As more is learned about injury mechanisms of concussion and scenarios under which injuries are sustained in football games, methods used to evaluate protective equipment must adapt. A combination of video review, videogrammetry, and laboratory reconstructions was used to characterize concussive impacts from National Football League games during the 2015-2017 seasons. Test conditions were generated based upon impact locations and speeds from this data set, and a method for scoring overall helmet performance was created. Head kinematics generated using a linear impactor and sliding table fixture were comparable to those from laboratory reconstructions of concussive impacts at similar impact conditions. Impact tests were performed on 36 football helmet models at two laboratories to evaluate the reproducibility of results from the resulting test protocol. Head acceleration response metric, a head impact severity metric, varied 2.9–5.6% for helmet impacts in the same lab, and 3.8–6.0% for tests performed in a separate lab when averaged by location for the models tested. Overall inter-lab helmet performance varied by 1.1 ± 0.9%, while the standard deviation in helmet performance score was 7.0%. The worst helmet performance score was 33% greater than the score of the best-performing helmet evaluated by this study.

随着对脑震荡的损伤机制和足球比赛中受伤的情景了解得越来越多，用于评估防护装备的方法必须适应。视频审查、视频测量和实验室重建相结合，用于描述 2015-2017 赛季美国国家橄榄球联盟比赛的震荡影响。根据来自该数据集的撞击位置和速度生成测试条件，并创建了一种对整体头盔性能进行评分的方法。使用线性冲击器和滑动台固定装置生成的头部运动学与在类似冲击条件下实验室重建的震荡冲击相当。在两个实验室对 36 个橄榄球头盔模型进行了冲击测试，以评估所得测试协议结果的可重复性。头部加速度响应指标（头部碰撞严重程度指标）在同一实验室中的头盔碰撞变化为 2.9-5.6%，而在单独实验室进行的测试中，当按测试模型的位置进行平均时，其变化为 3.8-6.0%。实验室间头盔的整体性能变化为 1.1 ± 0.9%，而头盔性能得分的标准偏差为 7.0%。最差头盔性能得分比本研究评估的性能最佳头盔得分高 33%。实验室间头盔的整体性能变化为 1.1 ± 0.9%，而头盔性能得分的标准偏差为 7.0%。最差头盔性能得分比本研究评估的性能最佳头盔得分高 33%。实验室间头盔的整体性能变化为 1.1 ± 0.9%，而头盔性能得分的标准偏差为 7.0%。最差头盔性能得分比本研究评估的性能最佳头盔得分高 33%。