Automated 2D and 3D finite element overclosure adjustment and mesh morphing using generalized regression neural networks.

Computer representations of three-dimensional (3D) geometries are crucial for simulating systems and processes in engineering and science. In medicine, and more specifically, biomechanics and orthopaedics, obtaining and using 3D geometries is critical to many workflows. However, while many tools exist to obtain 3D geometries of organic structures, little has been done to make them usable for their intended medical purposes. Furthermore, many of the proposed tools are proprietary, limiting their use. This work introduces two novel algorithms based on Generalized Regression Neural Networks (GRNN) and 4 processes to perform mesh morphing and overclosure adjustment. These algorithms were implemented, and test cases were used to validate them against existing algorithms to demonstrate improved performance. The resulting algorithms demonstrate improvements to existing techniques based on Radial Basis Function (RBF) networks by converting to GRNN-based implementations. Implementations in MATLAB of these algorithms and the source code are publicly available at the following locations: https://github.com/thor-andreassen/femors; https://simtk.org/projects/femors-rbf; https://www.mathworks.com/matlabcentral/fileexchange/120353-finite-element-morphing-overclosure-reduction-and-slicing.

Automatic generation of subject-specific finite element models of the spine from magnetic resonance images.

The generation of subject-specific finite element models of the spine is generally a time-consuming process based on computed tomography (CT) images, where scanning exposes subjects to harmful radiation. In this study, a method is presented for the automatic generation of spine finite element models using images from a single magnetic resonance (MR) sequence. The thoracic and lumbar spine of eight adult volunteers was imaged using a 3D multi-echo-gradient-echo sagittal MR sequence. A deep-learning method was used to generate synthetic CT images from the MR images. A pre-trained deep-learning network was used for the automatic segmentation of vertebrae from the synthetic CT images. Another deep-learning network was trained for the automatic segmentation of intervertebral discs from the MR images. The automatic segmentations were validated against manual segmentations for two subjects, one with scoliosis, and another with a spine implant. A template mesh of the spine was registered to the segmentations in three steps using a Bayesian coherent point drift algorithm. First, rigid registration was applied on the complete spine. Second, non-rigid registration was used for the individual discs and vertebrae. Third, the complete spine was non-rigidly registered to the individually registered discs and vertebrae. Comparison of the automatic and manual segmentations led to dice-scores of 0.93-0.96 for all vertebrae and discs. The lowest dice-score was in the disc at the height of the implant where artifacts led to under-segmentation. The mean distance between the morphed meshes and the segmentations was below 1 mm. In conclusion, the presented method can be used to automatically generate accurate subject-specific spine models.

Personalization of human body models and beyond via image registration.

Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, and VIVA+ in both seated and standing postures) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs show comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities, which facilitates converting a seated HBM to a standing one, combined with additional positioning tools. Furthermore, this method can be extended to personalize other models, and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.

Structural optimisation of the DEMO alternative divertor configurations based on FE and RBF mesh morphing.

The DEMO tokamak exhibits extraordinary complexity due to the constraints and requirements pertaining to different fields of physics and engineering. The multidisciplinary nature of the DEMO system makes its design phase extremely challenging since different and often opposite requirements need to be accounted for. Toroidal field (TF) coils generate the toroidal magnetic field required to magnetically confine the plasma particles and support at the same time the poloidal field coils. They must bear tremendous loads deriving from electromagnetic interactions between the coil currents and the generated magnetic field. An efficient tokamak design aims at minimizing the energy stored in its magnetic field and hence at reducing the toroidal volume within the TF coils whose shape would hence ideally mimic co-centrically the shape of the plasma. In order to bear the enormous forces a D-shape is most suitable for the TF coils as it allows them to resist the very large compression on the inner side and to carry the electro-magnetic (EM) pressure mainly by membrane stresses preventing large bending to occur on the outer side. At the same time the divertor structures must fit within the TF coils and this requires adaptations of the TF coil shape in the case of so-called advanced divertor configurations (ADCs), which require larger divertor structures. This article shows the TF coils adapted to ADCs using a structural optimisation procedure applied to the reference shape. The introduced strategy takes as structural optimum the iso-stress profile associated to each coil. A continuous transformation, based on radial basis functions mesh morphing, turns the baseline finite element (FE) model into its iso-stress counterpart, with a series of intermediate configurations available for electromagnetic and structural investigations as output. The adopted strategy allowed to determine, for each of the ADC cases, a candidate shape. Static membrane stress levels during magnetization could be reduced significantly from more than 700 MPa to below 450 MPa.

