Modal analysis of computational human brain dynamics during helmeted impacts

Abstract

Sports-related mild traumatic brain injury (mTBI) is a growing public health concern, affecting millions in the U.S., annually. Current helmets are primarily designed to mitigate head kinematics, despite the importance of the brain substructures mechanics in mTBI mechanism. Therefore, it is crucial to consider the dynamical behavior of brain substructures, which has been shown in prior studies to be associated with strain concentration. Here, we studied the modal behavior and strain patterns of the substructures of the brain finite element (FE) model through Dynamic Mode Decomposition. We conducted side and front impact pendulum tests on a dummy headform equipped with hockey, football, ski, and bicycle helmets. After simulating the impact tests using a brain FE model, we calculated the dynamic modes of this computational model for the whole brain, corpus callosum, brainstem, and cerebellum. The main mode of oscillation in all regions for all helmet types occurred around the frequency regime of 7–15 Hz. Also, in cerebellum, a second harmonic was observed at 40–50 Hz in front impact, and 38 and 62 Hz in side impact in bicycle and ski helmets, respectively. Furthermore, we analyzed the correlation between the modal response and peak maximum principal strain (MPS). These analyses mostly showed a direct association between the computational modal behavior and MPS, where helmet tests with closely spaced modes and high-frequency modal amplitudes led to higher MPS values. This association between the computational modal behavior and strain patterns demonstrated a potential for improving helmet designs through a novel design objective.