Effect of boundary conditions,impact loading and hydraulic stiffening on femoral fracture strength

Patient specific quantitative CT (QCT) imaging data together with the finite element (FE) method may provide an accurate prediction of a patient's femoral strength and fracture risk. Although numerous FE models investigating femoral fracture strength have been published, there is little consent on the effect of boundary conditions, dynamic loading and hydraulic strengthening due to intra-medullary pressure on the predicted fracture strength. We developed a QCT-derived FE model of a proximal femur that included node-specific modulus assigned based on the local bone density. The effect of three commonly used boundary conditions published in literature were investigated by comparing the resulting strain field due to an applied fracture load. The models were also augmented with viscoelastic material properties and subject to a realistic impact load profile to determine the effect of dynamic loads on the strain field. Finally, the effect of hydraulic strengthening was investigated by including node specific permeability and performing a coupled pore diffusion and stress analysis of the FE model. Results showed that all boundary conditions yield the same strain field patterns, but peak strains were 22% lower and fracture load was 18% higher when loaded at the greater trochanter than when loaded at the femoral head. Comparison of the dynamic models showed that material viscoelasticity was important, but inertial effects (vibration and shock) were not. Finally, pore pressure changes did not cause significant hydraulic strengthening of bone under fall impact loading.     

Proposing a Radial Basis Function and CSDM Indices to Predict the Traumatic Brain Injury Risk

BackgroundMany head injury indices and finite element (FE) head models have been proposed to predict traumatic brain injury (TBI). Although FE head models are suitable methods with high accuracy, they are computationally intensive. Head motion-based brain injury criteria are usually fast tools with lower accuracy. So, the objective of this study is to propose new criteria along with an artificial neural network model to predict TBI risks, which can be fast and accurate.MethodsFor this purpose, 250 FE head simulations have been carried out at 5 magnitudes and 50 rotational impact directions using the SIMon model. The effects of directions and magnitudes of rotational impacts were assessed for cumulative strain damage measure (CSDM) values. Next, statistical analysis and neural network were applied to predict CSDM values.ResultsThe results of the present research showed that the direction of rotation in the sagittal and frontal planes had a considerable effect on the CSDM values. Furthermore, new brain injury indices and a radial basis function neural network have been proposed to predict CSDM values which having high correlation coefficients with SIMon responses.ConclusionsThe results of this research demonstrated that rotational impact directions should be used to develop new head injury criteria being able to predict CSDM values. However, findings of present research proved that head motion-based brain injury criteria and RBF network can be used to predict FE head model responses with high speed and accuracy.     

The peculiar properties of the falx and tentorium in brain injury biomechanics

The influence of the falx and tentorium on brain injury biomechanics during impact was studied with finite element (FE) analysis. Three detailed 3D FE head models were created based on the images of a healthy, normal size head. Two of the models contained the addition of falx and tentorium with material properties from previously published experiments. Impact loadings from a reconstructed concussive case in a sport accident were applied to the two players involved. The results suggested that the falx and tentorium could induce large strains to the surrounding brain tissues, especially to the corpus callosum and brainstem. The tentorium seemed to constrain the motion of the cerebellum while inducing large strain in the brainstem in both players involved in the accident (one player had mainly coronal head rotation and the other had both coronal and transversal rotations). Since changed strain levels were observed in the brainstem and corpus callosum, which are classical sites for diffuse axonal injuries (DAI), we confirmed the importance of using accurate material properties for falx and tentorium in a FE head model when studying traumatic brain injuries.     

The importance of nonlinear tissue modelling in finite element simulations of infant head impacts

Despite recent efforts on the development of finite element (FE) head models of infants, a model capable of capturing head responses under various impact scenarios has not been reported. This is hypothesized partially attributed to the use of simplified linear elastic models for soft tissues of suture, scalp and dura. Orthotropic elastic constants are yet to be determined to incorporate the direction-specific material properties of infant cranial bone due to grain fibres radiating from the ossification centres. We report here on our efforts in advancing the above-mentioned aspects in material modelling in infant head and further incorporate them into subject-specific FE head models of a newborn, 5- and 9-month-old infant. Each model is subjected to five impact tests (forehead, occiput, vertex, right and left parietal impacts) and two compression tests. The predicted global head impact responses of the acceleration–time impact curves and the force–deflection compression curves for different age groups agree well with the experimental data reported in the literature. In particular, the newly developed Ogden hyperelastic model for suture, together with the nonlinear modelling of scalp and dura mater, enables the models to achieve more realistic impact performance compared with linear elastic models. The proposed approach for obtaining age-dependent skull bone orthotropic material constants counts both an increase in stiffness and decrease in anisotropy in the skull bone—two essential biological growth parameters during early infancy. The profound deformation of infant head causes a large stretch at the interfaces between the skull bones and the suture, suggesting that infant skull fractures are likely to initiate from the interfaces; the impact angle has a profound influence on global head impact responses and the skull injury metrics for certain impact locations, especially true for a parietal impact.     

