Brain Response of a Computational Head Model for Prescribed Skull Kinematics and Simulated 3 Football Helmet Impact Boundary Conditions

Abstract

Computational human body models (HBM) present a novel approach to predict brain response 3 in football impact scenarios, with prescribed kinematic boundary conditions for the HBM skull 4 typically used at present. However, computational optimization of helmets requires simulation 5 of the coupled helmet and HBM model; which is much more complex and has not been assessed 6 in the context of brain deformation and existing simplified approaches. In the current study, two 7 boundary conditions and the resulting brain deformations were compared using a HBM head 8 model: (1) a prescribed skull kinematics (PK) boundary condition using measured head kinematics 9 from experimental impacts; and (2) a novel detailed simulation of a HBM head and neck, helmet 10 and linear impactor (HBM‐S). While lateral and rear impacts exhibited similar levels of maximum 11 principal strain (MPS) in the brain tissue using both boundary conditions, differences were noted 12 in the frontal orientation (at 9.3 m/s, MPS was 0.39 for PK, 0.54 for HBM‐S). Importantly, both PK 13 and HBM‐S boundary conditions produced a similar distribution of MPS throughout the brain for 14 each impact orientation considered. Within the corpus callosum and thalamus, high MPS was 15 associated with lateral impacts and lower values with frontal and rear impacts. The good 16 correspondence of both boundary conditions is encouraging for future optimization of helmet 17 designs. A limitation of the PK approach is the need for experimental head kinematics data, while 18 the HBM‐S can predict brain response for varying impact conditions and helmet configurations, 19 with potential as a tool to improve helmet protection performance.