Ranking of Biomechanical Metrics to Describe Human Response to Impact-Induced Damage

N. Devogel, A. Banerjee, F. Pintar, N. Yoganandan
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Abstract

Determination of human tolerance to impact-induced damage or injury is needed to assess and improve safety in military, automotive, and sport environments. Impact biomechanics experiments using post mortem human surrogates (PMHS) are routinely used to this objective. Risk curves representing the damage of the tested components of the PMHS are developed using the metrics gathered from the experimental process. To determine the metric that best explains the underlying response to the observed damage, statistical analysis is required of all the output response metrics (such as peak force to injury) along with the examination of potential covariates. This is conducted by parametric survival analysis. The objective of this study is to present a robust statistical methodology that can be effectively used to achieve these goals by choosing the best metric explaining injury and provide a ranking of the metrics. Previously published data from foot-ankle-lower leg experiments were used with two possible forms of censoring: right and left censoring or right and exact censoring, representing the no injury and injury data points in a different manner. The statistical process and scoring scheme were based on the predictive ability assessed by the Brier Score Metric (BSM) which was used to rank the metrics. Response metrics were force, time to peak, and rate. The analysis showed that BSM is effective in incorporating different covariates: age, posture, stature, device used to deliver the impact load, and the personal protective equipment (PPE), i.e., military boot. The BSM-based analysis indicated that the peak force was the highest ranked metric for the exact censoring scheme and the age was a significant covariate, and that peak force was also the highest ranked metric for the left censored scheme and the PPE covariate was statistically significant. IRCs are presented for the best metric.
描述人类对撞击引起的损伤反应的生物力学指标排名
在军事、汽车和运动环境中,需要确定人体对撞击引起的损伤或伤害的耐受性,以评估和提高安全性。使用死后人体替代物(PMHS)的冲击生物力学实验通常用于这一目的。利用从实验过程中收集的指标,开发了代表PMHS测试部件损伤的风险曲线。为了确定最能解释对观察到的损伤的潜在反应的度量,需要对所有输出响应度量(如损伤的峰值力)进行统计分析,并检查潜在的协变量。这是通过参数生存分析进行的。本研究的目的是提出一种可靠的统计方法,通过选择解释损伤的最佳指标并提供指标排名,可以有效地用于实现这些目标。先前发表的足-踝-小腿实验数据使用两种可能的审查形式:右和左审查或右和精确审查,以不同的方式表示无损伤和损伤数据点。统计过程和评分方案基于Brier评分指标(BSM)评估的预测能力,BSM用于对指标进行排序。反应指标是力量、达到峰值的时间和速率。分析表明,结合不同的协变量:年龄、姿势、身材、用于传递冲击载荷的装置和个人防护装备(PPE),即军用靴,BSM是有效的。基于bsm的分析表明,峰值力是精确删减方案中排名最高的度量,年龄是显著的协变量;峰值力也是左侧删减方案中排名最高的度量,PPE协变量具有统计学意义。irc是为最佳度量而提出的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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