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实时步行事件检测与自适应频率振荡器从一个单头安装IMU的实时步行事件检测.

Matej Tomc1,2, Zlatko Matjačić1,2

  • 1University Rehabilitation Institute Republic of Slovenia Soča, Linhartova 51, 1000 Ljubljana, Slovenia.

Sensors (Basel, Switzerland)
|July 8, 2023
PubMed
概括

本研究介绍了一种适应频率振荡器 (AFO) 算法,用于使用单个头戴式惯性测量单元 (IMU) 实时检测步行事件. 对于健康的受试者来说,AFO方法显示了准确的步行阶段估计,特别有利于虚拟现实应用.

关键词:
适应性振荡器 适应性振荡器步态事件检测 步态事件检测惯性测量单位是惯性测量单位.虚拟现实 虚拟现实 虚拟现实 虚拟现实

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科学领域:

  • 生物力学 生物力学
  • 可穿戴技术可穿戴技术
  • 康复工程 康复工程 康复工程

背景情况:

  • 准确的实时步行事件检测对于推进步行康复至关重要,特别是机器人和虚拟现实 (VR).
  • 价格实惠的可穿戴惯性测量单元 (IMU) 已经启用了新的步态分析方法.
  • 传统的步态事件检测算法有其局限性.

研究的目的:

  • 突出适应频率振荡器 (AFO) 对于步态事件检测的优点.
  • 实施和验证基于AFO的实时算法,使用单个头部安装IMU进行步行阶段估计.
  • 评估该方法在VR应用中的实用性.

主要方法:

  • 开发了一个基于自适应频率振荡器 (AFOs) 的实时步行阶段估计算法.
  • 使用单个头部上的惯性测量单元 (IMU) 来获取数据.
  • 在不同步行速度的健康受试者上验证了算法.

主要成果:

  • 基于AFO的步行事件检测在两个不同的步行速度上是准确的.
  • 该方法在对称的步态模式上证明了可靠性.
  • 该算法的性能对于不对称的步态模式是不可靠的.

结论:

  • 基于AFO的方法为实时步行事件检测提供了准确和高效的方法.
  • 这种技术对于集成到虚拟现实 (VR) 系统尤其有前途,因为常用的是头部装载的IMU.
  • 可能需要进一步的研究来解决不对称的步态模式的可靠性.