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用于行人数值模拟的小儿下肢数据综述:损伤流行病学、解剖学、人体测量学、结构和力学特性

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

作者信息

Meng Yunzhu, Untaroiu Costin D

机构信息

Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, USA.

出版信息

Appl Bionics Biomech. 2018 Sep 4;2018:6271898. doi: 10.1155/2018/6271898. eCollection 2018.

Abstract

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.

摘要

行人受伤是1至19岁儿童非故意伤害相关死亡的第四大原因。在汽车与行人碰撞事故中,下肢是最常受伤的身体部位。本研究的目的是对与行人下肢损伤、解剖学、人体测量学、结构和力学性能相关的数据进行系统综述,这些数据可用于开发新的儿科计算模型。该研究首先回顾了与儿科行人事故相关的流行病学数据。还介绍了儿童下肢的解剖结构和与年龄相关的人体测量数据。然后,总结了文献中提供的下肢主要组成部分(如骨骼、软骨、膝关节韧带、肌肉、肌腱和生长板)的力学和结构特性。该研究最后简要描述了当前的儿童行人模型,其中包括对其局限性的讨论。我们相信,本综述研究中包含的数据有助于提高当前儿童模型的生物逼真度,并支持安全研究人员用于保护儿童群体的新儿童模型的开发和验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f63/6142772/ff0ad25fa391/ABB2018-6271898.001.jpg

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