A mass-length scaling law for modeling muscle strength in the lower limb

Musculoskeletal computer models are often used to study muscle function in children with and without impaired mobility. Calculations of muscle forces depend in part on the assumed strength of each muscle, represented by the peak isometric force parameter, which is usually based on measurements obtained from cadavers of adult donors. The aim of the present study was twofold: first, to develop a method for scaling lower-limb peak isometric muscle forces in typically-developing children; and second, to determine the effect of this scaling method on model calculations of muscle forces obtained for normal gait. Muscle volumes were determined from magnetic resonance (MR) images obtained from ten children aged from 7 to 13yr. A new mass-length scaling law was developed based on the assumption that muscle volume and body mass are linearly related, which was confirmed by the obtained volume and body mass data. Two musculoskeletal models were developed for each subject: one in which peak isometric muscle forces were estimated using the mass-length scaling law; and another in which these parameters were determined directly from the MR-derived muscle volumes. Musculoskeletal modeling and quantitative gait analysis were then used to calculate lower-limb muscle forces in normal walking. The patterns of muscle forces predicted by the model with scaled peak isometric force values were similar to those predicted by the MR-based model, implying that assessments of muscle function obtained from these two methods are practically equivalent. These results support the use of mass-length scaling in the development of subject-specific musculoskeletal models of children.     

Subject-specific musculoskeletal modelling in patients before and after total hip arthroplasty*

The goal of this study was to define the effect on hip contact forces of including subject-specific moment generating capacity in the musculoskeletal model by scaling isometric muscle strength and by including geometrical information in control subjects, hip osteoarthritis and total hip arthroplasty patients. Scaling based on dynamometer measurements decreased the strength of all flexor and abductor muscles. This resulted in a model that lacked the capacity to generate joint moments required during functional activities. Scaling muscle forces based on functional activities and inclusion of MRI-based geometrical detail did not compromise the model strength and resulted in hip contact forces comparable to previously reported measured contact forces.     

Evaluation of a method to scale muscle strength for gait simulations of children with cerebral palsy

Cerebral palsy (CP) is a neurological disorder that results in life-long mobility impairments. Musculoskeletal models used to investigate mobility deficits for children with CP often lack subject-specific characteristics such as altered muscle strength, despite a high prevalence of muscle weakness in this population. We hypothesized that incorporating subject-specific strength scaling within musculoskeletal models of children with CP would improve accuracy of muscle excitation predictions in walking simulations. Ten children (13.5 ± 3.3 years; GMFCS level II) with spastic CP participated in a gait analysis session where lower-limb kinematics, ground reaction forces, and bilateral electromyography (EMG) of five lower-limb muscles were collected. Isometric strength was measured for each child using handheld dynamometry. Three musculoskeletal models were generated for each child including a ‘Default’ model with the generic musculoskeletal model’s muscle strength, a ‘Uniform’ model with muscle strength scaled allometrically, and a ‘Custom’ model with muscle strength scaled based on handheld dynamometry strength measures. Muscle-driven gait simulations were generated using each model for each child. Simulation accuracy was evaluated by comparing predicted muscle excitations and measured EMG signals, both in the duration of muscle activity and the root-mean-square difference (RMSD) between signals. Improved agreement with EMG were found in both the ‘Custom’ and ‘Uniform’ models compared to the ‘Default’ model indicated by improvement in RMSD summed across all muscles, as well as RMSD and duration of activity for individual muscles. Incorporating strength scaling into musculoskeletal models can improve the accuracy of walking simulations for children with CP.     

Cycle time influences the development of muscle fatigue at low to moderate levels of intermittent muscle contraction

Localized muscle fatigue (LMF) during a repetitive task can be influenced by several aspects such as the level and duration of exertions. Among these aspects, though, the influence of cycle time remains unclear. Here, the effect of cycle time on LMF and performance was examined for a simple biomechanical system during repetitive static efforts. Participants performed 1-h trials of intermittent isometric index finger abduction with a duty cycle of 50% in all combinations of two cycle times (30 and 60 s) and two exertion levels (15% and 25% of maximum voluntary capacity). Measures of discomfort, performance (force fluctuations), and muscle capacity (voluntary strength and low-frequency twitch responses) were obtained, all of which demonstrated a beneficial effect of the 30 s cycle time. Specifically, the shorter cycle time led to lower rates of increase in perceived discomfort, lower rates of increase in force fluctuations, lower rates of decrease in voluntary capacity, and smaller changes in twitch responses. These benefits, reflecting less LMF development in the shorter cycle time, were quite consistent between genders and the two levels of effort. Results of this study can be used to modify current models predicting work–rest allowance and/or LMF, helping to enhance performance and reduce the risk of adverse musculoskeletal outcomes.     

