Development and Application for Biomechanical Computational Model of Lower Extremity of 5th Percentile Chinese Female Pedestrian
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    Abstract:

    Objective To predict and evaluate biomechanical responses and injury mechanism of lower extremity for a small-sized female pedestrian in pedestrian-car collision. Methods The lower extremity geometric model with detailed anatomical structure was reconstructed based on CT images from the 5th percentile Chinese female volunteer. The finite element computational model was developed by optimizing the curved surface and meshing. The finite element model of pedestrian lower extremity was validated by reconstructing several cadaver tests, including dynamic three-point bending corpse experiments, and knee joint lateral bending and shearing cadaver experiments at high speed. Four simulation tests of pedestrian lower extremity-car collision as specified Euro NCAP TB024 were set up to investigate injury mechanisms of lower extremity of 5th percentile female pedestrian. Results The biomechanical computational model was validated to have high biofidelity by comparing the simulation test results with the cadaver test results. The lower extremity suffered the least injury in pedestrian- SUV collision. The femurs quickly fractured in simulations on four types of vehicle, so that no injury was found in knee ligaments. Conclusions This lower extremity finite element model is an important part of basic work for developing the 5th percentile Chinese female whole body computational model, which lays the foundation for model development. This study has important application values for studying injury mechanisms of female lower extremity and developing pedestrian protection devices.

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RUAN Shijie, LIANG Yan, LI Haiyan, RAN Linghua, CUI Shihai, HE Lijuan, Lü Wenle. Development and Application for Biomechanical Computational Model of Lower Extremity of 5th Percentile Chinese Female Pedestrian[J]. Journal of medical biomechanics,2022,37(6):1056-1063

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History
  • Received:October 14,2021
  • Revised:January 15,2022
  • Adopted:
  • Online: December 24,2022
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