An image-based approach for the estimation of arterial local stiffness in vivo.

The analysis of mechanobiology of arterial tissues remains an important topic of research for cardiovascular pathologies evaluation. In the current state of the art, the gold standard to characterize the tissue mechanical behavior is represented by experimental tests, requiring the harvesting of ex-vivo specimens. In recent years though, image-based techniques for the in vivo estimation of arterial tissue stiffness were presented. The aim of this study is to define a new approach to provide local distribution of arterial stiffness, estimated as the linearized Young's Modulus, based on the knowledge of in vivo patient-specific imaging data. In particular, the strain and stress are estimated with sectional contour length ratios and a Laplace hypothesis/inverse engineering approach, respectively, and then used to calculate the Young's Modulus. After describing the method, this was validated by using a set of Finite Element simulations as input. In particular, idealized cylinder and elbow shapes plus a single patient-specific geometry were simulated. Different stiffness distributions were tested for the simulated patient-specific case. After the validation from Finite Element data, the method was then applied to patient-specific ECG-gated Computed Tomography data by also introducing a mesh morphing approach to map the aortic surface along the cardiac phases. The validation process revealed satisfactory results. In the simulated patient-specific case, root mean square percentage errors below 10% for the homogeneous distribution and below 20% for proximal/distal distribution of stiffness. The method was then successfully used on the three ECG-gated patient-specific cases. The resulting distributions of stiffness exhibited significant heterogeneity, nevertheless the resulting Young's moduli were always contained within the 1-3 MPa range, which is in line with literature.

Influence of morphological variation on brain impact responses among youth and young adults.

Tissue-level brain responses to sport-related head impacts may be stronger predictors of brain injury risk than head kinematics alone. Despite the importance of accurate impact response estimation, the influence of head morphological variations has not been properly considered due to the limited sizes and shapes of existing computational head models. In this study, we developed 101 subject-specific finite element (FE) head-brain models based on CT scans and a parametric modeling approach to estimate tissue-level brain impact responses (maximal principal strain, MPS) under three head impact conditions. Principal component analysis (PCA) was used to quantify the geometric variations, with statistically significant PCs then selected to predict MPS using a stepwise linear regression model. High adjusted R2 values (0.6-0.9) were achieved in the regression model, suggesting a good model predictability. Brain volume explained the largest variance of 51.3%, and it was highly correlated with MPS, indicating a significant size effect on brain impact responses. This is the first modeling study to systematically consider the influence of morphological variations in the inner skull and scalp on brain tissue impact response.

Superficial femoral artery stenting: Impact of stent design and overlapping on the local hemodynamics.

