Development and Full Body Validation of a 5th Percentile Female Finite Element Model

Davis, Matthew L.; Koya, Bharath; Schap, Jeremy M.; Gayzik, F. Scott

doi:10.4271/2016-22-0015

Cited by 25 publications

(21 citation statements)

References 117 publications

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“…Total CORA scores ranged from 0.7 to 0.8, which is analogous to other helmet models 5 or FE validation studies in general. 10,11,21,38,50 Scores for individual output traces ranged from 0.5 to 0.95. Head kinematics of the simulations generally followed the shape of the experimental traces, even with more complex bi-modal responses.…”

Section: Full Helmet Responsementioning

confidence: 99%

“…15,23,40,41,45,51,53 Computational tools, such as finite element (FE) models, allow researchers to directly analyze the internal complex behavior of a system responsible for injury. 47,52 There are FE models of the human brain, 12,22,25,29,[31][32][33]46,55 full body, 10,18,24 and anthropomorphic test dummies (ATDs). 36,56 All these models can be used to study injury but in different ways.…”

Section: Introductionmentioning

confidence: 99%

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Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Decker

Baker

et al. 2019

Ann Biomed Eng

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Head injury is a growing concern within contact sports, including American football. Computational tools such as finite element (FE) models provide an avenue for researchers to study, and potentially optimize safety tools, such as helmets. The goal of this study was to develop an accurate representative helmet model that could be used in further study of head injury to mitigate the toll of concussions in contact sports. An FE model of a Schutt Air XP Pro football helmet was developed through three major steps: geometry development, material characterization, and model validation. The fully assembled helmet model was fit onto a Hybrid III dummy head–neck model and National Operating Committee on Standards for Athletic Equipment (NOCSAE) head model and validated through a series of 67 representative impacts similar to those experienced by a football player. The kinematic and kinetic response of the model was compared to the response of the physical experiments, which included force, head linear acceleration, head angular velocity, and carriage acceleration. The outputs between the model and the physical tests were quantitatively evaluated using CORelation and Analysis (CORA), amounting to an overall averaged score of 0.76. The model described in this study has been extensively validated and can function as a building block for innovation in player safety.

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Section: Full Helmet Responsementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Decker

Baker

et al. 2019

Ann Biomed Eng

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“…The above studies are almost about the 50th percentile male model; in fact, establishing 5th percentile female GHBMC model was also listed as part of the project; the process of medical imaging dataset acquisition and the CAD model establishment was the same as that of the male model. The initial version of 5th percentile female had been established [ 83 ], but more validation work is needed in the future study.…”

Section: Computational Modelsmentioning

confidence: 99%

Development and Validation of Dummies and Human Models Used in Crash Test

Xiaoming

Zhang

et al. 2018

Applied Bionics and Biomechanics

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The crash test dummy, an important tool for car crash safety tests, is of great significance to explore the injury biomechanics of the occupants and improve the safety performance of the vehicle. The article mainly consists of four parts: brief introduction of injury mechanism, early experiments for obtaining biomechanical response (animal tests, cadaver tests, and volunteer tests), and development and validation of mechanical dummies and computational models. This study finds that the current crash test dummies are generally designed based on European and American, so they have limitations on the damage prediction of other regions. Further research in the crash test dummy needs the participation of various countries in order to develop a crash test dummy that meets the national conditions of each country. Simultaneously, it is necessary to develop dummies of vulnerable groups, such as the elderly dummy and obese people dummy.

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“…Another technique for efficient generation of subject-specific models is by mesh morphing (also called warping). The concept has been used extensively in many biomechanics fields on different organs (Couteau et al 2000;Castellano-Smith et al 2001;Fernandez et al 2004;Sigal et al 2008;Bucki et al 2010;Bijar et al 2016;Park et al 2017), full-body models (Davis et al 2016;Beillas and Berthet 2017;Liu et al 2020), as well as smooth brain models (Hu et al 2007;Ji et al 2011;Ji et al 2015;Wu et al 2019), showing promising results. A typical procedure includes image registration (rigid/affine and/or followed by nonlinear registration algorithms), from which displacement field representing the geometrical difference between the subject and baseline mesh is obtained.…”

Section: Introductionmentioning

confidence: 99%

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

Zhou

Kleiven

2020

Preprint

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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 work: 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 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 (MPS) and axonal strain (MAS) 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 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.

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Development and Full Body Validation of a 5th Percentile Female Finite Element Model

Cited by 25 publications

References 117 publications

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

Development and Validation of Dummies and Human Models Used in Crash Test

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

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