Head injury criteria assessment using head kinematics from crash tests and accident reconstructions. (2nd January 2023)

• Record Type: Journal Article
• Authors: Östh, Jonas; Bohman, Katarina; Jakobsson, Lotta
• Is Part Of: Traffic injury prevention. Volume 24:Number 1(2023)
• Page Start: 56
• Page End: 61
• Publication Date: 2023-01-02
• Subjects: Brain injury criteria -- Finite Element -- head model -- THOR -- WorldSID; Traffic safety -- Periodicals; Traffic accidents -- Periodicals; Wounds and injuries -- Prevention -- Periodicals; 363.125
• DOI: 10.1080/15389588.2022.2143238
• Languages: English
• ISSNs: 1538-9588

Abstract

Abstract: Objective: The aim of this study was to assess head injury criteria based on their correlation to brain strain in a Finite Element (FE) head model (the KTH Royal Institute of Technology model), by simulation of head kinematics data from frontal and side crash tests with Anthropomorphic Test Devices (ATDs), and from Human Body Model (HBM) accident reconstructions. Methods: Six Degrees of Freedom (DoF) head kinematic data was extracted from 221 crash tests, consisting of frontal impacts with the THOR-50M ATD, near-side and far-side impacts with the WorldSID-50M ATD, and from 19 FE HBM accident reconstructions. The head injury criteria HIC15, HIP, BrIC, UBrIC, DAMAGE and CIBIC were calculated, and FE head model simulations were conducted using the six DoF kinematics data. The 100th, 99th, and 95th percentile Maximum Principal Strains (MPS) of the brain were extracted and linear regression models with respect to the injury criteria were created. The injury criteria were then evaluated based on the coefficient of determination, R 2, and the Normalized Root Mean Square Error (NRMSE) of each regression model. Results: For all the data sets combined and for the WorldSID far-side data, CIBIC had the best goodness of fit, with R 2 of 0.76 and 0.85. For frontal impacts with THOR and the combined ATD data set, DAMAGE had highest R 2, 0.83 and 0.78, respectively. Injury criteria including translational accelerations were ranked lower, and BrIC were among the three lowest ranked for most data sets evaluated. UBrIC generally ranked after DAMAGE and CIBIC with respect to the goodness of fit but had the lowest NRMSE for all data sets. Conclusions: The two mass-spring-damper brain surrogate model criteria, DAMAGE and CIBIC, were best in capturing the head model MPS response for both the THOR and WorldSID data sets. BrIC had lower correlation to the head model MPS and performed marginally better than the linear acceleration only criteria for all the data sets combined. This study supports the suitability of DAMAGE and CIBIC as brain injury criteria to be used with THOR-50M and WorldSID-50M in vehicle crash test conditions, as they outperform BrIC.