Assessment of Kinematic Brain Injury Metrics for Predicting Strain Responses in Diverse Automotive Impact Conditions

Ann Biomed Eng. 2016 Dec;44(12):3705-3718. doi: 10.1007/s10439-016-1697-0. Epub 2016 Jul 19.

Abstract

Numerous injury criteria have been developed to predict brain injury using the kinematic response of the head during impact. Each criterion utilizes a metric that is some mathematical combination of the velocity and/or acceleration components of translational and/or rotational head motion. Early metrics were based on linear acceleration of the head, but recent injury criteria have shifted towards rotational-based metrics. Currently, there is no universally accepted metric that is suitable for a diverse range of head impacts. In this study, we assessed the capability of fifteen existing kinematic-based metrics for predicting strain-based brain response using four different automotive impact conditions. Tissue-level strains were obtained through finite element model simulation of 660 head impacts including occupant and pedestrian crash tests, and pendulum head impacts. Correlations between head kinematic metrics and predicted brain strain-based metrics were evaluated. Correlations between brain strain and metrics based on angular velocity were highest among those evaluated, while metrics based on linear acceleration were least correlative. BrIC and RVCI were the kinematic metrics with the highest overall correlation; however, each metric had limitations in certain impact conditions. The results of this study suggest that rotational head kinematics are the most important parameters for brain injury criteria.

Keywords: Brain injury criteria; Finite element modeling; Head kinematics; Rotational; Translational.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acceleration*
  • Accidents, Traffic*
  • Biomechanical Phenomena
  • Brain Injuries, Traumatic*
  • Humans