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A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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使用基于EMG的目标功能优化可穿戴设备参数的人在循环中的优化.

María Alejandra Díaz1,2, Sander De Bock2, Philipp Beckerle3,4

  • 1BruBotics, Vrije Universiteit Brussel, Brussels, 1050, Belgium.

Wearable technologies
|January 15, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种基于电肌图 (EMG) 的新方法,用于估计行走期间的能量成本 (EC). 这种新的方法优化了可穿戴机器人辅助,以改善用户体验,而不需要呼吸测量.

关键词:
人与机器人的交互人类在循环中的优化优化优化的优化优化优化.性能增强 性能增强是一种增强.

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科学领域:

  • 生物力学 生物力学
  • 机器人技术 机器人技术 机器人技术
  • 人与计算机的交互

背景情况:

  • 可穿戴机器人旨在通过最大限度地降低能源成本 (EC) 来提高用户的运动和体验.
  • 测量EC通常需要间接方法,如呼吸气体分析,这是具有挑战性的.
  • 优化外骨架辅助的现有方法通常依赖于难以获得的生理测量.

研究的目的:

  • 引入和验证一种基于电肌学 (EMG) 的新型客观功能,用于估计行走期间的能量消耗.
  • 为了证明基于EMG的目标函数与测量EC的相似性.
  • 优化可穿戴机器人辅助使用这个新的目标功能,以改善人机交互.

主要方法:

  • 开发了一个客观功能,结合EMG强度和肌肉协同作用.
  • 通过将其与步行时测量的EC进行比较,在线验证了目标功能.
  • 利用在线贝叶斯优化算法来最小化基于EMG的目标函数,优化步行步骤频率.

主要成果:

  • 提出的基于EMG的目标函数显示与测量EC有很强的相关性.
  • 使用新的目标函数进行优化,与梯度下降相比,需要更少的代和更短的融合时间.
  • 算法汇聚到接近用户首选频率的最佳步骤频率,有助于EC减速.

结论:

  • 基于EMG的新型目标函数提供了可靠和一致的能源支出估计.
  • 这种方法为优化可穿戴机器人的呼吸气体分析提供了切实可行的替代方案.
  • 这种方法有可能增强下肢外骨架的辅助,改善用户性能和人机交互.