskeletal models. Moment arms estimated with musculoskeletal models often assume a default motion of the knee derived from measurements of passive cadaveric flexion. However, knee kinematics are unique to each person and activity. The objective of this study was to estimate moment arms of the knee muscles with in vivo subject- and activity-specific kinematics from seven healthy subjects performing seated knee extension and single-leg lunge to show changes between subjects and activities. 3D knee motion was measured with a high-speed stereo-radiography system. Moment arms of ten muscles were estimated in OpenSim by replacing the default knee motion with in vivo measurements. Estimated inter-subject moment arm variability was similar to previously reported in vitro measurements. RMS deviations up to 9.0 mm (35.2% of peak value) were observed between moment arms estimated with subject-specific knee extension and passive cadaveric motion. The degrees of freedom that most impacted inter-activity differences were superior/inferior and anterior/posterior translations. Musculoskeletal simulations used to estimate in vivo muscle forces and joint loads may provide significantly different results when subject- and activity-specific kinematics are implemented.

Subject-specific modeling of muscle force and knee contact in total knee arthroplasty

Understanding the mechanical loading environment and resulting joint mechanics for activities of daily living in total knee arthroplasty is essential to continuous improvement in implant design. Although survivorship of these devices is good, a substantial number of patients report dissatisfaction with the outcome of their procedure. Knowledge of in vivo kinematics and joint loading will enable improvement in preclinical assessment and refinement of implant geometry. The purpose of this investigation was to describe the mechanics of total knee arthroplasty during a variety of activities of daily living (gait, walking down stairs, and chair rise/sit). Estimates of muscle forces, tibial contact load, location, and pressure distribution was performed through a combination of mobile fluoroscopy data collection, musculoskeletal modeling, and finite element simulation. For the activities evaluated, joint compressive load was greatest during walking down stairs; however, the highest contact pressure occurred during chair rise/sit. The joint contact moment in the frontal plane was mainly varus for gait and walking down stairs, while it was valgus during chair rise/sit. Excursion of the center of pressure on the tibial component was similar during each activity and between the medial and lateral sides. The main determinants of center of pressure location were internal-external rotation, joint load, and tibial insert conformity. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1576-1587, 2016.