Minimization of Analytical Injury Metrics for Head Impact Injuries

Abstract

Objective: To compare the predictions of the head injury criterion (HIC), currently used to predict the risk of traumatic brain injury in frontal vehicle impact and pedestrian impact tests, with the predictions of other empirical and analytical injury metrics. Methods: The appropriateness of different criteria relative to injury metrics derived from a head finite element (FE) model is investigated for different deceleration pulses in this research. Empirical injury metrics are computed by direct calculation for different analyzed pulses. In addition, for each pulse full FE model simulations of a complete human head were performed by means of the SIMon model. The computations are used to calculate the analytical injury metrics. Results: This article shows that an optimal head deceleration curve based on HIC does not minimize other analytical injury metrics. The results obtained in this study suggest that the HIC criterion does not necessarily provide the same severity ranking for different external loadings to the head as the injury metrics derived from the FE models. Conclusion: Countermeasures designed based only on HIC could differ significantly from those based on analytical injury measures computed by FE models. The use of multiple injury metrics is recommended given that no scalar measure seems to be positively and strongly correlated with relevant injury metrics.