利用表面肌电信号的下肢动态关节力矩预测模型

陈江城; 张小栋; 李睿; 石强勇; 王贺

doi:10.7652/xjtuxb201512005

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利用表面肌电信号的下肢动态关节力矩预测模型

更新时间：2025-07-09

- 利用表面肌电信号的下肢动态关节力矩预测模型
- Prediction Model for Dynamic Joint Torque of Lower Limb with Surface EMG
- 西安交通大学学报 2015年49卷第12期页码：26-33
- 作者机构：
  
  西安交通大学现代设计及转子轴承系统教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2015-03-08。作者简介: 陈江城(1987—),男,博士生;张小栋(通信作者),男,教授,博士生导师。基金项目: 国家高技术研究发展计划资助项目(2015AA042301);国家自然科学基金重大研究计划资助项目(91420301)
- DOI：10.7652/xjtuxb201512005
  中图分类号： TP242
- 网络首发：2015-12-10，
  
  纸质出版：2015
- 稿件说明：
移动端阅览
陈江城, 张小栋, 李睿, 等. 利用表面肌电信号的下肢动态关节力矩预测模型[J]. 西安交通大学学报, 2015,49(12):26-33.

Prediction Model for Dynamic Joint Torque of Lower Limb with Surface EMG[J]. 2015, 49(12): 26-33.
陈江城, 张小栋, 李睿, 等. 利用表面肌电信号的下肢动态关节力矩预测模型[J]. 西安交通大学学报, 2015,49(12):26-33. DOI： 10.7652/xjtuxb201512005.

Prediction Model for Dynamic Joint Torque of Lower Limb with Surface EMG[J]. 2015, 49(12): 26-33. DOI： 10.7652/xjtuxb201512005.

摘要

为实现表面肌电信号的下肢关节力矩动态解码

建立了从表面肌电信号到关节力矩输出的人体下肢运动系统正向生物力学模型。首先

从幅值和频率两个角度建立表面肌电信号到骨骼肌激活程度模型; 其次

根据肌丝滑移理论

构建反映骨骼肌生理结构和微观力学特性的肌肉力模型

同时确定活动肌肉拉力线方向及力作用点位移矢量

将骨骼肌力转换到关节力矩; 最后

以牛顿-欧拉逆动力学方法获得关节力矩作为准确值

给出正向生物力学模型参数动态标定方法。在模型基础上

对4名对象进行随意步态下膝关节屈伸动态力矩预测试验

结果表明:所建模型对步态行走下的膝关节动态关节力矩具有很好的动态跟踪性能

最大绝对误差为(11.0±1.32)N·m

平均残差为(4.43±0.698)N·m

预测值与准确值之间的平均线性相关系数为0.927±0.042

验证了该方法的正确性和有效性; 可为康复训练机器人人机协同过程中的力学交互模式研究提供接口。

Abstract

To achieve the dynamic joint torque decoding from surface electromyography(EMG)

the forward biomechanical model of lower limb motor system

which relates the surface EMG and joint torque

is established. The dynamic surface EMG to skeletal muscle activation model is constructed from the perspective of amplitude and frequency. Then the muscle contraction model reflecting physiological structure and micromechanical properties is constructed according to the sliding-filament theory. The force direction and displacement vector of active muscle are determined and the transformation from muscle force to joint moment is realized. The dynamic calibration for the forward biomechanical model using the exact joint torque value obtained with Newton-Eular method is finally put forward. Following the calibration

the flexion/extension(FE)knee joint torque of four objects under different speed walking is predicted. The results show that the forward biomechanical model can capture the general shape and timing of the joint torque

the maximum absolute error is(11.0±1.32)N·m

the mean residual error is(4.43±0.698)N·m

and the linear relationship between predicted and exact knee FE torque reaches 0.927±0.042. This prediction model provides an interface for the study of force interaction pattern in the process of human-machine cooperation in training.

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Keywords

references

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