Analysis and modeling of the biomechanics of brain injury under impact.

摘要

To better understand brain injury mechanisms and better predict brain injuries under impact, this work focuses on the analysis of experimental brain motion data and the development of brain injury models. An analytical method is used to separate the measured brain motion into rigid body displacement and brain deformation with a minimum total squared error. Under mild impact, it is found that the whole brain has nearly pure rigid body displacement, having a magnitude of 4 to 5 mm in translation and +/-5 degrees in rotation. As the impact becomes more severe, the rigid body displacement is limited in magnitude for both translation and rotation, while the increased brain motion primarily is due to brain deformation, which is largest in the superior region of the brain.; Validated against the experimental brain motion data under low-severity impacts, new lumped-parameter brain injury models are developed to bridge the gap between simplified models that predict brain injuries based only on linear or angular accelerations and more complex finite element models that require complete knowledge of material properties and interface conditions. With proposed metrics for brain injury prediction, the new models are applied to more severe frontal and side impact tests and real-world car-pedestrian accidents. The results show that the new models are capable of predicting various brain injuries due to impact. Verified using a high-fidelity finite element model, sensitivity analysis indicates that the brain injury prediction is most sensitive to the brain moment of inertia, followed by the brain mass.