A Dynamic Finite Element Analysis of Human Foot Complex in the Sagittal Plane during Level Walking

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%–33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning.     

Dynamic finite element knee simulation for evaluation of knee replacement mechanics

In vitro pre-clinical testing of total knee replacement (TKR) devices is a necessary step in the evaluation of new implant designs. Whole joint knee simulators, like the Kansas knee simulator (KKS), provide a controlled and repeatable loading environment for comparative evaluation of component designs or surgical alignment under dynamic conditions. Experimental testing, however, is time and cost prohibitive for design-phase evaluation of tens or hundreds of design variations. Experimentally-verified computational models provide an efficient platform for analysis of multiple components, sizes, and alignment conditions. The purpose of the current study was to develop and verify a computational model of a dynamic, whole joint knee simulator. Experimental internal-external and valgus-varus laxity tests, followed by dynamic deep knee bend and gait simulations in the KKS were performed on three cadaveric specimens. Specimen-specific finite element (FE) models of posterior-stabilized TKR were created from magnetic resonance images and CAD geometry. The laxity data was used to optimize mechanical properties of tibiofemoral soft-tissue structures on a specimen-specific basis. Each specimen was subsequently analyzed in a computational model of the experimental KKS, simulating both dynamic activities. The computational model represented all joints and actuators in the experimental setup, including a proportional-integral-derivative (PID) controller to drive quadriceps actuation. The computational model was verified against six degree-of-freedom patellofemoral (PF) and tibiofemoral (TF) kinematics and actuator loading during both deep knee bend and gait activities, with good agreement in trends and magnitudes between model predictions and experimental kinematics; differences were less than 1.8 mm and 2.2° for PF and TF translations and rotations. The whole joint FE simulator described in this study can be applied to investigate a wide range of clinical and research questions.     

Explicit finite element modeling of total knee replacement mechanics

Joint kinematics and contact mechanics dictate the success of current total knee replacement (TKR) devices. Efficient computer models present an effective way of evaluating these characteristics. Predicted contact stress and area due to articulations at the tibio-femoral and patello-femoral interfaces indicate potential clinical performance. Previous finite element (FE) knee models have generally been used to predict contact stresses and/or areas during static or quasi-static loading conditions. Explicit dynamic FE analyses have recently been used to efficiently predict TKR kinematics and contact mechanics during dynamic loading conditions. The objective of this study was to develop and experimentally validate an explicit FE TKR model that incorporates tibio-femoral and patello-femoral articulations. For computational efficiency, we developed rigid body analyses that can reasonably reproduce the kinematics, contact pressure distribution, and contact area of a fully deformable system. Results from the deformable model showed that the patello-femoral and tibio-femoral kinematics were in good agreement with experimental knee simulator measurements. Kinematic results from the rigid body analyses were nearly identical to those from the fully deformable model, and the contact pressure and contact area correlation was acceptable given the great reduction in analysis time. Component mesh density studied had little effect on the predicted kinematics, particularly for the patellar component, and small effects on the predicted contact pressure and area. These analyses have shown that, at low computational cost, a force-control dynamic simulation of a gait cycle can yield useful and predictable results.     

Rapid identification of elastic modulus of the interface tissue on dental implants surfaces using reduced-basis method and a neural network

This paper proposes a rapid inverse analysis approach based on the reduced-basis method (RBM) and neural network (NN) to identify the “unknown” elastic modulus (Young's modulus) of the interfacial tissue between a dental implant and the surrounding bones. In the present RBM–NN approach, a RBM model is first built to compute displacement responses of dental implant-bone structures subjected to a harmonic loading for a set of “assumed” Young's moduli. The RBM model is then used to train a NN model that is used for actual inverse analysis in real-time. Actual experimental measurements of displacement responses are fed into the trained NN model to inversely determine the “true” elastic modulus of the interfacial tissue. As an example, a physical model of dental implant-bone structure is built and inverse analysis is conducted to verify the present RBM–NN approach. Based on numerical simulation and actual experiments, it is confirmed that the identified results are very accurate, reliable, and the computational saving is very significant. The present RBM–NN approach is found robust and efficient for inverse material characterizations in noninvasive and/or nondestructive evaluations.     

