Funk James R, Jadischke Ron, Bailey Ann, Crandall Jeff, McCarthy Joe, Arbogast Kristy, Myers Barry
Biocore LLC, 1627 Quail Run, Charlottesville, VA, 22911, USA.
McCarthy Engineering Inc, 2280 Ambassador Drive, Windsor, ON, N9C 4E4, Canada.
Ann Biomed Eng. 2020 Nov;48(11):2652-2666. doi: 10.1007/s10439-020-02632-8. Epub 2020 Sep 30.
Seventeen concussive helmet-to-helmet impacts occurring in National Football League (NFL) games were analyzed using video footage and reconstructed by launching helmeted crash test dummies into each other in a laboratory. Helmet motion on-field and in the laboratory was tracked in 3D before, during, and after impact in multiple high frame rate video views. Multiple (3-10) tests were conducted for each of the 17 concussive cases (100 tests total) with slight variations in input conditions. Repeatability was assessed by duplicating one or two tests per case. The accuracy of the input conditions in each reconstruction was assessed based on how well the closing velocity, impact locations, and the path eccentricity of the dummy heads matched the video analysis. The accuracy of the reconstruction output was assessed based on how well the changes in helmet velocity (translational and rotational) from the impact matched the video analysis. The average absolute error in helmet velocity changes was 24% in the first test, 20% in the tests with the most accurate input configuration, and 14% in the tests with minimal error. Coefficients of variation in 22 repeated test conditions (1-2 per case) averaged 3% for closing velocity, 7% for helmet velocity changes, and 8% for peak head accelerations. Iterative testing was helpful in reducing error. A combination of sophisticated video analysis, articulated physical surrogates, and iterative testing was required to reduce the error to within half of the effect size of concussion.
利用视频片段对美国国家橄榄球联盟(NFL)比赛中发生的17次头盔对头盔的撞击进行了分析,并通过在实验室中让佩戴头盔的碰撞测试假人相互碰撞进行了重建。在多个高帧率视频视图中,对撞击前、撞击中和撞击后头盔在场上和实验室中的运动进行了三维跟踪。对这17起脑震荡案例中的每一起都进行了多次(3 - 10次)测试(总共100次测试),输入条件略有不同。通过对每个案例重复进行一两次测试来评估重复性。根据假人头的闭合速度、撞击位置和路径偏心率与视频分析的匹配程度,评估每次重建中输入条件的准确性。根据撞击导致的头盔速度(平移和旋转)变化与视频分析的匹配程度,评估重建输出的准确性。在第一次测试中,头盔速度变化的平均绝对误差为24%,在输入配置最准确的测试中为20%,在误差最小的测试中为14%。在22个重复测试条件下(每个案例1 - 2次),闭合速度的变异系数平均为3%,头盔速度变化的变异系数平均为7%,头部峰值加速度的变异系数平均为8%。迭代测试有助于减少误差。需要结合复杂的视频分析、关节式物理替身和迭代测试,将误差降低到脑震荡效应大小的一半以内。