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A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis

Concussions represent an increasing economic burden to society. Motor vehicle collisions (MVCs) are of the leading causes for sustaining a concussion, potentially due to high head accelerations. The change in velocity (i.e., delta-V) of a vehicle in a MVC is an established metric for impact severity...

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Autores principales: Limousis-Gayda, Manon, Hashish, Rami
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244952/
https://www.ncbi.nlm.nih.gov/pubmed/32508983
http://dx.doi.org/10.1155/2020/9679372
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author Limousis-Gayda, Manon
Hashish, Rami
author_facet Limousis-Gayda, Manon
Hashish, Rami
author_sort Limousis-Gayda, Manon
collection PubMed
description Concussions represent an increasing economic burden to society. Motor vehicle collisions (MVCs) are of the leading causes for sustaining a concussion, potentially due to high head accelerations. The change in velocity (i.e., delta-V) of a vehicle in a MVC is an established metric for impact severity. Accordingly, the purpose of this paper is to analyze findings from previous research to determine the relation between delta-V and linear head acceleration, including occupant parameters. Data was collected from previous research papers comprising both linear head acceleration and delta-V at the time of incident, head position of the occupant, awareness of the occupant prior to impact, as well as gender, age, height, and weight. Statistical analysis revealed the following significant power relation between delta-V and head acceleration: head acceleration = 0.465delta‐V(1.3231) (R(2) = 0.5913, p < 0.001). Further analysis revealed that alongside delta-V, the occupant's gender and head position prior to impact were significant predictors of head acceleration (p = 0.022 and p = 0.001, respectively). The strongest model developed in this paper is considered physiologically implausible as the delta-V corresponding to a theoretical concussion threshold of 80 g exceeds the delta-V associated with probability of fatality. Future research should be aimed at providing a more thorough data set of the occupant head kinematics in MVCs to help develop a stronger predictive model for the relation between delta-V and head linear and angular acceleration.
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spelling pubmed-72449522020-06-06 A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis Limousis-Gayda, Manon Hashish, Rami Appl Bionics Biomech Review Article Concussions represent an increasing economic burden to society. Motor vehicle collisions (MVCs) are of the leading causes for sustaining a concussion, potentially due to high head accelerations. The change in velocity (i.e., delta-V) of a vehicle in a MVC is an established metric for impact severity. Accordingly, the purpose of this paper is to analyze findings from previous research to determine the relation between delta-V and linear head acceleration, including occupant parameters. Data was collected from previous research papers comprising both linear head acceleration and delta-V at the time of incident, head position of the occupant, awareness of the occupant prior to impact, as well as gender, age, height, and weight. Statistical analysis revealed the following significant power relation between delta-V and head acceleration: head acceleration = 0.465delta‐V(1.3231) (R(2) = 0.5913, p < 0.001). Further analysis revealed that alongside delta-V, the occupant's gender and head position prior to impact were significant predictors of head acceleration (p = 0.022 and p = 0.001, respectively). The strongest model developed in this paper is considered physiologically implausible as the delta-V corresponding to a theoretical concussion threshold of 80 g exceeds the delta-V associated with probability of fatality. Future research should be aimed at providing a more thorough data set of the occupant head kinematics in MVCs to help develop a stronger predictive model for the relation between delta-V and head linear and angular acceleration. Hindawi 2020-05-13 /pmc/articles/PMC7244952/ /pubmed/32508983 http://dx.doi.org/10.1155/2020/9679372 Text en Copyright © 2020 Manon Limousis-Gayda and Rami Hashish. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Limousis-Gayda, Manon
Hashish, Rami
A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title_full A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title_fullStr A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title_full_unstemmed A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title_short A Proposed Algorithm to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
title_sort proposed algorithm to assess concussion potential in rear-end motor vehicle collisions: a meta-analysis
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244952/
https://www.ncbi.nlm.nih.gov/pubmed/32508983
http://dx.doi.org/10.1155/2020/9679372
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