Hemiarthroplasty of hip joint: An experimental validation using porcine acetabulum

Biphasic properties of articular cartilage allow it to be an excellent bearing material and have been studied through several simplified experiments as well as finite element modelling. However, three-dimensional biphasic finite element (FE) models of the whole joint are rare. The current study was carried out to experimentally validate FE methodology for modelling hemiarthroplasty. Material properties such as equilibrium elastic modulus and permeability of porcine acetabular cartilage were initially derived by curve-fitting an experimental deformation curve with that obtained using FE. These properties were then used in the hemiarthroplasty hip joint modelling. Each porcine acetabular cup was loaded with 400N using a 34mm diameter CoCr femoral head. A specimen-specific FE model of each acetabular cup was created using μCT and a series of software processes. Each model was analysed under conditions similar to those tested experimentally. Contact stresses and contact areas predicted by the model, immediately after loading, were then compared with the corresponding experimentally measured values. Very high peak contact stresses (maximum experimental: 14.09MPa) were recorded. A maximum difference of 12.42% was found in peak contact stresses. The corresponding error for contact area was 20.69%. Due to a fairly good agreement in predicted and measured values of contact stresses and contact areas, the integrated methodology developed in this study can be used as a basis for future work. In addition, FE predicted total fluid load support was around 80% immediately after loading. This was lower than that observed in conforming contact problems involving biphasic cartilage and was due to a smaller local contact area and variable clearance making fluid exudation easier.     

Design and numerical implementation of a 3-D non-linear viscoelastic constitutive model for brain tissue during impact

Finite Element (FE) head models are often used to understand mechanical response of the head and its contents during impact loading in the head. Current FE models do not account for non-linear viscoelastic material behavior of brain tissue. We developed a new non-linear viscoelastic material model for brain tissue and implemented it in an explicit FE code. To obtain sufficient numerical accuracy for modeling the nearly incompressible brain tissue, deviatoric and volumetric stress contributions are separated. Deviatoric stress is modeled in a non-linear viscoelastic differential form. Volumetric behavior is assumed linearly elastic. Linear viscoelastic material parameters were derived from published data on oscillatory experiments, and from ultrasonic experiments. Additionally, non-linear parameters were derived from stress relaxation (SR) experiments at shear strains up to 20%. The model was tested by simulating the transient phase in the SR experiments not used in parameter determination (strains up to 20%, strain rates up to 8s(-1)). Both time- and strain-dependent behavior were predicted accurately (R2>0.96) for strain and strain rates applied. However, the stress was overestimated systematically by approximately 31% independent of strain(rate) applied. This is probably caused by limitations of the experimental data at hand.     

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.     

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.     

Variability of a three-dimensional finite element model constructed using magnetic resonance images of a knee for joint contact stress analysis

Magnetic resonance (MR) imaging has been widely used to evaluate the thickness and volume of articular cartilage both in vivo and in vitro. While morphological information on the cartilage can be obtained using MR images, image processing for extracting geometric boundaries of the cartilage may introduce variations in the thickness of the cartilage. To evaluate the variability of using MR images to construct finite element (FE) knee cartilage models, five investigators independently digitized the same set of MR images of a human knee. The topology of cartilage thickness was determined using a minimal distance algorithm. Less than 8 percent variation in cartilage thickness was observed from the digitized data. The effect of changes in cartilage thickness on contact stress analysis was then investigated using five FE models of the knee. One FE model (average FE model) was constructed using the mean values of the digitized contours of the cartilage, and the other four were constructed by varying the thickness of the average FE model by +/- 5 percent and +/- 10 percent, respectively. The results demonstrated that under axial tibial compressive loading (up to 1,400 N), variations of cartilage thickness caused by digitization of MR images may result in a difference of approximately 10 percent in peak contact stresses (surface pressure, von Mises stress, and hydrostatic pressure) in the cartilage. A reduction of cartilage thickness caused increases of contact stresses, while an increase of cartilage thickness reduced contact stresses. Furthermore, the effect of variation of material properties of the cartilage on contact stress analysis was investigated. The peak contact stress increased almost linearly with the Young's modulus of the cartilage. The peak von Mises stress was dramatically reduced when the Poisson,s ratio was increased from 0.05 to 0.49 under an axial compressive load of 1,400 N, while peak hydrostatic pressure was dramatically increased. Peak surface pressure was also increased with the Poisson's ratio, but with a lower magnitude compared to von Mises stress and hydrostatic pressure. In conclusion, the imaging process may cause 10 percent variations in peak contact stress, and the predicted stress distribution is sensitive to the accuracy of the material properties of the cartilage model, especially to the variation of Poisson's ratio.     