Subject-specific hip geometry and hip joint centre location affects calculated contact forces at the hip during gait

Hip loading affects the development of hip osteoarthritis, bone remodelling and osseointegration of implants. In this study, we analyzed the effect of subject-specific modelling of hip geometry and hip joint centre (HJC) location on the quantification of hip joint moments, muscle moments and hip contact forces during gait, using musculoskeletal modelling, inverse dynamic analysis and static optimization. For 10 subjects, hip joint moments, muscle moments and hip loading in terms of magnitude and orientation were quantified using three different model types, each including a different amount of subject-specific detail: (1) a generic scaled musculoskeletal model, (2) a generic scaled musculoskeletal model with subject-specific hip geometry (femoral anteversion, neck-length and neck-shaft angle) and (3) a generic scaled musculoskeletal model with subject-specific hip geometry including HJC location. Subject-specific geometry and HJC location were derived from CT. Significant differences were found between the three model types in HJC location, hip flexion–extension moment and inclination angle of the total contact force in the frontal plane. No model agreement was found between the three model types for the calculation of contact forces in terms of magnitude and orientations, and muscle moments. Therefore, we suggest that personalized models with individualized hip joint geometry and HJC location should be used for the quantification of hip loading. For biomechanical analyses aiming to understand modified hip joint loading, and planning hip surgery in patients with osteoarthritis, the amount of subject-specific detail, related to bone geometry and joint centre location in the musculoskeletal models used, needs to be considered.     

Architectural properties of distal forelimb muscles in horses,Equus caballus

Articular injuries in athletic horses are associated with large forces from ground impact and from muscular contraction. To accurately and noninvasively predict muscle and joint contact forces, a detailed model of musculoskeletal geometry and muscle architecture is required. Moreover, muscle architectural data can increase our understanding of the relationship between muscle structure and function in the equine distal forelimb. Muscle architectural data were collected from seven limbs obtained from five thoroughbred and thoroughbred-cross horses. Muscle belly rest length, tendon rest length, muscle volume, muscle fiber length, and pennation angle were measured for nine distal forelimb muscles. Physiological cross-sectional area (PCSA) was determined from muscle volume and muscle fiber length. The superficial and deep digital flexor muscles displayed markedly different muscle volumes (227 and 656 cm3, respectively), but their PCSAs were very similar due to a significant difference in muscle fiber length (i.e., the superficial digital flexor muscle had very short fibers, while those of the deep digital flexor muscle were relatively long). The ulnaris lateralis and flexor carpi ulnaris muscles had short fibers (17.4 and 18.3 mm, respectively). These actuators were strong (peak isometric force, Fmax=5,814 and 4,017 N, respectively) and stiff (tendon rest length to muscle fiber length, LT:LMF=5.3 and 2.1, respectively), and are probably well adapted to stabilizing the carpus during the stance phase of gait. In contrast, the flexor carpi radialis muscle displayed long fibers (89.7 mm), low peak isometric force (Fmax=555 N), and high stiffness (LT:LMF=1.6). Due to its long fibers and low Fmax, flexor carpi radialis appears to be better adapted to flexion and extension of the limb during the swing phase of gait than to stabilization of the carpus during stance. Including muscle architectural parameters in a musculoskeletal model of the equine distal forelimb may lead to more realistic estimates not only of the magnitudes of muscle forces, but also of the distribution of forces among the muscles crossing any given joint.     

Robustness of kinematic weighting and scaling concepts for musculoskeletal simulation

Musculoskeletal modelling is widely used to estimate internal loading conditions. In order to optimise robustness and reduce errors between the subject-specific reference motion data (RMD) and the musculoskeletal simulation, 90 permutations of kinetic and kinematic data were analysed during split squats. A ranking for the scaling and kinematic weighting concepts based on the RMS errors when including functional centres of rotation (fCoRs), joint angles, and skin markers, revealed that analyses should include fCoR in the scaling and the simulation processes, as well as an automated weighting procedure including all attached skin markers for optimal registration of the musculoskeletal model to the RMD.     

