论文标题

一种通用的创伤严重性计算机方法应用于行人碰撞

A Generic Trauma Severity Computer Method Applied to Pedestrian Collisions

论文作者

Bastien, Christophe, Neal-Sturgess, Clive, Davies, Huw

论文摘要

在现实世界中,创伤性伤害的严重程度是使用缩写损伤量表(AIS)测量的。但是,目前无法使用有限元元素人体计算机模型来计算AIS量表,该计算机模型计算最大主菌株(MPS)。此外,国会议员仅建立一个阈值,在该阈值中发生严重或致命的伤害。为了克服这些局限性,提出了一个独特的器官创伤模型(OTM)能够计算任何器官损伤生命的威胁。在这种情况下,重点是现实世界的行人脑损伤。 OTM使用一种功率方法,称为峰值虚拟功率(PVP),并定义了脑白色和灰色事物的响应,这是从行人碰撞运动学提取的冲击位置的函数和冲击速度的函数。这项研究包括通过包括软组织材料降解以及大脑体积变化,包括损伤严重程度计算的衰老。此外,为了说明大脑模型代表出血的拉格朗日公式的局限性,提出了一种包括硬膜下血肿的作用的方法,并将其作为OTM预测的一部分,作为本研究的OTM预测的一部分。 OTM模型针对三起现实生活中的行人事故进行了测试,并已证明可以合理地预测验尸后(PM)结果。与当前推荐的标准MPS方法相比,它的AIS预测更接近现实世界伤害的严重性。这项研究表明,通过衡量损伤严重性的能力,OTM有可能改善法医预测,并有助于改善车辆安全设计。这项研究得出结论,创伤计算的未来进展将需要开发可以预测出血的大脑模型。

In the real world, the severity of traumatic injuries are measured using the Abbreviated Injury Scale (AIS). However the AIS scale cannot currently be computed by using finite element human computer models, which calculate a maximum principal strains (MPS). Further, MPS only establishes a threshold above which a serious or fatal injury occurs. In order to overcome these limitations, a unique Organ Trauma Model (OTM) able to calculate the threat to life of any organ injury is proposed. The focus, in this case is on real world pedestrian brain injuries. The OTM uses a power method, named Peak Virtual Power (PVP), and defines brain white and grey matters trauma responses as a function of impact location and impact speed extracted from the pedestrian collision kinematics. This research has included ageing in the injury severity computation by including soft tissue material degradation, as well as brain volume changes. Further, to account for the limitations of the Lagrangian formulation of the brain model in representing haemorrhage, an approach to include the effects of subdural hematoma is proposed and included as part of the OTM predictions in this study. The OTM model was tested against three real-life pedestrian accidents and has proven to reasonably predict the Post Mortem (PM) outcome. Its AIS predictions are closer to the real world injury severity than standard MPS methods currently recommended. This study suggests that the OTM has the potential to improve forensic predictions as well as contribute to the improvement in vehicle safety design through the ability to measure injury severity. This study concludes that future advances in trauma computing would require the development of a brain model which could predict haemorrhaging.

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