Combined finite element and multibody musculoskeletal investigation of a fractured clavicle with reconstruction plate

This paper addresses the evaluation of clavicle fixation devices, by means of computational models. The aim was to develop a method for comparison of stress distribution in various fixation devices, to determine whether the use of multibody musculoskeletal input in such model is applicable and to report the approach. The focus was on realistic loading and the motivation for the work is that the treatment can be enhanced by a better understanding of the loading of the clavicle and fixation device. The method can be used to confirm the strength of customised plates, for optimisation of new plates and to complement experimental studies. A finite element (FE) mesh of the clavicle geometry was created from computed tomography data and imported into the FE solver where the model was subjected to muscle forces and other boundary conditions from a multibody musculoskeletal model performing a typical activity of daily life. A reconstruction plate and screws were also imported into the model. The combination models returned stresses and displacements of plausible magnitudes in all included parts and the result, upon further development and validation, may serve as a design guideline for improved clavicle fixation.     

Evaluating knee replacement mechanics during ADL with PID-controlled dynamic finite element analysis

Validated computational knee simulations are valuable tools for design phase development of knee replacement devices. Recently, a dynamic finite element (FE) model of the Kansas knee simulator was kinematically validated during gait and deep flexion cycles. In order to operate the computational simulator in the same manner as the experiment, a proportional–integral–derivative (PID) controller was interfaced with the FE model to control the quadriceps actuator excursion and produce a target flexion profile regardless of implant geometry or alignment conditions. The controller was also expanded to operate multiple actuators simultaneously in order to produce in vivo loading conditions at the joint during dynamic activities. Subsequently, the fidelity of the computational model was improved through additional muscle representation and inclusion of relative hip–ankle anterior–posterior (A–P) motion. The PID-controlled model was able to successfully recreate in vivo loading conditions (flexion angle, compressive joint load, medial–lateral load distribution or varus-valgus torque, internal–external torque, A–P force) for deep knee bend, chair rise, stance-phase gait and step-down activities.     

A multibody knee model with discrete cartilage prediction of tibio-femoral contact mechanics

Combining musculoskeletal simulations with anatomical joint models capable of predicting cartilage contact mechanics would provide a valuable tool for studying the relationships between muscle force and cartilage loading. As a step towards producing multibody musculoskeletal models that include representation of cartilage tissue mechanics, this research developed a subject-specific multibody knee model that represented the tibia plateau cartilage as discrete rigid bodies that interacted with the femur through deformable contacts. Parameters for the compliant contact law were derived using three methods: (1) simplified Hertzian contact theory, (2) simplified elastic foundation contact theory and (3) parameter optimisation from a finite element (FE) solution. The contact parameters and contact friction were evaluated during a simulated walk in a virtual dynamic knee simulator, and the resulting kinematics were compared with measured in vitro kinematics. The effects on predicted contact pressures and cartilage–bone interface shear forces during the simulated walk were also evaluated. The compliant contact stiffness parameters had a statistically significant effect on predicted contact pressures as well as all tibio-femoral motions except flexion–extension. The contact friction was not statistically significant to contact pressures, but was statistically significant to medial–lateral translation and all rotations except flexion–extension. The magnitude of kinematic differences between model formulations was relatively small, but contact pressure predictions were sensitive to model formulation. The developed multibody knee model was computationally efficient and had a computation time 283 times faster than a FE simulation using the same geometries and boundary conditions.     

Principles of determination and verification of muscle forces in the human musculoskeletal system: Muscle forces to minimise bending stress

While there are a growing number of increasingly complex methodologies available to model geometry and material properties of bones, these models still cannot accurately describe physical behaviour of the skeletal system unless the boundary conditions, especially muscular loading, are correct. Available in vivo measurements of muscle forces are mostly highly invasive and offer no practical way to validate the outcome of any computational model that predicts muscle forces. However, muscle forces can be verified indirectly using the fundamental property of living tissue to functional adaptation and finite element (FE) analysis. Even though the mechanisms of the functional adaptation are not fully understood, its result is clearly seen in the shape and inner structure of bones. The FE method provides a precise tool for analysis of the stress/strain distribution in the bone under given loading conditions. The present work sets principles for the determination of the muscle forces on the basis of the widely accepted view that biological systems are optimized light-weight structures with minimised amount of unloaded/underloaded material and hence evenly distributed loading throughout the structure. Bending loading of bones is avoided/compensated in bones under physiological loading. Thus, bending minimisation provides the basis for the determination of the musculoskeletal system loading. As a result of our approach, the muscle forces for a human femur during normal gait and sitting down (peak hip joint force) are obtained such that the bone is loaded predominantly in compression and the stress distribution in proximal and diaphyseal femur corresponds to the material distribution in bone.     

