基于山型肌肉模型的功能电刺激诱导的指尖预测力控制
概括
功能电刺激 (FES) 精确地控制手指的力量以恢复手的功能. 这项研究使用个性化的Hill和多关节模型准确预测FES驱动的指纹输出,帮助康复.
科学领域:
- 生物医学工程
- 康复科学
- 神经科学
背景情况:
- 功能电刺激 (FES) 对于恢复神经障碍手部运动功能至关重要.
- 现有的FES研究往往缺乏同时多关节力预测和个性化建模.
- 精确的手指输出力控制对于有效的FES应用至关重要.
研究的目的:
- 通过Hill模型和多关节指模型准确预测FES的指出力.
- 根据实际的力量输出来验证个性化的Hill模型.
- 为了实现协调的多指控制.
主要方法:
- 针对个体参与者的个性化Hill模型.
- 希尔模型与多关节手指模型的整合.
- 通过在不同的电流条件下比较预测和测量的力来验证模型的准确性.
主要成果:
- 在最佳条件下达到最大目标力的5.1%的正常化平均平方误差.
- 证明了多个手指的协调控制.
- 在预测FES诱导的手指力时验证了个性化模型的准确性.
结论:
- 拟议的方法可以精确控制手动的FES力.
- 个性化的Hill和多关节模型显著提高了FES的准确性.
- 这种方法对先进的手部康复和辅助机器人有前途.
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