基于哈密尔顿端口系统和疲劳消耗端口补偿的康复机器人控制研究
Jingjing Li1, Zhen Chen1,2, Jian Li1
1School of Automation, Beijing Institute of Technology, Beijing, China.
Frontiers in bioengineering and biotechnology
|June 9, 2025
概括
本研究介绍了对上肢康复机器人的疲劳适应控制策略. 对于中风患者来说,这种新的方法可以减少45%的肌肉疲劳,并增加40%的训练时间.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 神经康复疗法 神经康复疗法
- 生物医学工程 生物医学工程
背景情况:
- 上肢康复机器人有助于中风恢复,但由于肌肉疲劳而导致面部控制不稳定.
- 积极训练模式中的肌肉疲劳对人机交互构成风险,并限制了康复的有效性.
研究的目的:
- 为上肢康复机器人开发一种新的,适应疲劳的控制策略.
- 提高机器人康复培训的安全性,有效性和生理适应性.
主要方法:
- 通过动态肌肉疲劳模型实施了哈密尔顿港式控制策略.
- 使用实时表面电肌图 (sEMG) 来评估疲劳并调整减缓参数.
- 采用分层的控制架构,采用外部循环入口和内部循环能量塑造.
主要成果:
- 理论分析证实了闭环被动性和系统稳定性.
- 实验结果显示,肌肉疲劳累积减少了45%.
- 与固定减噪控制相比,训练时间增加了40%.
结论:
- 适应疲劳的控制框架提高了机器人康复的安全性和有效性.
- 将实时sEMG反与Port-Hamiltonian建模集成,可以实现个性化康复.
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