BACKGROUND: Superficial femoral arteries (SFAs) treated with self-expanding stents are widely affected by in-stent restenosis (ISR), especially in case of long lesions and multiple overlapping devices. The altered hemodynamics provoked by the stent is considered as a promoting factor of ISR. In this context, this work aims to analyze the impact of stent design and stent overlapping on patient-specific SFA hemodynamics. METHODS: Through a morphing technique, single or multiple stents were virtually implanted within two patient-specific, post-operative SFA models reconstructed from computed tomography. The stented domains were used to perform computational fluid dynamics simulations, quantifying wall shear stress (WSS) based descriptors including time-averaged WSS (TAWSS), oscillatory shear index (OSI), transverse WSS (transWSS), and WSS ratio (WSSRATIO). Four stent designs (three laser-cut - EverFlex, Zilver and S.M.A.R.T. - and one prototype braided stent), and three typical clinical scenarios accounting for different order of stent implantation and overlapping length were compared. RESULTS: The main hemodynamic differences were found between the two types of stent designs (i.e. laser-cut vs. braided stents). The braided stent presented lower median transWSS and higher median WSSRATIO than the laser-cut stents (p < 0.0001). The laser-cut stents presented comparable WSS-based descriptor values, except for the Zilver, exhibiting a median TAWSS ∼30% higher than the other stents. Stent overlapping provoked an abrupt alteration of the WSS-based descriptors. The overlapping length, rather than the order of stent implantation, highly and negatively impacted the hemodynamics. CONCLUSION: The proposed computational workflow compared different SFA stent designs and stent overlapping configurations, highlighting those providing the most favorable hemodynamic conditions.

Cardiac mesh morphing method for finite element modeling of heart failure with preserved ejection fraction.

Numerical modeling of heart biomechanics can realistically capture morphological variations in diseases and has been helpful in advancing our understanding of the physiology. Subject-specific models require anatomic representation of medical images, and it is desirable to have a consistently repeatable models for any given morphology. In this study, we propose a novel and easily adaptable cardiac reconstruction algorithm by morphing an existing discretized mesh of an advanced finite element (FE) model, to match anatomies acquired from porcine cardiac magnetic resonance imaging (cMRI) scans. The morphing algorithm involves iterative FE simulations with visco-hyperelastic material properties. The living heart porcine model (LHPM) was chosen as the input baseline FE mesh, in order to preserve detailed anatomical features that cannot be captured in routine scans such as myofiber orientations and conduction pathways. The algorithm was demonstrated for the recreation of porcine hearts of a healthy subject and of a subject induced with heart failure with preserved ejection fraction (HFpEF) conditions, where there were substantial hypertrophy and anatomical alterations. We further used the morphed meshes for FE modeling of cardiac contraction and relaxation, thus demonstrating the applicability of the proposed algorithm in producing viable meshes. The results show that our algorithm can recreate the characteristic anatomical changes of cardiac remodeling, including heart muscle thickening, as well as replicate the reduction in ventricular volume. This algorithm allows for the creation of subject-specific models with the same mesh connectivity, thus enabling spatial comparison and analysis of pathologic progress.

Numerical simulations of flow patterns in the human left ventricle model with a novel dynamic mesh morphing approach based on radial basis function.

We present a new numerical simulation framework for prediction of flow patterns in the human left ventricle model. In this study, a radial basis function (RBF) mesh morphing method is developed and applied within the finite-volume computational fluid dynamics (CFD) approach. The numerical simulations are designed to closely mimic details of recent tomographic particle image velocimetry (TomoPIV) experiments. The numerically simulated dynamic motions of the left ventricle and tri-leaflet biological mitral valve are emulated through the RBF morphing method. The arbitrary Lagrangian-Eulerian (ALE) based CFD is performed with the RBF-defined deforming wall boundaries. The results obtained show a good agreement with experiments, confirming the reliability and accuracy of the developed simulation framework.

Influence of pelvic shape on strain patterns: A computational analysis using finite element mesh morphing techniques.

The pelvis functions to transmit upper body loads to the lower limbs and is critical in human locomotion. Semi-automated, finite element (FE) morphing techniques eliminate the need for segmentation and have shown to accelerate the generation of multiple specimen-specific pelvic FE models to enable the study of pelvic mechanical behaviour. The purpose of this research was to produce simulated human pelvic FE models representing android, gynecoid, anthropoid and platypelloid morphologies and to isolate differences in strain patterns due to anatomic shape under physiologic loading. Using five initially generated specimen-specific FE models, each specimen-specific FE model was reconfigured into three different morphologies using FE mesh morphing techniques. Significantly different strains were found comparing the gynecoid (classical female pelvis') to the android ('true male pelvis') models (p = 0.040), with strains twice as high in the superior pubic rami. No significant differences were seen in comparing overall strains between the other pelvic shapes (p = 0.61-0.126). The highest strain regions in all models were found in the supra-acetabular regions, with high strains also found in the regions of the superior pubic rami, the greater sciatic notch and sacral regions about the L5 vertebrae. Quantifying the contributions of shape to strain in the pelvis may increase the understanding of sex and patient-specific differences in fracture risk and motivate the consideration of treatment strategies that account for anatomic pelvic differences.

