Development of a Metric for Predicting Brain Strain Responses Using Head Kinematics

Abstract

Diffuse brain injuries are caused by excessive brain deformation generated primarily by rapid rotational head motion. Metrics that describe the severity of brain injury based on head motion often do not represent the governing physics of brain deformation, rendering them ineffective over a broad range of head impact conditions. This study develops a brain injury metric based on the response of a second-order mechanical system, and relates rotational head kinematics to strain-based brain injury metrics: maximum principal strain (MPS) and cumulative strain damage measure (CSDM). This new metric, universal brain injury criterion (UBrIC), is applicable over a broad range of kinematics encountered in automotive crash and sports. Efficacy of UBrIC was demonstrated by comparing it to MPS and CSDM predicted in 1600 head impacts using two different finite element (FE) brain models. Relative to existing metrics, UBrIC had the highest correlation with the FE models, and performed better in most impact conditions. While UBrIC provides a reliable measurement for brain injury assessment in a broad range of head impact conditions, and can inform helmet and countermeasure design, an injury risk function was not incorporated into its current formulation until validated strain-based risk functions can be developed and verified against human injury data.

Analysis of Swedish and Dutch accident data on cyclist injuries in cyclist-car collisions

“…Probabilistic evaluation approaches, comparable to (Forman et al 2012) should be developed for the long bones to enable the application of HBMs for the virtual testing of cyclist safety. Furthermore, a probabilistic brain injury criterion should be applied, either based on a FE brain model (Sahoo et al 2016) or on rotational loads (Gabler et al 2018).…”

Development and Multi-Scale Validation of a Finite Element Football Helmet Model

“…strain history within the brain) during an impact, which has been correlated to injury using metrics such as cumulative strain damage measure 2,46 and the universal BrIC (UBrIC). 16 Along with validated head models and injury prediction tools, there is a need for validated helmet models to more fully exploit modeling and simulation in the study of head injuries in contact sports. Because helmet rating agencies and head injury metrics both rely on head kinematics to determine injury risk, it is important to use kinematics to validate FE models of helmets.…”

Biomechanics of Periventricular Injury

“…In this study, the 95th percentile MPS is reported to alleviate the extracted responses in the ROIs from being driven by the response of a single element. As reported by Gabler and colleagues, 64 compared with the 95th percentile strain, the 50th percentile strain may be more indicative of the average deformation level. Thus, the 50th percentile MPS in the simulations of axial rotations are further checked.…”