The first mathematical human models were limited by computational capacity and knowledge of human mechanical characteristics. Models consisted of a limited number of lumped parameters and were more representative of a crash-test dummy than a human. The development of mathematical models for car crash research is proceeding rapidly, however. For example, the implementation of a model of the human spine has improved the global response of the human body to various loading conditions. For elucidating the complex dynamics of many real-world crashes, parametric studies are necessary since often many variables are unknown. One advantage of mathematical models is that they allow rapid assessment of multiple conditions. Global lumped parameter models as opposed to full finite element models, serve as a good compromise between computational efficiency and biofidelity. The goal of this study is to illustrate the utility of multi-body modeling to augment standard reconstruction techniques and medical assessment of injury causation in real-world crashes. (Author/publisher)
Abstract