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.

A novel formulation for the study of the ascending aortic fluid dynamics with in vivo data.

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

Influence of cervical spine sagittal alignment on range of motion after corpectomy: a finite element study.

BACKGROUND: Sagittal alignment of the cervical spine might influence the development of radiological adjacent segment pathology (RASP) after central corpectomy (CC). Range of motion (ROM) of the adjacent segments is closely linked to the development of RASP. METHODS: To investigate the ROM of the adjacent segments after CC, we developed a C2-T1 finite element (FE) model. The model with a lordotic sagittal alignment served as the baseline model. Models with straight and kyphotic alignment were generated using mesh morphing methods. Single-level corpectomy at C5 was done on these models. Segmental ROMs of intact and corpectomized spines were compared for physiologic flexion-extension loads. RESULTS: The flexion ROM decreased by an average of 13% with the change in sagittal alignment from lordosis to kyphosis; however, a consistent decrease was not observed in extension. After CC, the ROM increased by an average of 95% and 31% in the superior and inferior adjacent segments. With kyphotic change in the sagittal alignment, the postoperative increase in flexion ROM exhibited a decreasing trend, while this was not seen in extension. CONCLUSIONS: Kyphotic changes of the intact spine resulted in segmental stiffening, and after corpectomy, it resulted in inconsistent variations of segmental extension ROMs.

Validating diverse human body models against side impact tests with post-mortem human subjects.

This study aimed at evaluating the ability of morphed finite element (FE) human body models (HBMs) to reproduce the impact responses of post-mortem human subjects (PMHS) with various stature and shape. Ten side impact tests previously performed using seven PMHS under 3 m/s and 8 m/s impact velocities were selected for model evaluation. With weight, stature, sex, and age of PMHS, seven FE HBMs were developed by morphing the midsize male THUMS model into the target geometries predicted by the statistical skeleton and external body shape models. The model-predicted force histories, accelerations along the spine, and deflections in the chest and abdomen were compared to the test data. For comparison, simulations in all testing conditions were also conducted with the original midsize male THUMS, and the results from the THUMS simulations were scaled to the weight and stature from each PMHS. The CORrelation and Analysis (CORA) was used to evaluate the model accuracy, with CORA scores close to one indicating excellent agreement. Ten simulations using the morphed models exhibited 0.80 ±â€¯0.01, 0.80 ±â€¯0.01, 0.78 ±â€¯0.02, and 0.78 ±â€¯0.02 CORA scores for the impact forces to the thorax, abdomen, iliac-wings, and greater-trochanter, respectively; the corresponding CORA scores with the original THUMS were markedly lower at 0.60 ±â€¯0.06, 0.69 ±â€¯0.05, 0.71 ±â€¯0.05, and 0.69 ±â€¯0.04; while those for the scaled THUMS were 0.65 ±â€¯0.05, 0.71 ±â€¯0.05, 0.73 ±â€¯0.05, and 0.72 ±â€¯0.02, also lower than the morphed models. Across all simulations, the morphed HBMs demonstrated significantly higher accuracy than the THUMS with or without scaling. These results suggested the necessity of accounting for size and shape effects on predicting human responses in side impacts.

Frontal crash simulations using parametric human models representing a diverse population.

