一个基于主观意图下降模型的辅助所需控制策略
Hao Yan1,2, Fangcao Zhang3, Xingao Li1,2
1School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China.
Bioengineering (Basel, Switzerland)
|November 27, 2024
概括
这项研究介绍了中风康复的需要辅助策略,使用主观意图下降模型来优化辅助力. 该方法增强了患者的主动性,并防止在培训期间过度依赖机器人辅助.
科学领域:
- 康复工程 康复工程
- 生物医学工程 生物医学工程
- 神经康复疗法 神经康复疗法
背景情况:
- 卒中康复需要患者的参与,以获得最佳的结果.
- 当前的辅助系统可能会导致患者的依赖.
- 生理刺激对康复疗法的有效性有积极的影响.
研究的目的:
- 开发一种适应性辅助所需的控制策略,用于中风康复.
- 增强患者主动性,减少对辅助设备的依赖.
- 整合主观意图和四肢运动评估,以提供个性化的支持.
主要方法:
- 一个主观的意图下降模型使用表面电肌图 (sEMG) 优化与量子粒子群优化 (QPSO) 和支持矢量机 (SVM).
- 一个肢体运动评估模块,分析相互作用力和位置错误.
- 基于肢体联合运动和主观状态评估的辅助力实时调整.
主要成果:
- 与传统阻抗控制相比,平均辅助力减少了65.66%.
- 与基于力/位置的控制相比,平均辅助力减少了35.2%.
- 在使用意图下降模块识别受试者的疲劳水平时,获得了93.41%的准确性.
结论:
- 拟议的战略有效地增强了患者在康复培训中的主动性.
- 该系统成功地防止过度依赖辅助控制.
- 这种方法提供了一个更个性化,更有效的中风康复体验.
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