在整个家庭环境中进行的日常生活活动中的关节功能和运动变化:数字双胞胎建模研究
Zhou Fang1, Mohammad Yavari1, Yiqun Chen2
1Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC 3010, Australia.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
这项研究创建了一个家庭的数字双胞胎,在日常活动中跟踪关节运动. 数字双胞胎框架可以帮助家庭康复和人体工程设计.
科学领域:
- 生物力学 生物力学
- 人与计算机的交互
- 数字健康数字健康
背景情况:
- 在自然家庭环境中评估人类的流动性是一项挑战.
- 实验室环境对于现实世界联合运动分析缺乏生态有效性.
- 之前的研究还没有足够地测量关节运动和在家庭环境中分类任务.
研究的目的:
- 开发家庭环境的数字双胞胎,用于测量和可视化关节运动.
- 在数字双胞胎中使用传感器数据对日常生活活动 (ADL) 进行分类.
- 研究家庭环境在ADL期间对关节运动的影响.
主要方法:
- 一个单卧室的公寓用3D摄影测量技术进行了数字重建,以创建一个数字双胞胎.
- 十名健康成年人在佩戴惯性测量单元和超宽带传感器时进行了19次ADL.
- 监督机器学习用于任务分类,并将联合运动数据注册到数字家居模型中.
主要成果:
- 监督机器学习在分类日常生活任务方面实现了82.3%的准确性.
- 特定的ADL显示出明显的关节运动模式,例如,在理头发时最大的肩膀升高和在坐立时最大的部/膝盖曲.
- 关节运动在不同房间有显著的变化,影响了步行速度和脚背部屈曲.
结论:
- 在ADL期间的关节运动受到家庭内部环境的显著影响.
- 开发的数字双胞胎框架为分析家庭环境中的人类流动性提供了一种可行的方法.
- 这种方法在家庭康复,远程患者监控和人体工程学室内设计方面具有潜在的应用.
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