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Evaluation of brain injury criteria based on reliability analysis Cover

Evaluation of brain injury criteria based on reliability analysis

By: Máté Hazay and  Imre Bojtár  
Open Access
|Mar 2021

Abstract

Purpose: Among the proposed brain injury metrics, Brain Injury Criteria (BrIC) is a promising tool for performing safety assessment of vehicles in the future. In this paper, the available risk curves of BrIC were re-evaluated with the use of reliability analysis and new risk curves were constructed for different injury types based on literature data of tissue-level tolerances. Moreover, the comparison of different injury metrics and their corresponding risk curves were performed.

Methods: Tissue-level uncertainties of the effect and resistance were considered by random variables. The variability of the tissue-level predictors was quantified by the finite element reconstruction of 100 frontal crash tests which were performed in Simulated Injury Monitor environment. The applied tests were scaled to given BrIC magnitudes and the injury probabilities were calculated by Monte Carlo simulations. New risk curves were fitted to the observed results using Weibull and Lognormal distribution functions.

Results: The available risk curves of diffuse axonal injury (DAI) could be slightly improved, and combined AIS 4+ risk curves were obtained by considering subdural hematoma and contusion as well. The performance of several injury metrics and their risk curves were evaluated based on the observed correlations with the tissue-level predictors.

Conclusions: The cumulative strain damage measure and the BrIC provide the highest correlation (R2 = 0.61) and the most reliable risk curve for the evaluation of DAI. Although the observed correlation is smaller for other injury types, the BrIC and the associated reliability analysis-based risk curves seem to provide the best available method for estimating the brain injury risk for frontal crash tests.

DOI: https://doi.org/10.37190/abb-01755-2020-04 | Journal eISSN: 2450-6303 | Journal ISSN: 1509-409X
Language: English
Page range: 173 - 185
Submitted on: Nov 19, 2020
Accepted on: Oct 10, 2021
Published on: Mar 10, 2021
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2021 Máté Hazay, Imre Bojtár, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.