Comparison of deformable and elastic foundation finite element simulations for predicting knee replacement mechanics

Rigid body total knee replacement (TKR) models with tibiofemoral contact based on elastic foundation (EF) theory utilize simple contact pressure-surface overclosure relationships to estimate joint mechanics, and require significantly less computational time than corresponding deformable finite element (FE) methods. However, potential differences in predicted kinematics between these representations are currently not well understood, and it is unclear if the estimates of contact area and pressure are acceptable. Therefore, the objectives of the current study were to develop rigid EF and deformable FE models of tibiofemoral contact, and to compare predicted kinematics and contact mechanics from both representations during gait loading conditions with three different implant designs. Linear and nonlinear contact pressure-surface overclosure relationships based on polyethylene material properties were developed using EF theory. All other variables being equal, rigid body FE models accurately estimated kinematics predicted by fully deformable FE models and required only 2% of the analysis time. As expected, the linear EF contact model sufficiently approximated trends for peak contact pressures, but overestimated the deformable results by up to 30%. The nonlinear EF contact model more accurately reproduced trends and magnitudes of the deformable analysis, with maximum differences of approximately 15% at the peak pressures during the gait cycle. All contact area predictions agreed in trend and magnitude. Using rigid models, edge-loading conditions resulted in substantial overestimation of peak pressure. Optimal nonlinear EF contact relationships were developed for specific TKR designs for use in parametric or repetitive analyses where computational time is paramount. The explicit FE analysis method utilized here provides a unique approach in that both rigid and deformable analyses can be run from the same input file, thus enabling simple selection of the most appropriate representation for the analysis of interest.     

A novel in vivo mouse model for mechanically stimulated bone adaptation--a combined experimental and computational validation study

To facilitate the investigation of bone formation, in vivo, in response to mechanical loading a caudal vertebra axial compression device (CVAD) has been developed to deliver precise mechanical loads to the fifth caudal vertebra (C5) of the C57BL/6 female mouse. A combined experimental and computational approach was used to quantify the micro-mechanical strain induced in trabecular and cortical components following static and dynamic loading using the CVAD. Cortical bone strains were recorded using micro-strain gages. Finite element (FE) models based on micro-computed tomography were constructed for all C5 vertebrae. Both theoretical and experimental cortical strains correlated extremely well (R(2)>0.96) for a Young's modulus of 14.8 GPa, thus validating the FE model. In this study, we have successfully applied mechanical loads to the C5 murine vertebrae, demonstrating the potential of this model to be used for in vivo loading studies aimed at stimulating both trabecular and cortical bone adaptation.     

Computationally efficient modelling of hip replacement separation due to small mismatches in component centres of rotation

Patient imaging and explant analysis has shown evidence of edge loading of hard-on-hard hip replacements in vivo. Experimental hip simulator testing under edge loading conditions has produced increased, clinically-relevant, wear rates for hard-on-hard bearings when compared to concentric conditions. Such testing, however, is time consuming and costly. A quick running computational edge loading model (Python Edge Loading (PyEL) - quasi-static, rigid, frictionless), capable of considering realistic bearing geometries, was developed. The aim of this study was to produce predictions of separation within the typical experimental measurement error of ∼0.5 mm. The model was verified and validated against comparable finite element (FE) models (including inertia and friction) and pre-existing experimental test data for 56 cases, covering a variety of simulated cup orientations, positions, tissue tensions, and loading environments. The PyEL model agreed well with both the more complex computational modelling and experimental results. From comparison with the FE models, the assumption of no inertia had little effect on the maximum separation prediction. With high contact force cases, the assumption of no friction had a larger effect (up to ∼5% error). The PyEL model was able to predict the experimental maximum separations within ∼0.3 mm. It could therefore be used to optimise an experimental test plan and efficiently investigate a much wider range of scenarios and variables. It could also help explain trends and damage modes seen in experimental testing through identifying the contact locations on the liner that are not easily measured experimentally.     

