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In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation.

Authors :
Yu, Xiancheng
Baker, Claire E.
Brown, Mike
Ghajari, Mazdak
Source :
Bioengineering (Basel). Mar2023, Vol. 10 Issue 3, p317. 16p.
Publication Year :
2023

Abstract

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/s2) 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23065354
Volume :
10
Issue :
3
Database :
Academic Search Index
Journal :
Bioengineering (Basel)
Publication Type :
Academic Journal
Accession number :
162747672
Full Text :
https://doi.org/10.3390/bioengineering10030317