Feasibility of using MRIs to create subject-specific parallel-mechanism joint models

Musculoskeletal models typically use generic 2D models for the tibiofemoral (TFJ) and patellofemoral (PFJ) joints, with a hinge talocrural joint (TCJ), which are scaled to each subject׳s bone dimensions. Alternatively joints’ measured kinematics in cadavers are well-predicted using 3D cadaver-specific models. These employ mechanisms constrained by the articulations of geometric objects fitted to the joint׳s surfaces.In this study, we developed TFJ, PFJ and TCJ mechanism-based models off MRIs for fourteen participants and compared the estimated kinematics with those from published studies modified to be consistent with mechanisms models and subject-specific anatomical landmarks. The models’ parameters were estimated by fitting spheres to segmented articular cartilage surfaces, while ligament attachment points were selected from their bony attachment regions.Each participant׳s kinematics were estimated by ensuring no length changes in ligaments and constant distances between spheres’ centres. Two parameters’ optimizations were performed; both avoid singularities and one best matches the kinematic patterns off published studies. Sensitivity analysis determined which parameters the models were sensitive to.With both optimization methods, kinematics did not present singularities but correlation values were higher, exceeding 0.6, when matching the published studies. However, ranges of motion (ROM) were different between estimated and published studies. Across participants, models presented large parameter variation. Small variations were found between estimated- and optimized-parameters, and in the estimated-rotations and translations’ means and ROM. Model results were sensitive to changes in distal tibia, talus and patella spheres’ centres. These models can be implemented in subject-specific rigid-body musculoskeletal models to estimate joint moments and loads.     

Atlas-based non-rigid image registration to automatically define line-of-action muscle models: A validation study

Research has raised a growing concern about the accuracy of rescaled generic musculoskeletal models for estimating a subject's musculoskeletal geometry. Information extracted from magnetic resonance (MR) images can improve the subject-specific detail and accuracy of musculoskeletal models. Nevertheless, methods that allow efficient, automated definition of subject-specific muscular models for use in biomechanical analysis of gait have not yet been published to the best of our knowledge. We report a novel method for automated definition of subject-specific muscle paths using non-rigid image registration between an atlas image and the subject's MR images. We validated this approach quantitatively by measuring the distance between automatically and manually defined coordinates of muscle attachment sites. Data was collected for 34 muscles in each lower limb of 5 paediatric subjects diagnosed with diplegic cerebral palsy and presenting varying degrees of increased femoral anteversion. Distances showed an overall median Euclidean error of 6.1 mm: 2.0 mm along the medio-lateral direction, 1.8 mm along the anterior–posterior direction and 3.8 mm along the superior–inferior direction. A qualitative validation between automatically defined muscle points and the muscular geometry observed in the subject's medical image data corroborated the quantitative validation. This automated approach followed by visual inspection and, if needed, correction to the muscle paths, reduced the time required for defining 34 lower-limb muscle paths from around 3.5 to 1 h. Furthermore, the method was also applicable to aberrant skeletal geometry. Using the proposed method, defining MR-based musculoskeletal models becomes a time efficient and more accurate alternative to rescaling generic models.     

Non-rigid deformation to include subject-specific detail in musculoskeletal models of CP children with proximal femoral deformity and its effect on muscle and contact forces during gait

To account for proximal femoral deformities in children with cerebral palsy (CP), subject-specific musculoskeletal models are needed. Non-rigid deformation (NRD) deforms generic onto personalized bone geometry and thereby transforms the muscle points. The goal of this study was to determine to what extent the models and simulation outcomes in CP patients differ when including subject-specific detail using NRD or Magnetic Resonance Imaging (MRI)-based models. The NRD models slightly overestimated hip contact forces compared to MRI models and differences in muscle point positions and moment arm lengths (MALs) remained, although differences were smaller than for the generic model.     

Level of subject-specific detail in musculoskeletal models affects hip moment arm length calculation during gait in pediatric subjects with increased femoral anteversion

Biomechanical parameters of gait such as muscle's moment arm length (MAL) and muscle-tendon length are known to be sensitive to anatomical variability. Nevertheless, most studies rely on rescaled generic models (RGMo) constructed from averaged data of cadaveric measurements in a healthy adult population. As an alternative, deformable generic models (DGMo) have been proposed. These models integrate a higher level of subject-specific detail by applying characteristic deformations to the musculoskeletal geometry. In contrast, musculoskeletal models based on magnetic resonance (MR) images (MRMo) reflect the involved subject's characteristics in every level of the model. This study investigated the effect of the varying levels of subject-specific detail in these three model types on the calculated hip MAL during gait in a pediatric population of seven cerebral palsy subjects presenting aberrant femoral geometry. Our results show large percentage differences in calculated MAL between RGMo and MRMo. Furthermore, the use of DGMo did not uniformly reduce inter-model differences in calculated MAL. The magnitude of these percentage differences stresses the need to take these effects into account when selecting the level of subject-specific detail one wants to integrate in musculoskeletal. Furthermore, the variability of these differences between subjects and between muscles makes it very difficult to a priori estimate their importance for a biomechanical analysis of a certain muscle in a given subject.     