Objective: Analyses of crash data have shown that older, obese, and/or female occupants have a higher risk of injury in frontal crashes compared to the rest of the population. The objective of this study was to use parametric finite element (FE) human models to assess the increased injury risks and identify safety concerns for these vulnerable populations. Methods: We sampled 100 occupants based on age, sex, stature, and body mass index (BMI) to span a wide range of the U.S. adult population. The target anatomical geometry for each of the 100 models was predicted by the statistical geometry models for the rib cage, pelvis, femur, tibia, and external body surface developed previously. A regional landmark-based mesh morphing method was used to morph the Global Human Body Models Consortium (GHBMC) M50-OS model into the target geometries. The morphed human models were then positioned in a validated generic vehicle driver compartment model using a statistical driving posture model. Frontal crash simulations based on U.S. New Car Assessment Program (U.S. NCAP) were conducted. Body region injury risks were calculated based on the risk curves used in the US NCAP, except that scaling was used for the neck, chest, and knee-thigh-hip injury risk curves based on the sizes of the bony structures in the corresponding body regions. Age effects were also considered for predicting chest injury risk. Results: The simulations demonstrated that driver stature and body shape affect occupant interactions with the restraints and consequently affect occupant kinematics and injury risks in severe frontal crashes. U-shaped relations between occupant stature/weight and head injury risk were observed. Chest injury risk was strongly affected by age and sex, with older female occupants having the highest risk. A strong correlation was also observed between BMI and knee-thigh-hip injury risk, whereas none of the occupant parameters meaningfully affected neck injury risks. Conclusions: This study is the first to use a large set of diverse FE human models to investigate the combined effects of age, sex, stature, and BMI on injury risks in frontal crashes. The study demonstrated that parametric human models can effectively predict the injury trends for the population and may now be used to optimize restraint systems for people who are not similar in size and shape to the available anthropomorphic test devices (ATDs). New restraints that adapt to occupant age, sex, stature, and body shape may improve crash safety for all occupants.

Rear-Impact Neck Whiplash: Role of Head Inertial Properties and Spine Morphological Variations on Segmental Rotations.

Whiplash injuries continue to be a concern in low-speed rear impact. This study was designed to investigate the role of variations in spine morphology and head inertia properties on cervical spine segmental rotation in rear-impact whiplash loading. Vertebral morphology is rarely considered as an input parameter in spine finite element (FE) models. A methodology toward considering morphological variations as input parameters and identifying the influential variations is presented in this paper. A cervical spine FE model, with its morphology parametrized using mesh morphing, was used to study the influence of disk height, anteroposterior vertebral depth, and segmental size, as well as variations in head mass, moment of inertia, and center of mass locations. The influence of these variations on the characteristic S-curve formation in whiplash response was evaluated using the peak C2-C3 flexion marking the maximum S-curve formation and time taken for the formation of maximum S-curve. The peak C2-C3 flexion in the S-curve formation was most influenced by disk height and vertebral depth, followed by anteroposterior head center of mass location. The time to maximum S-curve was most influenced by the anteroposterior location of head center of mass. The influence of gender-dependent variations, such as the vertebral depth, suggests that they contribute to the greater segmental rotations observed in females resulting in different S-curve formation from men. These results suggest that both spine morphology and head inertia properties should be considered to describe rear-impact responses.

Cervical spine morphology and ligament property variations: A finite element study of their influence on sagittal bending characteristics.

Cervical spine finite element models reported in biomechanical literature usually represent a static morphology. Not considering morphology as a model parameter limits the predictive capabilities for applications in personalized medicine, a growing trend in modern clinical practice. The objective of the study was to investigate the influence of variations in spinal morphology on the flexion-extension responses, utilizing mesh-morphing-based parametrization and metamodel-based sensitivity analysis. A C5-C6 segment was used as the baseline model. Variations of intervertebral disc height, facet joint slope, facet joint articular processes height, vertebral body anterior-posterior depth, and segment size were parametrized. In addition, material property variations of ligaments were considered for sensitivity analysis. The influence of these variations on vertebral rotation and forces in the ligaments were analyzed. The disc height, segmental size, and body depth were found to be the most influential (in the cited order) morphology variations; while among the ligament material property variations, capsular ligament and ligamentum flavum influenced vertebral rotation the most. Changes in disc height influenced forces in the posterior ligaments, indicating that changes in the anterior load-bearing column of the spine could have consequences on the posterior column. A method to identify influential morphology variations is presented in this work, which will help automation efforts in modeling to focus on variations that matter. This study underscores the importance of incorporating influential morphology parameters, easily obtained through computed tomography/magnetic resonance images, to better predict subject-specific biomechanical responses for applications in personalized medicine.

