Literature DB >> 31130209

Characteristics of pedestrian head injuries observed from real world collision data.

Guibing Li1, Fang Wang2, Dietmar Otte3, Ciaran Simms4.   

Abstract

Head injury is one of the most common injury types in vehicle-to-pedestrian collisions, which leads to death and long-term disabilities. However, detailed analysis of pedestrian head injuries in real world collisions is scarce. Thus the current study used two samples of 120 cases and 184 cases extracted from 1060 pedestrian collision cases captured during 2000-2015 from the GIDAS (German In-Depth-Accident Study) database to investigate the detailed characteristics of AIS2+ pedestrian head injuries. Firstly, the interrelationship between different head injury types (skull fracture, focal brain injury, concussion and diffuse axonal injury (DAI)) was analysed using the sample of 120 cases which each had at least one AIS2+ head injury. Then the influences of impact speed, pedestrian age and car front shape parameters on the injury risk of skull fracture, focal brain injury and concussion were assessed using the logistic regression method, based on the sample of 184 AIS1+ cases where the primary head contact location was within the windscreen glass area. The results show that: skull fractures and focal brain injuries dominate for AIS3+ head injuries and are generally associated with each other; concussion is the most important injury type for AIS2 head injuries and usually occurs in isolation. Further, for head impacts to the windscreen glass area a higher bonnet leading edge helps to reduce concussion odds, and none of the selected car front shape parameters are significant for the odds of skull fracture and focal brain injury, and vehicle impact speed and pedestrian age are insignificant for concussion. These detailed characteristics of pedestrian head injuries provide a basis for future pedestrian head injury prevention strategies with skull fractures and focal brain injuries being the most important injuries to address.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Collision data; Injury risk; Pedestrian head injury

Mesh:

Year:  2019        PMID: 31130209     DOI: 10.1016/j.aap.2019.05.007

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  5 in total

1.  A Computationally Efficient Finite Element Pedestrian Model for Head Safety: Development and Validation.

Authors:  Guibing Li; Zheng Tan; Xiaojiang Lv; Lihai Ren
Journal:  Appl Bionics Biomech       Date:  2019-07-24       Impact factor: 1.781

2.  Realistic Reference for Evaluation of Vehicle Safety Focusing on Pedestrian Head Protection Observed From Kinematic Reconstruction of Real-World Collisions.

Authors:  Guibing Li; Jinming Liu; Kui Li; Hui Zhao; Liangliang Shi; Shuai Zhang; Jin Nie
Journal:  Front Bioeng Biotechnol       Date:  2021-12-21

3.  The relationship between road traffic collision dynamics and traumatic brain injury pathology.

Authors:  Claire E Baker; Phil Martin; Mark H Wilson; Mazdak Ghajari; David J Sharp
Journal:  Brain Commun       Date:  2022-02-12

4.  Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea.

Authors:  Seung-Hoon Park; Min-Kyung Bae
Journal:  Int J Environ Res Public Health       Date:  2020-03-31       Impact factor: 3.390

5.  A Computational Biomechanics Human Body Model Coupling Finite Element and Multibody Segments for Assessment of Head/Brain Injuries in Car-To-Pedestrian Collisions.

Authors:  Chao Yu; Fang Wang; Bingyu Wang; Guibing Li; Fan Li
Journal:  Int J Environ Res Public Health       Date:  2020-01-13       Impact factor: 3.390

  5 in total

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