Rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton based on sEMG

LI Xingshan; XU Shuai; ZHANG Jiaqi

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Rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton based on sEMG

Design & Manufacture | 更新时间：2026-06-24

- Rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton based on sEMG
- Vol. 45, Issue 6, Pages: 119-124(2026)
- 作者机构：
  
  沈阳理工大学机械工程学院,辽宁,沈阳,110159
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP242;TP212
- Published：2026
- 稿件说明：
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LI Xingshan, XU Shuai, ZHANG Jiaqi. Rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton based on sEMG[J]. 2026, 45(6): 119-124.
DOI：

LI Xingshan, XU Shuai, ZHANG Jiaqi. Rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton based on sEMG[J]. 2026, 45(6): 119-124. DOI：

摘要

针对传统手部外骨骼存在的延迟性与运动范围受限问题，设计了一种基于表面肌电信号（sEMG）控制的刚柔耦合二自由度康复外骨骼，该设计融合sEMG的可靠性、形状记忆合金（SMA）的高功率密度特性，以及二自由度结构的灵活性。首先，分析了sEMG的生成机制，在采集过程中对其进行预处理，并通过特征提取方法获取特征。基于外骨骼的结构组成，构建SMA驱动的数学模型。实验结果表明，外骨骼辅助下掌指关节（MCP）的最大屈曲角度为30.5°，最小伸展角度为4.1°；指间关节（PIP）的最大屈曲角度为40.8°，最小伸展角度为12.5°；手部最大承受力达4.701N。sEMG强度的降低，表明该外骨骼能满足预期运动需求。卷积神经网络（CNN）的手势识别率达到了72.85%，为外骨骼的准确控制提供了有力支持。

Abstract

Aiming at the problems of delay and limited motion range of traditional hand exoskeletons

a rigid-flexible coupled two-degree-of-freedom rehabilitation exoskeleton controlled by surface electromyography(sEMG)is designed.This design integrates the reliability of sEMG

the high power density characteristic of shape memory alloy(SMA)

and the flexibility of the two-degree-of-freedom structure.Firstly

the generation mechanism of sEMG is analyzed.The signal is preprocessed during collection

and features are obtained through feature extraction methods.Based on the exoskeleton’s structural composition

a mathematical model driven by SMA is constructed.Experimental results show that with the exoskeleton’s assistance

the maximum flexion angle of the metacarpophalangeal joint (MCP) is 30.5°

and the minimum extension angle is 4.1°.For the proximal interphalangeal joint (PIP)

the maximum flexion angle is 40.8°

and the minimum extension angle is 12.5°.The hand’s maximum bearing capacity reaches 4.701N.The decrease in sEMG intensity indicates that the exoskeleton can meet the expected motion requirements.The gesture recognition rate of the convolutional neural network(CNN)reaches 72.85%

providing strong support for the exoskeleton’s accurate control.

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