AUTHOR=Tang Jisi , Zhou Qing , Shen Wenxuan , Chen Wentao , Tan Puyuan TITLE=Can we reposition finite element human body model like dummies? JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1176818 DOI=10.3389/fbioe.2023.1176818 ISSN=2296-4185 ABSTRACT=

Rapidly repositioning finite element human body models (FE-HBMs) with high biofidelity is an important but notorious problem in vehicle safety and injury biomechanics. We propose to reposition the FE-HBM in a dummy-like manner, i.e., through pose parameters prescribing joint configurations. Skeletons are reconfigured along the trajectories inferred from model-specific bone geometries. We leverage differential geometry to steer equidistant moves along the congruent articulated bone surfaces. Soft tissues are subsequently adapted to reconfigured skeletons through a series of operations. The morph–contact algorithm allows the joint capsule to slide and wrap around the repositioned skeletons. Nodes on the deformed capsule are redistributed following an optimization-based approach to enhance element regularity. The soft tissues are transformed accordingly via thin plate spline. The proposed toolbox can reposition the Total Human Body Model for Safety (THUMS) in a few minutes on a whole-body level. The repositioned models are simulation-ready, with mesh quality maintained on a comparable level to the baseline. Simulations of car-to-pedestrian impact with repositioned models exhibiting active collision-avoidance maneuvers are demonstrated to illustrate the efficacy of our method. This study offers an intuitive, effective, and efficient way to reposition FE-HBMs. It benefits all posture-sensitive works, e.g., out-of-position occupant safety and adaptive pedestrian protection. Pose parameters, as an intermediate representation, join our method with recently prosperous perception and reconstruction techniques of the human body. In the future, it is promising to build a high-fidelity digital twin of real-world accidents using the proposed method and investigate human biomechanics therein, which is of profound significance in reshaping transportation safety studies in the future.