Specimen-specific predictions of contact stress under physiological loading in the human hip: validation and sensitivity studies

Hip osteoarthritis may be initiated and advanced by abnormal cartilage contact mechanics, and finite element (FE) modeling provides an approach with the potential to allow the study of this process. Previous FE models of the human hip have been limited by single specimen validation and the use of quasi-linear or linear elastic constitutive models of articular cartilage. The effects of the latter assumptions on model predictions are unknown, partially because data for the instantaneous behavior of healthy human hip cartilage are unavailable. The aims of this study were to develop and validate a series of specimen-specific FE models, to characterize the regional instantaneous response of healthy human hip cartilage in compression, and to assess the effects of material nonlinearity, inhomogeneity and specimen-specific material coefficients on FE predictions of cartilage contact stress and contact area. Five cadaveric specimens underwent experimental loading, cartilage material characterization and specimen-specific FE modeling. Cartilage in the FE models was represented by average neo-Hookean, average Veronda Westmann and specimen- and region-specific Veronda Westmann hyperelastic constitutive models. Experimental measurements and FE predictions compared well for all three cartilage representations, which was reflected in average RMS errors in contact stress of less than 25 %. The instantaneous material behavior of healthy human hip cartilage varied spatially, with stiffer acetabular cartilage than femoral cartilage and stiffer cartilage in lateral regions than in medial regions. The Veronda Westmann constitutive model with average material coefficients accurately predicted peak contact stress, average contact stress, contact area and contact patterns. The use of subject- and region-specific material coefficients did not increase the accuracy of FE model predictions. The neo-Hookean constitutive model underpredicted peak contact stress in areas of high stress. The results of this study support the use of average cartilage material coefficients in predictions of cartilage contact stress and contact area in the normal hip. The regional characterization of cartilage material behavior provides the necessary inputs for future computational studies, to investigate other mechanical parameters that may be correlated with OA and cartilage damage in the human hip. In the future, the results of this study can be applied to subject-specific models to better understand how abnormal hip contact stress and contact area contribute to OA.     

Simulation-based assessment for construction helmets

In recent years, there has been a concerted effort for greater job safety in all industries. Personnel protective equipment (PPE) has been developed to help mitigate the risk of injury to humans that might be exposed to hazardous situations. The human head is the most vulnerable to impact as a moderate magnitude can cause serious injury or death. That is why industries have required the use of an industrial hard hat or helmet. There have only been a few articles published to date that are focused on the risk of head injury when wearing an industrial helmet. A full understanding of the effectiveness of construction helmets on reducing injury is lacking. This paper presents a simulation-based method to determine the threshold at which a human will sustain injury when wearing a construction helmet and assesses the risk of injury for wearers of construction helmets or hard hats. Advanced finite element, or FE, models were developed to study the impact on construction helmets. The FE model consists of two parts: the helmet and the human models. The human model consists of a brain, enclosed by a skull and an outer layer of skin. The level and probability of injury to the head was determined using both the head injury criterion (HIC) and tolerance limits set by Deck and Willinger. The HIC has been widely used to assess the likelihood of head injury in vehicles. The tolerance levels proposed by Deck and Willinger are more suited for finite element models but lack wide-scale validation. Different cases of impact were studied using LSTC's LS-DYNA.     

