A Review of Pediatric Lower Extremity Data for Pedestrian Numerical Modeling: Injury Epidemiology, Anatomy, Anthropometry, Structural, and Mechanical Properties

Pedestrian injuries are the fourth leading cause of unintentional injury-related death among children aged 1 to 19. The lower extremity represents the most frequently injured body region in car-to-pedestrian accidents. The goal of this study was to perform a systematic review of the data related to...

Full description

Saved in:
Bibliographic Details
Main Authors: Yunzhu Meng, Costin D. Untaroiu
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Applied Bionics and Biomechanics
Online Access:http://dx.doi.org/10.1155/2018/6271898
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Pedestrian injuries are the fourth leading cause of unintentional injury-related death among children aged 1 to 19. The lower extremity represents the most frequently injured body region in car-to-pedestrian accidents. The goal of this study was to perform a systematic review of the data related to pedestrian lower extremity injuries, anatomy, anthropometry, structural, and mechanical properties, which can be used in the development of new pediatric computational models. The study began with a review of epidemiologic data related to pediatric pedestrian accidents. Anatomy of the child lower extremity and age-related anthropometry data were presented as well. Then, both the mechanical and structural properties of the lower extremity main components (e.g., bones, cartilages, knee ligaments, muscles, tendons, and growth plates) available in literature were summarized. The study concluded with a brief description of current child pedestrian models, which included a discussion about their limitations. We believe that data included in this review study can help in improving the biofidelity of current child models and support the development and validation of new child models used by safety researchers for protection of pediatric population.
ISSN:1176-2322
1754-2103