Use of a statistical model of the whole femur in a large scale,multi-model study of femoral neck fracture risk

Interpatient variability is often overlooked in orthopaedic computational studies due to the substantial challenges involved in sourcing and generating large numbers of bone models. A statistical model of the whole femur incorporating both geometric and material property variation was developed as a potential solution to this problem. The statistical model was constructed using principal component analysis, applied to 21 individual computer tomography scans. To test the ability of the statistical model to generate realistic, unique, finite element (FE) femur models it was used as a source of 1000 femurs to drive a study on femoral neck fracture risk. The study simulated the impact of an oblique fall to the side, a scenario known to account for a large proportion of hip fractures in the elderly and have a lower fracture load than alternative loading approaches. FE model generation, application of subject specific loading and boundary conditions, FE processing and post processing of the solutions were completed automatically. The generated models were within the bounds of the training data used to create the statistical model with a high mesh quality, able to be used directly by the FE solver without remeshing. The results indicated that 28 of the 1000 femurs were at highest risk of fracture. Closer analysis revealed the percentage of cortical bone in the proximal femur to be a crucial differentiator between the failed and non-failed groups. The likely fracture location was indicated to be intertrochantic. Comparison to previous computational, clinical and experimental work revealed support for these findings.     

A finite element model of the lower limb during stance phase of gait cycle including the muscle forces

Background

Results of finite element (FE) analyses can give insight into musculoskeletal diseases if physiological boundary conditions, which include the muscle forces during specific activities of daily life, are considered in the FE modelling. So far, many simplifications of the boundary conditions are currently made. This study presents an approach for FE modelling of the lower limb for which muscle forces were included.

Methods

The stance phase of normal gait was simulated. Muscle forces were calculated using a musculoskeletal rigid body (RB) model of the human body, and were subsequently applied to a FE model of the lower limb. It was shown that the inertial forces are negligible during the stance phase of normal gait. The contact surfaces between the parts within the knee were modelled as bonded. Weak springs were attached to the distal tibia for numerical reasons.

Results

Hip joint reaction forces from the RB model and those from the FE model were similar in magnitude with relative differences less than 16%. The forces of the weak spring were negligible compared to the applied muscle forces. The maximal strain was 0.23% in the proximal region of the femoral diaphysis and 1.7% in the contact zone between the tibia and the fibula.

Conclusions

The presented approach based on FE modelling by including muscle forces from inverse dynamic analysis of musculoskeletal RB model can be used to perform analyses of the lower limb with very realistic boundary conditions. In the present form, this model can be used to better understand the loading, stresses and strains of bones in the knee area and hence to analyse osteotomy fixation devices.

     

Computational efficiency of numerical approximations of tangent moduli for finite element implementation of a fiber-reinforced hyperelastic material model

In this study, we evaluated computational efficiency of finite element (FE) simulations when a numerical approximation method was used to obtain the tangent moduli. A fiber-reinforced hyperelastic material model for nearly incompressible soft tissues was implemented for 3D solid elements using both the approximation method and the closed-form analytical method, and validated by comparing the components of the tangent modulus tensor (also referred to as the material Jacobian) between the two methods. The computational efficiency of the approximation method was evaluated with different perturbation parameters and approximation schemes, and quantified by the number of iteration steps and CPU time required to complete these simulations. From the simulation results, it can be seen that the overall accuracy of the approximation method is improved by adopting the central difference approximation scheme compared to the forward Euler approximation scheme. For small-scale simulations with about 10,000 DOFs, the approximation schemes could reduce the CPU time substantially compared to the closed-form solution, due to the fact that fewer calculation steps are needed at each integration point. However, for a large-scale simulation with about 300,000 DOFs, the advantages of the approximation schemes diminish because the factorization of the stiffness matrix will dominate the solution time. Overall, as it is material model independent, the approximation method simplifies the FE implementation of a complex constitutive model with comparable accuracy and computational efficiency to the closed-form solution, which makes it attractive in FE simulations with complex material models.     

Estimation of conditions evoking fracture in finger bones under pinch loading based on finite element analysis

A finger finite element (FE) model was created from CT images of a Japanese male in order to obtain a shape-biofidelic model. Material properties and articulation characteristics of the model were taken from the literature. To predict bone fracture and realistically represent the fracture pattern under various loading conditions, the ESI-Wilkins-Kamoulakos rupture model in PAM-CRASH (ESI Group S.A., Paris, France) was utilized in this study with parameter values of the rupture model determined by compression testing and simulation of porcine fibula. A finger pinch simulation was then conducted to validate the finger FE model. The force-displacement curve and fracture load from the pinch simulation was compared to the result of finger pinch test using cadavers. Simulation results are coincident with the test result, indicating that the finger FE model can be used in an analysis of finger bone fracture during pinch accident. With this model, several pinch simulations were conducted with different pinching object’s stiffness and pinching energy. Conditions for evoking finger bone fracture under pinch loading were then estimated based on these results. This study offers a novel method to predict possible hazards of manufactured goods during the design process, thus finger injury due to pinch loading can be avoided.     

