Nicholas A. Vavalle

An Evaluation of Objective Rating Methods for Full-Body Finite Element Model Comparison to PMHS Tests

Objective: Objective evaluation methods of time history signals are used to quantify how well simulated human body responses match experimental data. As the use of simulations grows in the field of biomechanics, there is a need to establish standard approaches for comparisons. There are 2 aims of this study. The first is to apply 3 objective evaluation methods found in the literature to a set of data from a human body finite element model. The second is to compare the results of each method, examining how they are correlated to each other and the relative strengths and weaknesses of the algorithms. Methods: In this study, the methods proposed by Sprague and Geers (magnitude and phase error, SGM and SGP), Rhule et al. (cumulative standard deviation, CSD), and Gehre et al. (CORrelation and Analysis, or CORA, size, phase, shape, corridor) were compared. A 40 kph frontal sled test presented by Shaw et al. was simulated using the Global Human Body Models Consortium midsized male full-body finite element model (v. 3.5). Mean and standard deviation experimental data (n = 5) from Shaw et al. were used as the benchmark. Simulated data were output from the model at the appropriate anatomical locations for kinematic comparison. Force data were output at the seat belts, seat pan, knee, and foot restraints. Results: Objective comparisons from 53 time history data channels were compared to the experimental results. To compare the different methods, all objective comparison metrics were cross-plotted and linear regressions were calculated. The following ratings were found to be statistically significantly correlated (P < .01): SGM and CORrelation and Analysis (CORA) size, R 2 = 0.73; SGP and CORA shape, R 2 = 0.82; and CSD and CORAs corridor factor, R 2 = 0.59. Relative strengths of the correlated ratings were then investigated. For example, though correlated to CORA size, SGM carries a sign to indicate whether the simulated response is greater than or less than the benchmark signal. A further analysis of the advantages and drawbacks of each method is discussed. Conclusions: The results demonstrate that a single metric is insufficient to provide a complete assessment of how well the simulated results match the experiments. The CORA method provided the most comprehensive evaluation of the signal. Regardless of the method selected, one primary recommendation of this work is that for any comparison, the results should be reported to provide separate assessments of a signals match to experimental variance, magnitude, phase, and shape. Future work planned includes implementing any forthcoming International Organization for Standardization standards for objective evaluations. Supplemental materials are available for this article. Go to the publishers online edition of Traffic Injury Prevention to view the supplemental file.

Validation of Simulated Chestband Data in Frontal and Lateral Loading Using a Human Body Finite Element Model

Objective: Finite element (FE) computer models are an emerging tool to examine the thoracic response of the human body in the simulated environment. In this study, a recently developed human body model, the Global Human Body Models Consortium (GHBMC) mid-sized male, was used to examine chestband contour deformations in a frontal and lateral impact. The objective of this study was 2-fold. First, a methodology for extracting and analyzing virtual chestband data from a full-body FE model is presented. Then, this method is applied to virtual chestband data from 2 simulations to evaluate the models performance against experimental data. Methods: One frontal and one lateral impact case were simulated using the FE model, which was preprogrammed with upper, middle, and lower chestbands. Maximum compression was determined using established techniques. Furthermore, a quadrant-based analysis technique for the results was introduced that enabled regional comparisons between the model and the experimental data in the anterior, posterior, right, and left sections of the chestband. Results: For the frontal case at 13.3 m/s, the model predicted a peak compression of 13.6 and 12.9 percent for the upper and middle chestbands. For the lateral case at 6.7 m/s, the model predicted peak compression of the upper, middle, and lower chestbands of 27.9, 26.0, and 20.4 percent. Regional analysis showed average differences at maximum deformation between the model and experiments ranging from 0.9 percent (posterior) to 6.3 percent (anterior) in the frontal case and 2.3 percent (posterior) to 10.8 percent (anterior) in the lateral case. The greatest difference between model and experimental findings was found in the anterior quadrant. Conclusions: Though this work was focused on techniques to extract and analyze chestband data from FE models, the comparative results provide further validation of the model used in this study. The results suggest the importance of evaluating comparisons between virtual and experimental chestband data on a regional basis. These data also provide the potential to correlate chestband deformations to the loading of underlying thoraco-abdominal structures. Supplemental materials are available for this article. Go to the publishers online edition of Traffic Injury Prevention to view the supplemental file.

Age- and sex-specific thorax finite element model development and simulation.

Objective: The shape, size, bone density, and cortical thickness of the thoracic skeleton vary significantly with age and sex, which can affect the injury tolerance, especially in at-risk populations such as the elderly. Computational modeling has emerged as a powerful and versatile tool to assess injury risk. However, current computational models only represent certain ages and sexes in the population. The purpose of this study was to morph an existing finite element (FE) model of the thorax to depict thorax morphology for males and females of ages 30 and 70 years old (YO) and to investigate the effect on injury risk. Methods: Age- and sex-specific FE models were developed using thin-plate spline interpolation. In order to execute the thin-plate spline interpolation, homologous landmarks on the reference, target, and FE model are required. An image segmentation and registration algorithm was used to collect homologous rib and sternum landmark data from males and females aged 0–100 years. The Generalized Procrustes Analysis was applied to the homologous landmark data to quantify age- and sex-specific isolated shape changes in the thorax. The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant model was morphed to create age- and sex-specific thoracic shape change models (scaled to a 50th percentile male size). To evaluate the thoracic response, 2 loading cases (frontal hub impact and lateral impact) were simulated to assess the importance of geometric and material property changes with age and sex. Results: Due to the geometric and material property changes with age and sex, there were observed differences in the response of the thorax in both the frontal and lateral impacts. Material property changes alone had little to no effect on the maximum thoracic force or the maximum percent compression. With age, the thorax becomes stiffer due to superior rotation of the ribs, which can result in increased bone strain that can increase the risk of fracture. For the 70-YO models, the simulations predicted a higher number of rib fractures in comparison to the 30-YO models. The male models experienced more superior rotation of the ribs in comparison to the female models, which resulted in a higher number of rib fractures for the males. Conclusion: In this study, age- and sex-specific thoracic models were developed and the biomechanical response was studied using frontal and lateral impact simulations. The development of these age- and sex-specific FE models of the thorax will lead to an improved understanding of the complex relationship between thoracic geometry, age, sex, and injury risk.

