Bicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall’s tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.

自行车头盔被证明可以防止头部受伤。评级方法和测试标准用于评估不同的头盔设计和安全性能。从有限元脑损伤模型中获得的基于应变的损伤标准和从全局运动学响应中获得的指标都可用于评估头盔安全性能。人们对不同的伤害模型或伤害指标如何对不同的头盔进行排名和评级知之甚少。本研究的目的是确定基于全局运动学的八个大脑模型和八个指标如何对大量受到倾斜冲击的自行车头盔 (n=17) 进行排名和评级。结果表明，排名和评级受模型和指标选择的影响。肯德尔的 tau 在 0.50 和 0 之间变化。当排名基于大脑模型的最大主要应变时，为 95。一个特定的头盔在使用一个大脑模型时被评为 2 星，但在另一个模型中被评为 4 星。这可能会给消费者造成混淆，而不是让他们了解头盔的相对安全性能。因此，我们建议生物力学界应该为未来的排名和评级方法制定规范或建议。