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Upper-Limb Muscle Synergy Features in Human-Robot Interaction with Circle-Drawing Movements
Applied Bionics and Biomechanics ( IF 1.8 ) Pub Date : 2021-09-15 , DOI: 10.1155/2021/8850785
Cheng Wang 1 , Shutao Zhang 2 , Jingyan Hu 2 , Zhejing Huang 3 , Changcheng Shi 2
Affiliation  

The upper-limb rehabilitation robots can be developed as an efficient tool for motor function assessments. Circle-drawing has been used as a specific task for robot-based motor function measurement. The upper-limb movement-related kinematic and kinetic parameters measured by motion and force sensors embedded in the rehabilitation robots have been widely studied. However, the muscle synergies characterized by multiple surface electromyographic (sEMG) signals in upper limbs during human-robot interaction (HRI) with circle-drawing movements are rarely investigated. In this research, the robot-assisted and constrained circle-drawing movements for upper limb were used to increase the consistency of muscle synergy features. Both clockwise and counterclockwise circle-drawing tasks were implemented by all healthy subjects using right hands. The sEMG signals were recorded from six muscles in upper limb, and nonnegative matrix factorization (NMF) analysis was utilized to obtain muscle synergy information. Both synergy pattern and activation coefficient were calculated to represent the spatial and temporal features of muscle synergies, respectively. The results obtained from the experimental study confirmed that high structural similarity of muscle synergies was found among the subjects during HRI with circle-drawing movement by healthy subjects, which indicates healthy people may share a common underlying muscle control mechanism during constrained upper-limb circle-drawing movement. This study indicates the muscle synergy analysis during the HRI with constrained circle-drawing movement could be considered as a task for upper-limb motor function assessment.

中文翻译:

人机交互中的上肢肌肉协同特征与画圆运动

上肢康复机器人可以开发为运动功能评估的有效工具。画圆已被用作基于机器人的运动功能测量的特定任务。由嵌入在康复机器人中的运动和力传感器测量的上肢运动相关运动学和动力学参数已得到广泛研究。然而,在人机交互 (HRI) 与画圆运动过程中,以上肢的多个表面肌电图 (sEMG) 信号为特征的肌肉协同作用很少被研究。在本研究中,机器人辅助和约束的上肢画圈运动被用于增加肌肉协同特征的一致性。顺时针和逆时针画圆任务均由所有健康受试者使用右手完成。从上肢的六块肌肉中记录 sEMG 信号,并利用非负矩阵分解 (NMF) 分析获得肌肉协同信息。计算协同模式和激活系数以分别代表肌肉协同的空间和时间特征。实验研究的结果证实,在HRI与健康受试者画圈运动时,受试者之间的肌肉协同结构具有高度的结构相似性,这表明健康人在受限上肢画圈时可能具有共同的潜在肌肉控制机制——绘画运动。该研究表明,在限制画圈运动的 HRI 期间进行肌肉协同分析可被视为上肢运动功能评估的一项任务。
更新日期:2021-09-15
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