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Normalized frontal impact biofidelity kinematic corridors using post mortem human surrogates

Due to reducing cost and powerful computing resources and the ability of finite element human body models (FEHBM) to predict human body response more realistically, they are gaining acceptance to be a substitute for mechanical surrogates. Unlike mechanical surrogates, FEHBM can realistically simulat...

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Bibliographic Details
Published in:Journal of the mechanical behavior of biomedical materials 2018-03, Vol.79, p.20-29
Main Authors: Arun, Mike W J, Hadagali, Prasannaah, Pintar, Frank, Yoganandan, Narayan
Format: Article
Language:English
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Summary:Due to reducing cost and powerful computing resources and the ability of finite element human body models (FEHBM) to predict human body response more realistically, they are gaining acceptance to be a substitute for mechanical surrogates. Unlike mechanical surrogates, FEHBM can realistically simulate human kinematics and kinetics. Moreover, an array of quantities can be directly measured from FEHBMs. However, similar to Anthropomorphic Test Devices (ATDs), in order to evaluate the biofidelity, these models must be validated using PMHS response corridors. Therefore, availability of such PMHS corridors that can be used to validate both ATD and FEHBM kinematics is of primary importance. The current study presents normalized biofidelity corridors of head CG, T1, T12, and sacrum accelerations using PMHS frontal sled tests that were previously conducted. In addition, rotational accelerations and displacements of the head are also presented. The experimental data were collected using four specimens. Each specimens were tested with non-injurious pulses using two different velocities (low: 3.6m/s and medium: 6.9m/s). These data were normalized using mass-based technique to represent mid-sized United States population. Using the normalized data, average and plus/minus one standard deviation response corridors were generated that can be used to evaluate the biofidelity of ATDs and FEHBMs.
ISSN:1751-6161
1878-0180
DOI:10.1016/j.jmbbm.2017.12.007