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利用视频测量法对美国职业橄榄球运动中的震荡事件进行特征描述。

Characterization of Concussive Events in Professional American Football Using Videogrammetry.

作者信息

Bailey Ann M, Sherwood Christopher P, Funk James R, Crandall Jeff R, Carter Neal, Hessel David, Beier Stephen, Neale William

机构信息

Biomechanics Consulting and Research, LLC, Charlottesville, VA, USA.

Kineticorp, Greenwood Village, CO, USA.

出版信息

Ann Biomed Eng. 2020 Nov;48(11):2678-2690. doi: 10.1007/s10439-020-02637-3. Epub 2020 Oct 6.

DOI:10.1007/s10439-020-02637-3
PMID:33025319
Abstract

Sports concussions offer a unique opportunity to study head kinematics associated with mild traumatic brain injury. In this study, a model-based image matching (MBIM) approach was employed to analyze video footage of 57 concussions which occurred in National Football League (NFL) games. By utilizing at least two camera views, higher frame rate footage (> 60 images s), and laser scans of the field and helmets involved in each case, it was possible to calculate the change in velocity of the helmet during impact in six degrees of freedom. The average impact velocity for these concussive events was 8.9 ± 2.0 m s. The average changes in translational and rotational velocity for the concussed players' helmets were 6.6 ± 2.1 m s and 29 ± 13 rad s, respectively. The average change in translational velocity was higher for helmet-to-ground (n = 16) impacts compared to helmet-to-helmet (n = 30) or helmet-to-shoulder (n = 11) events (p < 0.001), while helmet-to-shoulder impacts had a smaller change in rotational velocity compared to the other impact sources (p < 0.001). By quantifying the impact velocities and locations associated with concussive impacts in professional American football, this study provides information that may be used to improve upon current helmet testing methodologies.

摘要

运动性脑震荡为研究与轻度创伤性脑损伤相关的头部运动学提供了一个独特的机会。在本研究中,采用了基于模型的图像匹配(MBIM)方法来分析美国国家橄榄球联盟(NFL)比赛中发生的57次脑震荡的视频片段。通过利用至少两个摄像机视角、更高帧率的片段(>60帧/秒)以及对每个案例中涉及的场地和头盔进行激光扫描,能够计算出头盔在撞击过程中六个自由度的速度变化。这些脑震荡事件的平均撞击速度为8.9±2.0米/秒。脑震荡球员头盔的平移速度和旋转速度的平均变化分别为6.6±2.1米/秒和29±13弧度/秒。与头盔对头盔(n = 30)或头盔对肩部(n = 11)事件相比,头盔对地(n = 16)撞击的平移速度平均变化更高(p < 0.001),而与其他撞击源相比,头盔对肩部撞击的旋转速度变化更小(p < 0.001)。通过量化与职业美式橄榄球中脑震荡撞击相关的撞击速度和位置,本研究提供了可用于改进当前头盔测试方法的信息。

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J Biomech Eng. 2019 Aug 1;141(8). doi: 10.1115/1.4043038.
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J Biomech Eng. 2019 Feb 1;141(2):0210111-02101111. doi: 10.1115/1.4042014.
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Assessment of Kinematic Brain Injury Metrics for Predicting Strain Responses in Diverse Automotive Impact Conditions.用于预测不同汽车碰撞条件下应变响应的运动学脑损伤指标评估。
Sensors (Basel). 2023 Mar 28;23(7):3538. doi: 10.3390/s23073538.
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Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis.共识头加速度测量实践(CHAMP):研究设计和统计分析。
Ann Biomed Eng. 2022 Nov;50(11):1346-1355. doi: 10.1007/s10439-022-03101-0. Epub 2022 Oct 17.
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Consensus Head Acceleration Measurement Practices (CHAMP): Origins, Methods, Transparency and Disclosure.共识头加速度测量实践(CHAMP):起源、方法、透明度和披露。
Ann Biomed Eng. 2022 Nov;50(11):1317-1345. doi: 10.1007/s10439-022-03025-9. Epub 2022 Aug 3.
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Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players.基于机器学习的分类器的开发,用于识别澳大利亚式橄榄球精英级球员的头部和身体撞击。
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Ann Biomed Eng. 2021 Oct;49(10):2760-2776. doi: 10.1007/s10439-021-02826-8. Epub 2021 Jul 14.
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