在跑步机上行走时的质量中心 (CoM) 运动和脚部位置使用一次飞行时间相机
Joshua T Chang1,2, Alisha Ragatz2, Anjana Ganesh1
1Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
本研究介绍了一种使用跑步机和摄像头的快速无接触方法,通过分析质量中心 (CoM) 和支基 (BoS) 相互作用来评估跌倒风险. 这种方法提供了一种空间效率高的方法来评估临床环境中的步态稳定性.
科学领域:
- 生物力学 生物力学
- 步态分析 步态分析
- 临床评估 临床评估
背景情况:
- 在临床环境中评估患者跌倒风险是具有挑战性的,原因是空间限制和难以将传统测试与生物力学原理联系起来.
- 现有的步态稳定性评估,如定时上行测试,缺乏与基本生物力学概念的直接联系,例如质量中心 (CoM) 和支基 (BoS) 相互作用.
研究的目的:
- 开发一种快速,空间高效,无接触的方法来评估步行稳定性和跌倒风险.
- 为了捕捉身体的质量中心 (CoM) 与其支基 (BoS) 在步行过程中的相互作用.
主要方法:
- 使用1.2米跑步机和飞行时间的Azure Kinect摄像头进行数据采集.
- 使用无标记运动捕捉来确定20个关节位置,将身体分成14个部分来计算CoM.
- 在连续步骤中跟踪了CoM和共同立场,以评估步行稳定性指标.
主要成果:
- 在5分钟的时间框架内成功捕获了CoM-BoS交互.
- 启用了通过一步到步跟踪对步态稳定度指标的评估.
- 为步态分析提供了一种无标记,无接触和空间高效的方法.
结论:
- 开发的方法为在受限制的临床环境中评估跌倒风险提供了一个实际的解决方案.
- 收集的关于相对于脚位的CoM运动的数据可以促进未来开发人工智能驱动的跌倒风险识别工具.
- 这种技术增强了将步行表现与基本生物力学稳定性原则联系起来的能力.
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