Finite element analysis of the effect of loading curve shape on brain injury predictors

Prediction of traumatic and mild traumatic brain injury is an important factor in managing their prevention. Currently, the prediction of these injuries is limited to peak linear and angular acceleration loading curves derived from laboratory reconstructions. However it remains unclear as to what aspect of these loading curves contributes to brain tissue damage. This research will use the University College Dublin Brain Trauma Model (UCDBTM) to analyze three distinct loading curve shapes meant to represent different helmet loading scenarios. The loading curves were applied independently in each axis of linear and angular acceleration, and their effect on currently used predictors of TBI and mTBI. Loading curve shape A had a late time to peak, B an early time to peak and C had a consistent plateau. The areas for all three loading curve shapes were identical. The results indicate that loading curve A produced consistently higher maximum principal strains and Von Mises Stress than the other two loading curve types. Loading curve C consistently produced the lowest values, with loading curve B being lowest in only 2 cases. The areas of peak Von Mises Stress and Principal strain also varied depending on loading curve shape and acceleration input.