模拟公共交通不稳定性:一种新的VR和基于斯图尔特平台的平衡训练方法
概括
这项研究开发了一个虚拟现实 (VR) 培训系统,以改善公共交通中的平衡. 基于扰动的VR集成平衡训练显示了在动态环境中降落预防的潜力.
科学领域:
- 生物力学 生物力学
- 康复工程 康复工程 康复工程
- 虚拟现实 虚拟现实 虚拟现实
背景情况:
- 在公共交通工具中摔倒会带来很大的风险,特别是对于老年人和平衡障碍者来说.
- 现有的康复方法可能不能充分为动态,现实世界的破坏稳定的条件做好准备.
研究的目的:
- 开发和评估一个新的培训系统,将斯图尔特平台与沉浸式虚拟现实 (VR) 集成在一起.
- 模拟在公共交通中遇到的现实世界的破坏稳定的条件,以进行平衡训练.
- 评估该系统在改善姿势控制方面的有效性.
主要方法:
- 一个斯图尔特平台与沉浸式VR相结合,创造了一个动态的平衡训练环境.
- 实施了基于扰乱的平衡训练 (PBT) 协议,包括感官和机械挑战.
- 用斯图尔特平台的压力中心 (CoP) 度量 (摇摆速度,面积,总功率,平均频率) 来量化姿势稳定性.
主要成果:
- VR & MOVEMENT & NOISY FLOOR条件证明是最具挑战性的,增加了姿势的不稳定性.
- 在基于扰乱的平衡训练后,健康参与者表现出姿势适应.
- 一名患有前体障碍的参与者表现出持续的不稳定性,这表明需要更长时间的康复.
结论:
- 与VR集成的PBT显示出增强对公共交通相关的动态环境中的姿势控制的承诺.
- 该系统的有效性可能因个体感官缺陷而异,需要量身定制的康复方案.
- 需要进一步的研究,以优化对有感官障碍的人的干预措施,并降低跌倒风险.
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