北京生物医学工程

训练轨迹对上肢肌肉协同的影响

The effect of training trajectories on upper limb muscle synergy

作者：何勇施长城左国坤马冶浩刘吉成

单位：上海大学（上海 200444）；中国科学院宁波材料技术与工程研究所，慈溪生物医学工程研究所（浙江宁波 315399)；中国科学院宁波材料技术与工程研究所，先进制造技术研究所（浙江宁波 315201）

关键词：康复机器人；肌肉协同；训练轨迹；非负矩阵算法

分类号：R318.04

出版年·卷·期（页码）：2019·38·5（441-449）

摘要：

目的通过分析康复机器人辅助训练过程中沿不同轨迹运动的上肢肌肉协同特性，探究运动轨迹对上肢肌肉骨骼特性的影响，为康复机器人训练轨迹优化设计提供基础实验数据与指导。方法首先在末端牵引式康复机器人系统中设计3种上肢运动训练轨迹（L1：直线，L2：弧线，L3：半圆），然后采集12名健康志愿者在沿3种训练轨迹上肢运动过程中的的表面肌电信号，并使用非负矩阵分解算法进行肌肉协同特性的获取，对不同轨迹组间肌肉协同结构的相似系数、屈肌占比以及募集模式积分系数进行对比分析，探讨康复机器人不同训练轨迹对上肢肌肉骨骼特性的影响。结果同一训练轨迹中各志愿者的肌肉协同结构具有较高相似性（平均SI>0.81）。各轨迹组的肌肉协同结构中的屈肌占比随运动进程逐渐增加。各轨迹组的肌肉协同募集模式均具有时序特性，前期伸肌起主要作用，后期屈肌起主要作用，中期屈肌占比随轨迹曲率增加而增加。轨迹L1与L2、L2与L3协同结构非常相似（SI >0.90），而L1与L3协同结构较为相似（SI >0.75）。结论康复机器人辅助上肢的训练轨迹对上肢肌肉特性有一定影响，不同训练轨迹带来的肌肉协同结构较为相似，但是运动过程中屈肌群占比及协同贡献度会为了协调动作而发生变化。由此可推测不同训练轨迹对不同肌群的训练强度可能会有所不同。康复机器人训练轨迹设计需根据康复需求进行优化设计。

Objective By analyzing the muscle synergy characteristics of upper limb during rehabilitation robot-assisted training, the influence of the motion trajectories on upper limb musculoskeletal characteristics is explored,which provides the basic experimental data and guidance for the optimal design of the training trajectory of rehabilitation robot. Methods Firstly, three kinds of upper limb training trajectories (L1: straight line, L2: arc, L3: semicircle) were designed in the end-traction rehabilitation robot system. Then the surface electromyogram signals of 12 healthy volunteers during the upper limb movement along three training trajectories were collected, and the muscle synergy characteristics were obtained by non-negative matrix decomposition algorithm. The similarity coefficients, flexor ratio and recruitment mode integral coefficients of muscle synergy structure between different trajectory groups were compared and analyzed, and the influence of different training trajectories of rehabilitation robot on upper limb musculoskeletal system was studied. Results In the same training trajectory, the muscle synergy structure of each volunteer had a high similarity (average SI > 0.81). The ratio of flexors in the synergy structure of each trajectory group increased gradually with the movement process. The synergy recruitment mode of each trajectory group had the characteristics of time series. The extensor played a major role in the early stage, the flexor played a major role in the late stage, and the ratio of flexors increased with increasing of trajectory curvature in the middle stage. The synergy structures of L1 and L2, L2 and L3 were very similar respectively(SI > 0.90), while L1 and L3 were similar (SI > 0.75). Conclusions The rehabilitation robot-assisted upper limb training trajectory has a certain impact on the characteristics of upper limb muscles. Different training trajectories bring about similar muscle synergy structure, but the ratio of flexors and the contribution degree of muscle synergy will change in order to coordinate the movement. It can be inferred that different training trajectories may have different training intensities for different muscle groups. The trajectory design of rehabilitation robot needs to be optimized according to rehabilitation needs.

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