Duma Lauren A, Begonia Mark T, Miller Barry, Jung Caitlyn, Wood Matthew, Duma Brock G, Rowson Steve
Virginia Tech Helmet Lab, Blacksburg, VA, 24061, USA.
Ann Biomed Eng. 2025 Apr 28. doi: 10.1007/s10439-025-03723-0.
The current equestrian helmet standards set minimal requirements for passing helmets, highlighting the need for a rating system that differentiates helmets based on their impact performance. This study's objectives were to compare equestrian helmet impact response kinematics between linear-driven and oblique impact conditions and then to evaluate the effect of incorporating oblique drop tests into a previously established equestrian helmet rating system, Equestrian STAR.
Oblique drop tests were conducted with 45 equestrian helmet models at two impact locations, front boss and rear boss, at an impact velocity of 6.56 m/s. The resulting peak linear and rotational head accelerations were compared to those measured during linear-driven pendulum impacts on the same helmet models. A total of 720 impact tests were performed, making this the largest published study on equestrian helmets to date. Equestrian STAR was modified to include both pendulum and oblique impacts by computing and summing weighted concussion risks for each test condition.
Oblique impacts had peak linear accelerations ranging from 105.8 to 204.5 g and peak rotational accelerations ranging from 3304 to 13854 rad/s. Between the linear-driven and oblique impacts, peak linear acceleration was weakly correlated (R = 0.34, p < 0.001), while peak rotational acceleration was not correlated (R = 0.04, p = 0.21). Equestrian STAR scores calculated using both pendulum and oblique impacts suggested that the worst-performing helmet on both systems had nearly four times the concussion risk as the best-performing.
Pendulum and oblique impacts have different methods of generating head rotation, which can highlight different modes of helmet performance. The updated Equestrian STAR helmet rating system differentiates between high-performing and low-performing helmets, enabling equestrians to purchase helmets best at reducing concussion risk and providing companies with a process to compare their helmet designs.
当前的马术头盔标准规定了合格头盔的最低要求，这凸显了建立一个基于冲击性能区分头盔的评级系统的必要性。本研究的目的是比较线性驱动冲击和斜向冲击条件下马术头盔的冲击响应运动学，然后评估将斜向跌落测试纳入先前建立的马术头盔评级系统“马术之星”（Equestrian STAR）的效果。
对45种马术头盔模型在两个冲击位置（前帽舌和后帽舌）进行斜向跌落测试，冲击速度为6.56米/秒。将由此产生的头部线性和旋转加速度峰值与在相同头盔模型上进行线性驱动摆锤冲击时测得的结果进行比较。总共进行了720次冲击测试，这是迄今为止关于马术头盔发表的规模最大的研究。通过计算并汇总每种测试条件下的加权脑震荡风险，对“马术之星”进行了修改，使其包括摆锤冲击和斜向冲击。
斜向冲击的线性加速度峰值范围为105.8至204.5g，旋转加速度峰值范围为3304至13854rad/s。在直线驱动冲击和斜向冲击之间，峰值线性加速度呈弱相关（R = 0.34，p < 0.001），而峰值旋转加速度不相关（R = 0.04，p = 0.21）。使用摆锤冲击和斜向冲击计算得出的“马术之星”分数表明，两个系统中表现最差的头盔的脑震荡风险几乎是表现最佳头盔的四倍。
摆锤冲击和斜向冲击产生头部旋转的方式不同，这可以凸显头盔性能的不同模式。更新后的“马术之星”头盔评级系统区分了高性能和低性能头盔，使骑手能够购买最能降低脑震荡风险的头盔，并为公司提供了一个比较其头盔设计的流程。