Lumbar spine finite element model for healthy subjects: development and validation

Finite element (FE) method is a proven powerful and efficient tool to study the biomechanics of the human lumbar spine. However, due to the large inter-subject variability of geometries and material properties in human lumbar spines, concerns existed on the accuracy and predictive power of one single deterministic FE model with one set of spinal geometry and material properties. It was confirmed that the combined predictions (median or mean value) of several distinct FE models can be used as an improved prediction of behavior of human lumbar spine under identical loading and boundary conditions. In light of this improved prediction, five FE models (L1-L5 spinal levels) of the human lumbar spine were developed based on five healthy living subjects with identical modeling method. The five models were extensively validated through experimental and computational results in the literature. Mesh convergence and material sensitivity analysis were also conducted. We have shown that the results from the five FE models developed in this paper were consistent with the experimental data and simulation results from the existing literature. The validated modeling method introduced in this study can be used in modeling dysfunctional lumber spines such as disc degeneration and scoliosis in future work.     

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.     

Motion control of musculoskeletal systems with redundancy

Motion control of musculoskeletal systems for functional electrical stimulation (FES) is a challenging problem due to the inherent complexity of the systems. These include being highly nonlinear, strongly coupled, time-varying, time-delayed, and redundant. The redundancy in particular makes it difficult to find an inverse model of the system for control purposes. We have developed a control system for multiple input multiple output (MIMO) redundant musculoskeletal systems with little prior information. The proposed method separates the steady-state properties from the dynamic properties. The dynamic control uses a steady-state inverse model and is implemented with both a PID controller for disturbance rejection and an artificial neural network (ANN) feedforward controller for fast trajectory tracking. A mechanism to control the sum of the muscle excitation levels is also included. To test the performance of the proposed control system, a two degree of freedom ankle–subtalar joint model with eight muscles was used. The simulation results show that separation of steady-state and dynamic control allow small output tracking errors for different reference trajectories such as pseudo-step, sinusoidal and filtered random signals. The proposed control method also demonstrated robustness against system parameter and controller parameter variations. A possible application of this control algorithm is FES control using multiple contact cuff electrodes where mathematical modeling is not feasible and the redundancy makes the control of dynamic movement difficult.     

Finite element modeling of α-helices and tropocollagen molecules referring to spike of SARS-CoV-2

The newly developed finite element (FE) modeling at the atomic scale was used to predict the static and dynamic response of the α-helix (AH) and tropocollagen (TC) protein fragments, the main building blocks of the spike of the SARS-CoV-2. The geometry and morphology of the spike’s stalk and its connection to the viral envelope were determined from the combination of most recent molecular dynamics (MD) simulation and images of cryoelectron microscopy. The stiffness parameters of the covalent bonds in the main chain of the helix were taken from the literature. The AH and TC were modeled using both beam elements (wire model) and shell elements (ribbon model) in FE analysis to predict their mechanical properties under tension. The asymptotic stiffening features of AH and TC under tensile loading were revealed and compared with a new analytical solution. The mechanical stiffnesses under other loading conditions, including compression, torsion, and bending, were also predicted numerically and correlated with the results of the existing MD simulations and tests. The mode shapes and natural frequencies of the spike were predicted using the built FE model. The frequencies were shown to be within the safe range of 1–20 MHz routinely used for medical imaging and diagnosis by means of ultrasound. These results provide a solid theoretical basis for using ultrasound to study damaging coronavirus through transient and resonant vibration at large deformations.     

Implementation and validation of probabilistic models of the anterior longitudinal ligament and posterior longitudinal ligament of the cervical spine

The objective of this investigation was to develop probabilistic finite element (FE) models of the anterior longitudinal ligament (ALL) and posterior longitudinal ligament (PLL) of the cervical spine that incorporate the natural variability of biological specimens. In addition to the model development, a rigorous validation methodology was developed to quantify model performance. Experimental data for the geometry and dynamic properties of the ALL and PLL were used to create probabilistic FE models capable of predicting not only the mean dynamic relaxation response but also the observed experimental variation of that response. The probabilistic FE model uses a quasilinear viscoelastic material constitutive model to capture the time-dependent behaviour of the ligaments. The probabilistic analysis approach yields a statistical distribution for the model-predicted response at each time point rather than a single deterministic quantity (e.g. ligament force) and that response can be statistically compared to experimental data for validation. A quantitative metric that compares the cumulative distribution functions of the experimental data and model response is computed for both the ALL and PLL throughout the time histories and is used to quantify model performance.