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用智能手机进行多发性硬化症的步态评估.

Keren Regev1, Noa Eren2, Ziv Yekutieli2

  • 1Neuroimmunology and Multiple Sclerosis Unit, Neurology Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.

Multiple sclerosis and related disorders
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概括

通过使用智能手机传感器检测步态变化,Mon4t®应用程序有效监测多发性硬化症 (MS) 患者. 这个数字工具提供了生态相关的数据,用于早期检测损伤和MS的临床决策.

关键词:
数字监控数字监控步态分析 步态分析多发性硬化症是多发性硬化症.一个智能手机的智能手机.

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科学领域:

  • 神经学 神经学
  • 生物医学工程 生物医学工程
  • 数字健康数字健康

背景情况:

  • 多发性硬化症 (MS) 显著影响步态,即使在疾病早期阶段.
  • 传统的步态评估方法缺乏生态相关性.
  • 该Mon4t®应用程序使用智能手机传感器进行步态参数测量.

研究的目的:

  • 评估Mon4t®技术对多发性硬化症患者监测的有效性.
  • 评估应用程序在MS患者中检测步态变化的能力.

主要方法:

  • 100名多发性硬化患者和健康对照组 (HC) 使用Mon4t ClinicTM应用程序和人类评分器进行了评估.
  • 在定时上行 (TUG) 和并行行走的测试中分析了步态.
  • 数字步行标记在MS和HC组之间进行了比较,包括基于EDSS分数的子组.

主要成果:

  • 在MS患者和HC患者之间观察到显著的步态参数差异.
  • 与HC相比,非残疾的MS患者 (EDSS=0) 显示出改变的步态,可用高置信度 (85.65%AUC) 区分.
  • 步行参数与残疾相关 (EDSS>0) 并且在残疾级别之间有显著差异.

结论:

  • 通过Mon4t®应用程序进行数字步行评估显示了增强传统MS监测的潜力.
  • 该应用程序提供了一个方便的,生态相关的工具,用于检测MS的早期步行障碍.
  • 结果支持在MS管理的临床决策中使用数字工具.