Statistical shape modelling versus linear scaling: Effects on predictions of hip joint centre location and muscle moment arms in people with hip osteoarthritis

Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p = <0.001) and regression (31.2 ± 15 mm, p = <0.001) methods. The addition of complete pelvis imaging data to the shape modelling workflow further reduced HJC error estimates compared to no imaging (6.6 ± 3.1 mm, p = 0.002). Average RMSE were greatest for the hip flexor and extensor muscle groups using the functional (16.71 mm and 8.87 mm respectively) and regression methods (16.15 mm and 9.97 mm respectively). The effects on moment-arms were less substantial for the shape modelling methods, ranging from 0.05 to 3.2 mm. Shape modelling methods improved HJC location and muscle moment-arm estimates compared to linear scaling of musculoskeletal models in patients with hip osteoarthritis.     

Subject-specific musculoskeletal model of the lower limb in a lying and standing position

Accurate estimation of joint loads implies using subject-specific musculoskeletal models. Moreover, as the lines of action of the muscles are dictated by the soft tissues, which are in turn influenced by gravitational forces, we developed a method to build subject-specific models of the lower limb in a functional standing position. Bones and skin envelope were obtained in a standing position, whereas muscles and a set of bony landmarks were obtained from conventional magnetic resonance images in a lying position. These muscles were merged with the subject-specific skeletal model using a nonlinear transformation, taking into account soft tissue movements and gravitational effects. Seven asymptomatic lower limbs were modelled using this method, and results showed realistic deformations. Comparing the subject-specific skeletal model to a scaled reference model rendered differences in terms of muscle length up to 4% and in terms of moment arm for adductor muscles up to 30%. These preliminary findings enlightened the importance of subject-specific modelling in a functional position.     

Inter-individual variation in vertebral kinematics affects predictions of neck musculoskeletal models

Experimental studies have found significant variation in cervical intervertebral kinematics (IVK) among healthy subjects, but the effect of this variation on biomechanical properties, such as neck strength, has not been explored. The goal of this study was to quantify variation in model predictions of extension strength, flexion strength and gravitational demand (the ratio of gravitational load from the weight of the head to neck muscle extension strength), due to inter-subject variation in IVK. IVK were measured from sagittal radiographs of 24 subjects (14F, 10M) in five postures: maximal extension, mid-extension, neutral, mid-flexion, and maximal flexion. IVK were defined by the position (anterior-posterior and superior-inferior) of each cervical vertebra with respect to T1 and its angle with respect to horizontal, and fit with a cubic polynomial over the range of motion. The IVK of each subject were scaled and incorporated into musculoskeletal models to create models that were identical in muscle force- and moment-generating properties but had subject-specific kinematics. The effect of inter-subject variation in IVK was quantified using the coefficient of variation (COV), the ratio of the standard deviation to the mean. COV of extension strength ranged from 8% to 15% over the range of motion, but COV of flexion strength was 20–80%. Moreover, the COV of gravitational demand was 80–90%, because the gravitational demand is affected by head position as well as neck strength. These results indicate that including inter-individual variation in models is important for evaluating neck musculoskeletal biomechanical properties.     

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain–skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.

     

Musculoskeletal modeling of user groups for virtual product and process development

Abstract

Although biomechanical digital human models find their way into virtual engineering processes, biomechanical considerations are currently still unrecognized to a large extent. One major obstacle lies in the fact that even though subject-specific modeling procedures are developed, virtual user groups or populations are still missing. The objective of this contribution is to create such groups of musculoskeletal models. Therefore, a modeling procedure based upon population data is described. First of all, two generic three-dimensional models, one with female and one with male average anthropometric dimensions, were obtained. These models constitute the starting point for the following model adjustment phases. Evenly distributed dimensionless values for gender, age, height, mass, range of motion and strength are sampled and translated into more expressive parameters for the mentioned modeling domains serving as input data for the creation of each individual model of the desired population or user group. The most sophisticated step of the adaption is the strength mapping aiming to create models matching arbitrary target joint torques. Finally, the models’ maximal strength is assessed in a manual material handling task and compared to empirical strength data. The approach is shown using the example of the German population.     

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

IntroductionMusculoskeletal 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.MethodsTwo 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.ResultsPeak 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).DiscussionThe 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.     

