Integrating Human and Nonhuman Primate Data to Estimate Human Tolerances for Traumatic Brain InjurySource: Journal of Biomechanical Engineering:;2022:;volume( 144 ):;issue: 007::page 71003-1Author:Wu, Taotao
,
Sato, Fusako
,
Antona-Makoshi, Jacobo
,
Gabler, Lee F.
,
Giudice, J. Sebastian
,
Alshareef, Ahmed
,
Yaguchi, Masayuki
,
Masuda, Mitsutoshi
,
Margulies, Susan S.
,
Panzer, Matthew B.
DOI: 10.1115/1.4053209Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Traumatic brain injury (TBI) contributes to a significant portion of the injuries resulting from motor vehicle crashes, falls, and sports collisions. The development of advanced countermeasures to mitigate these injuries requires a complete understanding of the tolerance of the human brain to injury. In this study, we developed a new method to establish human injury tolerance levels using an integrated database of reconstructed football impacts, subinjurious human volunteer data, and nonhuman primate data. The human tolerance levels were analyzed using tissue-level metrics determined using harmonized species-specific finite element (FE) brain models. Kinematics-based metrics involving complete characterization of angular motion (e.g., diffuse axonal multi-axial general evaluation (DAMAGE)) showed better power of predicting tissue-level deformation in a variety of impact conditions and were subsequently used to characterize injury tolerance. The proposed human brain tolerances for mild and severe TBI were estimated and presented in the form of injury risk curves based on selected tissue-level and kinematics-based injury metrics. The application of the estimated injury tolerances was finally demonstrated using real-world automotive crash data.
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contributor author | Wu, Taotao | |
contributor author | Sato, Fusako | |
contributor author | Antona-Makoshi, Jacobo | |
contributor author | Gabler, Lee F. | |
contributor author | Giudice, J. Sebastian | |
contributor author | Alshareef, Ahmed | |
contributor author | Yaguchi, Masayuki | |
contributor author | Masuda, Mitsutoshi | |
contributor author | Margulies, Susan S. | |
contributor author | Panzer, Matthew B. | |
date accessioned | 2022-05-08T09:43:00Z | |
date available | 2022-05-08T09:43:00Z | |
date copyright | 2/15/2022 12:00:00 AM | |
date issued | 2022 | |
identifier issn | 0148-0731 | |
identifier other | bio_144_07_071003.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4285496 | |
description abstract | Traumatic brain injury (TBI) contributes to a significant portion of the injuries resulting from motor vehicle crashes, falls, and sports collisions. The development of advanced countermeasures to mitigate these injuries requires a complete understanding of the tolerance of the human brain to injury. In this study, we developed a new method to establish human injury tolerance levels using an integrated database of reconstructed football impacts, subinjurious human volunteer data, and nonhuman primate data. The human tolerance levels were analyzed using tissue-level metrics determined using harmonized species-specific finite element (FE) brain models. Kinematics-based metrics involving complete characterization of angular motion (e.g., diffuse axonal multi-axial general evaluation (DAMAGE)) showed better power of predicting tissue-level deformation in a variety of impact conditions and were subsequently used to characterize injury tolerance. The proposed human brain tolerances for mild and severe TBI were estimated and presented in the form of injury risk curves based on selected tissue-level and kinematics-based injury metrics. The application of the estimated injury tolerances was finally demonstrated using real-world automotive crash data. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Integrating Human and Nonhuman Primate Data to Estimate Human Tolerances for Traumatic Brain Injury | |
type | Journal Paper | |
journal volume | 144 | |
journal issue | 7 | |
journal title | Journal of Biomechanical Engineering | |
identifier doi | 10.1115/1.4053209 | |
journal fristpage | 71003-1 | |
journal lastpage | 71003-10 | |
page | 10 | |
tree | Journal of Biomechanical Engineering:;2022:;volume( 144 ):;issue: 007 | |
contenttype | Fulltext |