优化仪器口罩数据分析:使用交叉相关性方法进行视频同步
James Tooby1, Steve Rowson2,3, Kevin Till2,4
1Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK. j.tooby@leedsbeckett.ac.uk.
Annals of biomedical engineering
|January 21, 2025
概括
开发了两种计算方法来与视频录制同步仪器口罩 (iMG) 数据,从而能够有效分析橄球中头部加速事件 (HAE). 这些方法加快了HAE分析,改善了反和研究能力.
科学领域:
- 运动医学 运动医学
- 生物力学 生物力学
- 数据科学数据科学数据科学
背景情况:
- 头部加速事件 (HAE) 是像橄球这样的接触体育运动的一个重要问题.
- 仪器口罩 (iMG) 是橄球管理机构授权的,产生大量数据集.
- 分析iMG数据给研究人员和分析师带来了财务和时间的限制.
研究的目的:
- 介绍两种用于同步iMG数据与视频编码匹配事件的计算方法.
- 通过交叉关联同步,在视频中有效地定位HAE.
- 为了确定与HAE相关的特定匹配事件,使用后同步事件匹配进行概率计算.
主要方法:
- 交叉关联同步使iMG数据与视频播放时间标记保持一致.
- 后同步事件匹配将HAE与编码的比赛事件 (例如,球,球运输) 联系起来.
- 通过60场橄球比赛的视频验证来评估准确性和有效性,使用同步错误,PPV和灵敏度.
主要成果:
- 交叉关联同步实现了0.61-0.71秒的平均误差,所有匹配都在3秒内同步.
- 后同步事件匹配显示了高诊断准确度,PPV为0.90-0.95和灵敏度为0.99-1.00.
- 这两种方法都在使用视频编码的比赛事件数据集时证实了高准确性和有效性.
结论:
- 开发的计算方法有效地将iMG数据与视频分析同步起来.
- 实施是可行的,特别是当利用商业视频编码的匹配事件数据集时.
- 这些方法可以加快iMG分析,提高反的及时性,并支持进一步的运动伤害预防研究.
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