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一个可解释的框架用于睡眠姿势变化检测和姿势不活动细分,使用手腕动力学.

Omar Elnaggar1, Roselina Arelhi2, Frans Coenen3

  • 1School of Engineering, University of Liverpool, Liverpool, L69 3GH, UK.

Scientific reports
|October 21, 2023
PubMed
概括

这项研究引入了一种新的可穿戴传感器框架,以准确检测睡眠姿势的变化和不活动. 这项技术提供了可靠的,基于家庭的睡眠运动分析,以获得更好的以患者为中心的护理.

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科学领域:

  • 生物医学工程 生物医学工程
  • 神经科学是一个神经科学.
  • 睡眠医学 睡眠医学

背景情况:

  • 睡眠姿势和运动是神经生理健康和生活质量的重要指标.
  • 目前的临床睡眠评估方法,如多睡眠学,是侵入性的,资源密集的.
  • 可穿戴传感器技术提供了不那么侵入性的替代方案,但可靠性和标准化算法仍然是挑战.

研究的目的:

  • 开发和评估一个全面的框架,用于客观地检测睡眠姿势的变化,并对姿势不活动的细分.
  • 用一个定制的可穿戴传感器测量临床相关的关节动力学.
  • 为潜在的临床监测和诊断提供一个可解释的框架.

主要方法:

  • 使用定制可穿戴传感器捕获关节动力学的全面框架的开发.
  • 维度减小的应用用于动力时间序列的直观3D可视化.
  • 对模拟睡眠期间五名健康参与者的手腕运动数据框架的评估.

主要成果:

  • 拟议的框架在睡眠姿势检测方面达到了高达99.2%的F1分数.
  • 对于姿势不活动的时间细分,达到了0.96的皮尔森相关系数.
  • 该框架展示了直观的3D可视化和通过尺寸缩小的可解释性.

结论:

  • 开发的框架允许对睡眠姿势和运动进行可靠,客观的分析.
  • 这项技术支持基于家庭的睡眠运动分析,用于以患者为中心的纵向护理.
  • 该框架的可解释性可能有助于临床监测和诊断.