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使用二维视频图像和姿势估计人工智能在单脚着陆期间估计垂直地面反应力
Tomoya Ishida1, Takumi Ino2, Yoshiki Yamakawa1
1Faculty of Health Sciences, Hokkaido University, Japan.
Physical therapy research
|May 1, 2024
概括
在单脚着陆期间的垂直地面反应力 (VGRF) 可以使用2D视频和姿势估计AI准确估计. 这种非侵入性方法有助于物理治疗师在体育伤害评估和康复中.
科学领域:
- 生物力学 生物力学
- 运动医学 运动医学
- 医疗保健中的人工智能
背景情况:
- 垂直地面反应力 (VGRF) 评估对于体育物理治疗至关重要.
- 精确的VGRF测量有助于了解着陆机制并防止受伤.
研究的目的:
- 通过使用二维视频和姿势估计人工智能评估单脚着陆期间估计VGRF的有效性.
- 将基于人工智能的估计与传统的力板测量进行比较.
主要方法:
- 18名健康的男性从30厘米高的高度单脚着陆.
- 通过力板测量VGRF,并使用2D视频与姿势估计AI (2D-AI) 和3D运动捕捉来估计.
- 配对的t测试和皮尔森相关性分析了VGRF和错误差异.
主要成果:
- 在力板测量VGRF和2D-AI或3D-Mocap估计之间没有发现显著差异.
- 用力板 (3.37 BW) 测量的峰值VGRF与2D-AI (3.32 BW) 和3D-Mocap (3.50 BW) 的估计非常相匹配.
- 在测量和2D-AI估计的峰值VGRF之间观察到强烈的显著相关性 (R=0.835).
结论:
- 2D视频和姿势估计人工智能提供了一种临床上有用的方法,用于估计单脚着陆期间的峰值VGRF.
- 这种人工智能驱动的方法为体育物理治疗中的VGRF评估提供了一个可行的,非侵入性的替代方案.
- 这些发现支持将人工智能工具集成到临床环境中进行增强的生物力学分析.
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