Investigation of the mass distribution of a detailed seated male finite element model.

Accurate mass distribution in computational human body models is essential for proper kinematic and kinetic simulations. The purpose of this study was to investigate the mass distribution of a 50th percentile male (M50) full body finite element model (FEM) in the seated position. The FEM was partitioned into 10 segments, using segment planes constructed from bony landmarks per the methods described in previous research studies. Body segment masses and centers of gravity (CGs) of the FEM were compared with values found from these studies, which unlike the present work assumed homogeneous body density. Segment masses compared well to literature while CGs showed an average deviation of 6.0% to 7.0% when normalized by regional characteristic lengths. The discrete mass distribution of the FEM appears to affect the mass and CGs of some segments, particularly those with low-density soft tissues. The locations of the segment CGs are provided in local coordinate systems, thus facilitating comparison with other full body FEMs and human surrogates. The model provides insights into the effects of inhomogeneous mass on the location of body segment CGs.

A technique for developing CAD geometry of long bones using clinical CT data

Computed tomography scans are a valuable tool for developing computational models of bones. The objective of this study is to present a method to generate CAD representations of long bones from clinically based CT scans. A secondary aim is to apply the method to six long bones from a sample of three individuals. Periosteal and endosteal bone surfaces were segmented and used to calculate the characteristic cortical thickness, Tc, at 1 mm increments along the bone axis. In the epiphyses where the value of Tc fell below the scanner threshold, the endosteal bone layer was replaced using literature values projected inward from the periosteal surface. On average, 74.7 ± 7.4% of the bone geometry was above the scanner cut-off and was therefore derived from the CT scan data. The thickness measurement was also compared to experimental measurements of cadaveric bone and was found to predict Tc with an error of 3.1%. This method presents a possible solution for the characterization of characteristic thickness along the length of the bone and may also aid in the development of orthopedic implant design and subject specific finite element models.

A Multi-Modality Dataset for the Development of a Small Female Full Body Finite Element Model

Motor vehicle fatalities and injuries remain a leading public health problem worldwide. In 2009, the World Health Organization reported more than 1.2 million people die each year worldwide as a result of motor vehicle crash [1]. Researchers are using a wide array of tools to mitigate the societal tool of this epidemic, and finite element (FE) computer models are one method gaining interest in the biomechanics field. Full body FE models are used to examine the potential for occupant injury in vehicle crash. Such models are often built to represent an average (50th percentile) male occupant [2]. However computational models can be made to represent essentially any driving cohort.© 2013 ASME

Application of a Standard Quantitative Comparison Method to Assess a Full Body Finite Element Model in Frontal Impact

Advanced human body finite element models (FEMs) are gaining popularity in the study of injury biomechanics [1, 2]. FEMs must be validated to ensure that model outputs correspond to experimentally-observed phenomena. During the validation process researchers often qualitatively compare the model response to a laboratory experiment. However, a more rigorous approach is to use quantitative methods. Often, these methods attempt to parse the error contributions of phase, magnitude, and a shape factor. The purpose of this study is to apply one such method for validation quantification, called the enhanced error assessment of response time histories (EEARTH), to a model that was recently developed. The EEARTH method is anticipated to be part of the forthcoming ISO standard (ISO/TC 22/SC 10/WG 4) on comparing model outcomes to experimental data. The subject of this study is the Global Human Body Models Consortium (GHBMC) 50th percentile male seated model (M50). The mission statement of the consortium is to develop a set of biofidelic computational human body models to aid in the study injury biomechanics and safety system enhancement.Copyright

The Effect of Impactor Location on the Validation of a Full Body Finite Element Model in Two Loading Cases

Finite element analysis (FEA) is a tool used by many in the injury biomechanics field. FEA allows researchers to study the stresses and strains in complex loading scenarios that would be impossible to determine experimentally. A vital step toward ensuring accurate results is validation of the finite element model (FEM), which is often based on matching model results to experimental results. While care is taken in performing experiments, there are still sources of variance in empirical results like experimental error and cadaver variation. In order to mimic these, location variations of two validation cases were studied, an oblique impact to the right thoracoabdominal region and a lateral impact to the right shoulder. Five locations were studied for each case, the nominal and four variations. The object of this study was to determine model robustness, conduct a sensitivity study of the model, and to simulate experimental subject variation without the use of subject-specific models. This study utilizes the Global Human Body Models Consortium (GHBMC) midsized male model. The model reflects a global effort to develop a set of state-of-the-art full body finite element models.Copyright