Finite element modeling of the human kidney for probabilistic occupant models: Statistical shape analysis and mesh morphing.

Statistical shape analysis was conducted on 15 pairs (left and right) of human kidneys. It was shown that the left and right kidney were significantly different in size and shape. In addition, several common modes of kidney variation were identified using statistical shape analysis. Semi-automatic mesh morphing techniques have been developed to efficiently create subject specific meshes from a template mesh with a similar geometry. Subject specific meshes as well as probabilistic kidney meshes were created from a template mesh. Mesh quality remained about the same as the template mesh while only taking a fraction of the time to create the mesh from scratch or morph with manually identified landmarks. This technique can help enhance the quality of information gathered from experimental testing with subject specific meshes as well as help to more efficiently predict injury by creating models with the mean shape as well as models at the extremes for each principal component.

Analysis of pelvic strain in different gait configurations in a validated cohort of computed tomography based finite element models.

The pelvis functions to transmit upper body loads to the lower limbs and is critical in human locomotion. Semi-automated, landmark-based finite element (FE) morphing and mapping techniques eliminate the need for segmentation and have shown to accelerate the generation of multiple specimen-specific pelvic FE models to enable the study of pelvic mechanical behaviour. The purpose of this research was to produce an experimentally validated cohort of specimen-specific FE models of the human pelvis and to use this cohort to analyze pelvic strain patterns during gait. Using an initially segmented specimen-specific pelvic FE model asa source model, four more specimen-specific pelvic FE models were generated from target clinical CT scans using landmark-based morphing and mapping techniques. FE strains from the five models were compared to the experimental strains obtained from cadaveric testing via linear regression analysis, (R2 values ranging from 0.70 to 0.93). Inter-specimen variability in FE strain distributions was seen among the five specimen-specific pelvic FE models. The validated cohort of specimen-specific pelvic FE models was utilized to examine pelvic strains at different phases of the gait cycle. Each validated specimen-specific FE model was reconfigured into gait cycle phases representing heel-strike/heel-off and midstance/midswing. No significant difference was found in the double-leg stance and heel-strike/heel-off models (p=0.40). A trend was observed between double-leg stance and midstance/midswing models (p=0.07), and a significant difference was found between heel-strike/heel-off models and midstance/midswing models (p=0.02). Significant differences were also found in comparing right vs. left models (heel-strike/heel-off p=0.14, midstance/midswing p=0.04).

An automated method to morph finite element whole-body human models with a wide range of stature and body shape for both men and women.

Field data analyses have shown that small female, obese, and/or older occupants are at increased risks of death and serious injury in motor-vehicle crashes compared with mid-size young men. The current adult finite element (FE) human models represent occupants in the same three body sizes (large male, mid-size male, and small female) as those for the contemporary adult crash dummies. Further, the time needed to develop an FE human model using the traditional method is measured in months or even years. In the current study, an improved regional mesh morphing method based on landmark-based radial basis function (RBF) interpolation was developed to rapidly morph a mid-size male FE human model into different geometry targets. A total of 100 human models with a wide range of human attributes were generated. A pendulum chest impact condition was applied to each model as an initial assessment of the resulting variability in response. The morphed models demonstrated mesh quality similar to the baseline model. The peak impact forces and chest deflections in the chest pendulum impacts varied substantially with different models, supportive of consideration of population variation in evaluating the occupant injury risks. The method developed in this study will enable future safety design optimizations targeting at various vulnerable populations that cannot be considered with the current models.