A subject-specific finite element musculoskeletal framework for mechanics analysis of a total knee replacement

Concurrent use of finite element (FE) and musculoskeletal (MS) modeling techniques is capable of considering the interactions between prosthetic mechanics and subject dynamics after a total knee replacement (TKR) surgery is performed. However, it still has not been performed in terms of favorable prediction accuracy and systematic experimental validation. In this study, we presented a methodology to develop a subject-specific FE-MS model of a human right lower extremity including the interactions among the subject-specific MS model, the knee joint model with ligament bundles, and the deformable FE prosthesis model. In order to evaluate its accuracy, the FE-MS model was compared with a traditional hinge-constraint MS model and experimentally verified over a gait cycle. Both models achieved good temporal agreement between the predicted muscle force and the electromyography results, though the magnitude on models is different. A higher predicted accuracy, quantified by the root-mean-square error (RMSE) and the squared Pearson correlation coefficient (r²), was found in the FE-MS model (RMSE = 177.2 N, r² = 0.90) when compared with the MS model (RMSE = 224.1 N, r² = 0.81) on the total tibiofemoral contact force. The contact mechanics, including the contact area, pressure, and stress were synchronously simulated, and the maximum contact pressure, 22.06 MPa, occurred on the medial side of the tibial insert without exceeding the yield strength of the ultra-high-molecular-weight polyethylene, 24.79 MPa. The approach outlines an accurate knee joint biomechanics analysis and provides an effective method of applying individualized prosthesis design and verification in TKR.     

Subject-specific tendon-aponeurosis definition in hill-type model predicts higher muscle forces in dynamic tasks

Neuromusculoskeletal models are a common method to estimate muscle forces. Developing accurate neuromusculoskeletal models is a challenging task due to the complexity of the system and large inter-subject variability. The estimation of muscles force is based on the mechanical properties of tendon-aponeurosis complex. Most neuromusculoskeletal models use a generic definition of the tendon-aponeurosis complex based on in vitro test, perhaps limiting their validity. Ultrasonography allows subject-specific estimates of the tendon-aponeurosis complex's mechanical properties. The aim of this study was to investigate the influence of subject-specific mechanical properties of the tendon-aponeurosis complex on a neuromusculoskeletal model of the ankle joint. Seven subjects performed isometric contractions from which the tendon-aponeurosis force-strain relationship was estimated. Hopping and running tasks were performed and muscle forces were estimated using subject-specific tendon-aponeurosis and generic tendon properties. Two ultrasound probes positioned over the muscle-tendon junction and the mid-belly were combined with motion capture to estimate the in vivo tendon and aponeurosis strain of the medial head of gastrocnemius muscle. The tendon-aponeurosis force-strain relationship was scaled for the other ankle muscles based on tendon and aponeurosis length of each muscle measured by ultrasonography. The EMG-driven model was calibrated twice - using the generic tendon definition and a subject-specific tendon-aponeurosis force-strain definition. The use of subject-specific tendon-aponeurosis definition leads to a higher muscle force estimate for the soleus muscle and the plantar-flexor group, and to a better model prediction of the ankle joint moment compared to the model estimate which used a generic definition. Furthermore, the subject-specific tendon-aponeurosis definition leads to a decoupling behaviour between the muscle fibre and muscle-tendon unit in agreement with previous experiments using ultrasonography. These results indicate the use of subject-specific tendon-aponeurosis definitions in a neuromusculoskeletal model produce better agreement with measured external loads and more physiological model behaviour.     

Moving muscle points provide accurate curved muscle paths in a model of the cervical spine

Muscle paths in musculoskeletal models have been modeled using several different methods; however, deformation of soft tissue with changes in posture is rarely accounted for, and often only the neutral posture is used to define a muscle path. The objective of this study was to model curved muscle paths in the cervical spine that take into consideration soft tissue deformation with changes in neck posture. Two subject-specific models were created from magnetic resonance images (MRI) in 5 different sagittal plane neck postures. Curved paths of flexor and extensor muscles were modeled using piecewise linear lines-of-action in two ways; (1) using fixed via points determined from muscle paths in the neutral posture and (2) using moving muscle points that moved relative to the bones determined from muscle paths in all 5 postures. Accuracy of each curved modeled muscle path was evaluated by an error metric, the distance from the anatomic (centroid) muscle path determined from the MRI. Error metric was compared among three modeled muscle path types (straight, fixed via and moving muscle point) using a repeated measures one-way ANOVA (α=0.05). Moving muscle point paths had 21% lower error metric than fixed via point paths over all 15 pairs of neck muscles examined over 5 postures (3.86 mm vs. 4.88 mm). This study highlights the importance of defining muscle paths in multiple postures in order to properly define the changing curvature of a muscle path due to soft tissue deformation with posture.