渐进的无人监督控制肌电上肢
Andrea Gigli1,2, Arjan Gijsberts3, Markus Nowak1
1Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Wessling, Germany.
Journal of neural engineering
|October 26, 2023
概括
这项研究引入了一种渐进式无监督肌肉控制 (PUM) 系统,允许用户自主学习假肢控制. PUM适应用户的技能,并支持开发用于肌电假肢的新运动功能.
科学领域:
- 生物医学工程 生物医学工程
- 康复机器人 康复机器人
- 人与计算机的交互
背景情况:
- 假肢的无监督肌肉控制方法避免了复杂的训练数据,但往往预先定义了功能号码.
- 现有的方法限制了用户,因为它们不能适应不断发展的运动技能或新功能发现.
- 这种差距阻碍了肌电假肢使用者的自然适应和技能发展.
研究的目的:
- 引入和评估一个渐进的无监督肌肉控制 (PUM) 范式.
- 为了使用户和对照模型能够协同适应地识别用于假肢控制的肌肉协同作用.
- 允许用户随着他们的技能发展而逐步学习新的假肢功能.
主要方法:
- 开发了PUM范式,用于肌肉协同作用和假肢功能的协同适应性学习.
- 用户从一个功能开始,可以在掌握后要求更多.
- 通过虚拟的手和手腕进行了一项多会话用户研究,将PUM与非渐进的基线进行比较.
- 包括上肢差异和非残疾对照的参与者.
主要成果:
- 在两组参与者中,PUM促进了对3-4个神经控制功能的自主学习.
- 有肢体差异的参与者表现出相似的成功率,但在技能内化和运动质量方面面临挑战.
- 使用PUM的表现与非残疾参与者的非渐进基线相当.
- 现有的和新发现的肌肉协同作用都被用于控制.
结论:
- PUM范式支持自主学习和适应用户的运动技能.
- 它适应了各种先前存在的运动技能,并促进了随着时间的推移发展新的技能.
- PUM提供了灵活的肌电控制方法,增强了用户的独立性和假肢功能.
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