一种基于离散EMG信号的人类关节相互作用扭矩的识别方法
Liangchuang Liao1,2, Ding Yan2,3, Guoan Zhang4
1School of Electronic Science and Engineering, Southeast University, Nanjin, Jiangsu, China.
Frontiers in bioengineering and biotechnology
|May 14, 2025
概括
这项研究引入了一种使用电肌图 (EMG) 信号的新方法,以准确估计人类互动关节扭矩. 这种进步有助于通过理解肌肉活动和关节运动关系来开发更具响应性的下肢外骨架控制系统.
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:
- 交互式关节扭矩对于外骨运动控制中的意图识别至关重要.
- 联合输出扭矩的实时监控为自适应控制提供了对人类运动意图的洞察力.
研究的目的:
- 提出一种方法,利用离散电肌图 (EMG) 信号提取人类互动关节扭矩.
- 为了建立人体肌肉活动和互动关节扭矩之间的数值关系.
主要方法:
- 获取人类的EMG信号.
- 使用离散预测方法,在连续范围内对人类关节运动进行分离化.
- 将离散学习结果转换为连续形式,以建立肌肉运动和交互式关节扭矩之间的关系.
主要成果:
- 开发的识别方法在各种人类运动状态中表现出高精度.
- 实验结果显示平均平方误差为0.1502,平均确定系数为0.8616,平均相关系数为0.9365.
结论:
- 已经建立了基于EMG获取的人体关节交互扭矩的离散预测技术.
- 这项技术加深了对肌肉活动和关节运动之间的关系的理解.
- 它提供了一种可行的方法来提取人类关节扭矩,用于像下肢外骨架这样的应用.
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