Development of a Finite Element Model of Decompressive Craniectomy

Decompressive craniectomy (DC), an operation whereby part of the skull is removed, is used in the management of patients with brain swelling. While the aim of DC is to reduce intracranial pressure, there is the risk that brain deformation and mechanical strain associated with the operation could damage the brain tissue. The nature and extent of the resulting strain regime is poorly understood at present. Finite element (FE) models of DC can provide insight into this applied strain and hence assist in deciding on the best surgical procedures. However there is uncertainty about how well these models match experimental data, which are difficult to obtain clinically. Hence there is a need to validate any modelling approach outside the clinical setting. This paper develops an axisymmetric FE model of an idealised DC to assess the key features of such an FE model which are needed for an accurate simulation of DC. The FE models are compared with an experimental model using gelatin hydrogel, which has similar poro-viscoelastic material property characteristics to brain tissue. Strain on a central plane of the FE model and the front face of the experimental model, deformation and load relaxation curves are compared between experiment and FE. Results show good agreement between the FE and experimental models, providing confidence in applying the proposed FE modelling approach to DC. Such a model should use material properties appropriate for brain tissue and include a more realistic whole head geometry.     

On the use of a patient-specific rapid-prototyped model to simulate the response of the human head to impact and comparison with analytical and finite element models

Every year, thousands of fatalities result from head injuries, the majority of which are sustained in automotive accidents. In this paper, an experimental study of the response of the human head to impact is presented. A rapid prototyped model of a human head was generated based on high-resolution magnetic resonance imaging (MRI) scan data. The physical model was subjected to low velocity impacts using a metallic pendulum and a sensitivity study was performed to explore the influence of various parameters, including mass and velocity of the impactor, on the response. The experimental response characteristics are compared with predictions from an analytical model as well as with numerical predictions from finite element (FE) models generated from the same MRI data set. The results from the experimental tests closely match those predicted by both the analytical and the FE models and thus provide us with substantive corroboration of all three approaches. The remarkable agreement obtained between the measured response characteristics of rapid-prototyped skulls and numerical (FE) models obtained from in vivo MRI data clearly demonstrates the potential use of rapid-prototyping to generate experimental models for head impact studies, and, more generally, for the study of the response of complex bio-structures to loading. In addition, the quantitative and qualitative accuracy of the predictions from the analytical model is clearly demonstrated by the FE and experimental corroboration. In particular, the analytical prediction that, as impact mass drops the impact duration becomes increasingly short, appears to be substantiated, which has important implications for the onset of high pressure and shear strain gradients in the brain with potentially deleterious effects.     

Finite element modeling for predicting the contact pressure between a foam mattress and the human body in a supine position

In this paper, we generated finite element (FE) models to predict the contact pressure between a foam mattress and the human body in a supine position. Twenty-year-old males were used for three-dimensional scanning to produce the FE human models, which was composed of skin and muscle tissue. A linear elastic isotropic material model was used for the skin, and the Mooney–Rivlin model was used for the muscle tissue because it can effectively represent the nonlinear behavior of muscle. The contact pressure between the human model and the mattress was predicted by numerical simulation. The human models were validated by comparing the body pressure distribution obtained from the same human subject when he was lying on two different mattress types. The experimental results showed that the slope of the lower part of the mattress caused a decrease in the contact pressure at the heels, and the effect of bone structure was most pronounced in the scapula. After inserting a simple structure to function as the scapula, the contact pressure predicted by the FE human models was consistent with the experimental body pressure distribution for all body parts. These results suggest that the models proposed in this paper will be useful to researchers and designers of products related to the prevention of pressure ulcers.     

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.     

Modified Bilston nonlinear viscoelastic model for finite element head injury studies

This paper proposes a modified nonlinear viscoelastic Bilston model (Bilston et al., 2001, Biorheol., 38, pp. 335-345). for the modeling of brain tissue constitutive properties. The modified model can be readily implemented in a commercial explicit finite element (FE) code, PamCrash. Critical parameters of the model have been determined through a series of rheological tests on porcine brain tissue samples and the time-temperature superposition (TTS) principle has been used to extend the frequency to a high region. Simulations by using PamCrash are compared with the test results. Through the use of the TTS principle, the mechanical and rheological behavior at high frequencies up to 10(4) rads may be obtained. This is important because the properties of the brain tissue at high frequencies and impact rates are especially relevant to studies of traumatic head injury. The averaged dynamic modulus ranges from 130 Pa to 1500 Pa and loss modulus ranges from 35 Pa to 800 Pa in the frequency regime studied (0.01 rads to 3700 rads). The errors between theoretical predictions and averaged relaxation test results are within 20% for strains up to 20%. The FEM simulation results are in good agreement with experimental results. The proposed model will be especially useful for application to FE analysis of the head under impact loads. More realistic analysis of head injury can be carried out by incorporating the nonlinear viscoelastic constitutive law for brain tissue into a commercial FE code.     

