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Updated: Jun 13, 2025

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor
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基于深度感应的算法用于评估脑儿童的胸部形态学.

Olivera Tomašević1, Aleksandra Ivančić2, Luka Mejić1

  • 1Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
概括

这项研究开发了一种深度感应方法,用于跟踪物理治疗期间的胸部变化. 可靠的算法准确地测量了胸部形态,帮助评估康复进展.

关键词:
胸部的移动性 胸部的移动性患有脑的儿童.深度传感器 - 深度传感器患者形态学 患者形态学一个点云数据数据.波形变换的波形变换.

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科学领域:

  • 生物医学工程 生物医学工程
  • 康复科学 康复科学 康复科学
  • 医疗成像医学成像

背景情况:

  • 评估胸部形态变化对于物理治疗的有效性至关重要.
  • 呼吸会导致周期性的形态变化,使准确的测量变得复杂.
  • 现有的方法可能缺乏准确性来捕捉微妙的胸部变化.

研究的目的:

  • 引入一种深度感应方法来跟踪患者胸部的相对形态变化.
  • 开发强大的算法来分析物理治疗期间的胸部形态.
  • 验证拟议测量技术的可靠性和可重复性.

主要方法:

  • 使用深度传感技术进行连续的胸部记录.
  • 从最大和最小胸部体积 (吸气/呼气) 的横截面 (CSs) 提取的形态参数.
  • 使用变化系数 (CV) 评估测量可靠性和通过两次会议记录的可重复性.

主要成果:

  • CS深度值的平均CV为<2%;CS面积的平均CV为<1%,表明高可靠性.
  • 统计分析证实两次测量期间没有显著差异,支持可重现性.
  • 该算法成功评估了静静呼吸期间的胸部移动性,显示了跨会话一致的结果.

结论:

  • 拟议的深度传感算法是监测胸部形态的可靠和可重复的工具.
  • 这种方法可以有效地评估物理治疗和康复练习对胸部变化的影响.
  • 这些发现支持了这种方法在患者监测和治疗评估中的临床实用性.