BACKGROUND Recent advances in technology have enabled the development of head impact sensors, which provide a unique opportunity for sports medicine researchers to study head kinematics in contact sports. Studies have suggested that video or observer confirmation of head impact sensor data is required to remove false positives. In addition, manufacturer filtering algorithms may be ineffective in identifying true positives and removing true negatives. PURPOSE To (1) identify the percentage of video-confirmed events recorded by headband-mounted sensors in high school soccer through video analysis, overall and by sex; (2) compare video-confirmed events with the classification by the manufacturer filtering algorithms; and (3) quantify and compare the kinematics of true- and false-positive events. STUDY DESIGN Cohort study; Level of evidence, 2. METHODS Adolescent female and male soccer teams were instrumented with headband-mounted impact sensors (SIM-G; Triax Technologies) during games over 2 seasons of suburban high school competition. Sensor data were sequentially reduced to remove events recorded outside of game times, associated with players not on the pitch (ie, field) and players outside the field of view of the camera. With video analysis, the remaining sensor-recorded events were identified as an impact event, trivial event, or nonevent. The mechanisms of impact events were identified. The classifications of sensor-recorded events by the SIM-G algorithm were analyzed. RESULTS A total of 6796 sensor events were recorded during scheduled varsity game times, of which 1893 (20%) were sensor-recorded events associated with players on the pitch in the field of view of the camera during verified game times. Most video-confirmed events were impact events (n = 1316, 70%), followed by trivial events (n = 396, 21%) and nonevents (n = 181, 10%). Female athletes had a significantly higher percentage of trivial events and nonevents with a significantly lower percentage of impact events. Most impact events were head-to-ball impacts (n = 1032, 78%), followed by player contact (n = 144, 11%) and falls (n = 129, 10%) with no significant differences between male and female teams. The SIM-G algorithm correctly identified 70%, 52%, and 66% of video-confirmed impact events, trivial events, and nonevents, respectively. CONCLUSION Video confirmation is critical to the processing of head impact sensor data. Percentages of video-confirmed impact events, trivial events, and nonevents vary by sex in high school soccer. Current manufacturer filtering algorithms and magnitude thresholds are ineffective at correctly classifying sensor-recorded events and should be used with caution.

中文翻译：

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来自高中足球运动员的头部碰撞传感器数据的视频确认。

背景技术近来技术的进步使得头部碰撞传感器的发展成为可能，这为运动医学研究人员提供了研究接触运动中头部运动学的独特机会。研究表明，需要视频或观察者确认头部碰撞传感器数据才能消除误报。此外，制造商过滤算法可能无法有效识别真实阳性和消除真实阴性。目的（1）通过整体和性别的视频分析，确定高中足球中头戴式传感器记录的视频确认事件的百分比；（2）将视频确认的事件与制造商过滤算法进行的分类进行比较；（3）量化和比较正负事件的运动学。研究设计队列研究；证据水平2。方法在郊区高中比赛的2个赛季中，青少年男女足球队都在头带安装的碰撞传感器（SIM-G; Triax Technologies）进行了测试。传感器数据被顺序减少以消除在比赛时间之外记录的，与不在球场（即场地）上的玩家以及摄像机视野之外的玩家相关的事件。通过视频分析，将传感器记录的其余事件识别为冲击事件，琐碎事件或非事件。确定了影响事件的机制。分析了SIM-G算法对传感器记录的事件的分类。结果在预定的校队比赛时间中总共记录了6796个传感器事件，其中1893个（20％）是传感器记录的事件，这些事件与在经过验证的游戏时间段内摄像机视野中的运动员相关。大部分经视频确认的事件是影响事件（n = 1316，70％），其次是琐碎事件（n = 396，21％）和非事件（n = 181，10％）。女运动员的琐事和非琐事百分比显着较高，而影响项目的百分比显着较低。大多数冲击事件是头对球冲击（n = 1032，78％），其次是球员接触（n = 144，11％）和摔倒（n = 129，10％），男女球队之间没有显着差异。SIM-G算法分别正确地确定了70％，52％和66％的视频确认冲击事件，琐碎事件和非事件。结论视频确认对于头部碰撞传感器数据的处理至关重要。在高中足球中，经视频确认的影响事件，琐碎事件和非事件的百分比因性别而异。当前的制造商过滤算法和幅度阈值在正确分类传感器记录的事件方面无效，因此应谨慎使用。