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In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation
Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045787/ https://www.ncbi.nlm.nih.gov/pubmed/36978708 http://dx.doi.org/10.3390/bioengineering10030317 |
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author | Yu, Xiancheng Baker, Claire E. Brown, Mike Ghajari, Mazdak |
author_facet | Yu, Xiancheng Baker, Claire E. Brown, Mike Ghajari, Mazdak |
author_sort | Yu, Xiancheng |
collection | PubMed |
description | Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s(2)) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only. |
format | Online Article Text |
id | pubmed-10045787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100457872023-03-29 In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation Yu, Xiancheng Baker, Claire E. Brown, Mike Ghajari, Mazdak Bioengineering (Basel) Article Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s(2)) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only. MDPI 2023-03-02 /pmc/articles/PMC10045787/ /pubmed/36978708 http://dx.doi.org/10.3390/bioengineering10030317 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yu, Xiancheng Baker, Claire E. Brown, Mike Ghajari, Mazdak In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title | In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title_full | In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title_fullStr | In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title_full_unstemmed | In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title_short | In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation |
title_sort | in-depth bicycle collision reconstruction: from a crash helmet to brain injury evaluation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045787/ https://www.ncbi.nlm.nih.gov/pubmed/36978708 http://dx.doi.org/10.3390/bioengineering10030317 |
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