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使用手腕穿戴的惯性传感器进行现实世界步态检测:验证研究

Felix Kluge1, Yonatan E Brand2, M Encarna Micó-Amigo3

  • 1Novartis Biomedical Research, Novartis Pharma AG, Basel, Switzerland.

JMIR formative research
|May 1, 2024
PubMed
概括

佩戴在手腕上的传感器可以在现实环境中检测步态序列,帮助进行移动性分析. 然而,腰部传感器在不同患者群体的步态检测中提供了更高的准确性.

关键词:
动员-D 动员-D 动员加速度计的加速计是什么?数字健康数字健康数字移动性的结果.惯性测量单位是一种惯性测量单位.验证验证的时间走路走路,走路走路,走路走路.可穿戴式传感器传感器

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科学领域:

  • 数字健康数字健康
  • 生物医学工程 生物医学工程
  • 康复技术 康复技术 康复技术

背景情况:

  • 戴在手腕上的惯性传感器对于数字健康中的真实世界移动性评估至关重要.
  • 步态检测算法对于分析长期传感器数据至关重要,但手臂运动使基于手腕的检测变得复杂.
  • 缺乏跨不同患者群体和传感器位置的手腕穿戴步态检测算法的比较验证.

研究的目的:

  • 通过使用现实世界的数据,验证手腕佩戴传感器的步态序列 (GS) 检测算法.
  • 为了比较手腕佩戴传感器算法的性能与背部佩戴传感器的性能.

主要方法:

  • 83名参与者 (包括患有帕金森病,多发性硬化症,关节骨折恢复,慢性肺炎,心力衰竭和健康的老年人) 佩戴了手腕,腰部和脚的惯性传感器.
  • 一个多传感器参考系统 (包括压力内和红外距离传感器) 用于验证.
  • 十个基于手腕的步态检测算法得到了验证,并与基于下背的算法进行了比较.

主要成果:

  • 最好的基于手腕的算法实现了0.55-0.81之间的平均灵敏度和0.95-0.98.8之间的特异性.
  • 最好的手腕算法估计的步行时间误差在8.9%至32.7%之间.
  • 腰部传感器表现出卓越的性能,平均灵敏度为0.71-0.91,特异性为0.96-0.99,步行时间误差为6.3%-23.5%,特别是在严重步行障碍患者中.

结论:

  • 佩戴在手腕上的传感器可以在现实场景中有效地检测步态序列,从而促进步态参数提取.
  • 该研究提供了关于临床步态研究中传感器放置的知情决策的证据.
  • 低背部传感器的放置通常会比手腕的放置更高的步态检测准确度,特别是在复杂的患者群体中.