Evaluation of Geometrically Personalized THUMS Pedestrian Model Response against Sedan-Pedestrian PMHS Impact Test Data
Objective: Evaluating the biofidelity of pedestrian finite element models (PFEM) using post-mortem human subjects (PMHS) is a challenge as differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry which could alleviate this issue. In this study, the THUMS PFEM (v4.01) was compared to the cadaveric response in
... esponse in vehicle-pedestrian impacts using geometrically personalized models. Methods: The AM50 THUMS PFEM was used as the baseline model, and two morphed PFEM were created to the anthropometric specifications of two obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold), and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy. Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain and injury risks, while the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during post-test autopsy. Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle-pedestrian impact scenarios.