Effects of idealized joint geometry on finite element predictions of cartilage contact stresses in the hip

Computational models may have the ability to quantify the relationship between hip morphology, cartilage mechanics and osteoarthritis. Most models have assumed the hip joint to be a perfect ball and socket joint and have neglected deformation at the bone-cartilage interface. The objective of this study was to analyze finite element (FE) models of hip cartilage mechanics with varying degrees of simplified geometry and a model with a rigid bone material assumption to elucidate the effects on predictions of cartilage stress. A previously validated subject-specific FE model of a cadaveric hip joint was used as the basis for the models. Geometry for the bone-cartilage interface was either: (1) subject-specific (i.e. irregular), (2) spherical, or (3) a rotational conchoid. Cartilage was assigned either a varying (irregular) or constant thickness (smoothed). Loading conditions simulated walking, stair-climbing and descending stairs. FE predictions of contact stress for the simplified models were compared with predictions from the subject-specific model. Both spheres and conchoids provided a good approximation of native hip joint geometry (average fitting error ～0.5 mm). However, models with spherical/conchoid bone geometry and smoothed articulating cartilage surfaces grossly underestimated peak and average contact pressures (50% and 25% lower, respectively) and overestimated contact area when compared to the subject-specific FE model. Models incorporating subject-specific bone geometry with smoothed articulating cartilage also underestimated pressures and predicted evenly distributed patterns of contact. The model with rigid bones predicted much higher pressures than the subject-specific model with deformable bones. The results demonstrate that simplifications to the geometry of the bone-cartilage interface, cartilage surface and bone material properties can have a dramatic effect on the predicted magnitude and distribution of cartilage contact pressures in the hip joint.     

Can sulci protect the brain from traumatic injury?

The influence of sulci in dynamic finite element simulations of the human head has been investigated. First, a detailed 3D FE model was constructed based on an MRI scan of a human head. A second model with a smoothed brain surface was created based on the same MRI scan as the first FE model. These models were validated against experimental data to confirm their human-like dynamic responses during impact. The validated FE models were subjected to several acceleration impulses and the maximum principle strain and strain rate in the brain were analyzed. The results suggested that the inclusion of sulci should be considered for future FE head models as it alters the strain and strain distribution in an FE model.     

Statistical methods in finite element analysis

Finite element analysis (FEA) is a commonly used tool within many areas of engineering and can provide useful information in structural analysis of mechanical systems. However, most analyses within the field of biomechanics usually take no account either of the wide variation in material properties and geometry that may occur in natural tissues or manufacturing imperfections in synthetic materials. This paper discusses two different methods of incorporating uncertainty in FE models. The first, Taguchi's robust parameter design, uses orthogonal matrices to determine how to vary the parameters in a series of FE models, and provides information on the sensitivity of a model to input parameters. The second, probabilistic analysis, enables the distribution of a response variable to be determined from the distributions of the input variables. The methods are demonstrated using a simple example of an FE model of a beam that is assigned material properties and geometry over a range similar to an orthopaedic fixation plate. In addition to showing how each method may be used on its own, we also show how computational effort may be minimised by first identifying the most important input variables before determining the effects of imprecision.     

The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint

In finite element (FE) models knee ligaments can represented either by a group of one-dimensional springs, or by three-dimensional continuum elements based on segmentations. Continuum models closer approximate the anatomy, and facilitate ligament wrapping, while spring models are computationally less expensive. The mechanical properties of ligaments can be based on literature, or adjusted specifically for the subject. In the current study we investigated the effect of ligament modelling strategy on the predictive capability of FE models of the human knee joint. The effect of literature-based versus specimen-specific optimized material parameters was evaluated. Experiments were performed on three human cadaver knees, which were modelled in FE models with ligaments represented either using springs, or using continuum representations. In spring representation collateral ligaments were each modelled with three and cruciate ligaments with two single-element bundles. Stiffness parameters and pre-strains were optimized based on laxity tests for both approaches. Validation experiments were conducted to evaluate the outcomes of the FE models.Models (both spring and continuum) with subject-specific properties improved the predicted kinematics and contact outcome parameters. Models incorporating literature-based parameters, and particularly the spring models (with the representations implemented in this study), led to relatively high errors in kinematics and contact pressures. Using a continuum modelling approach resulted in more accurate contact outcome variables than the spring representation with two (cruciate ligaments) and three (collateral ligaments) single-element-bundle representations. However, when the prediction of joint kinematics is of main interest, spring ligament models provide a faster option with acceptable outcome.