Articles | Volume 13, issue 2
https://doi.org/10.5194/ms-13-675-2022
https://doi.org/10.5194/ms-13-675-2022
Research article
 | 
03 Aug 2022
Research article |  | 03 Aug 2022

Electromyogram-based motion compensation control for the upper limb rehabilitation robot in active training

Qiaoling Meng, Yiming Yue, Sujiao Li, and Hongliu Yu

Related authors

A reconfigurable seven-link multi-mode external-fixation system for improving emergency limb fracture stabilization efficiency
Cuizhi Fei, Zongqi Jiao, Qiaoling Meng, Bangke Zhang, and Xuhua Lu
Mech. Sci., 17, 453–467, https://doi.org/10.5194/ms-17-453-2026,https://doi.org/10.5194/ms-17-453-2026, 2026
Short summary
Design and validation of a programmable dual-tunnel soft pneumatic origami actuator with a large maximum shrinkage rate for reciprocating motion
Rongna Xu, Qiaoling Meng, Qiaolian Xie, Yuxin Zheng, Cuizhi Fei, Vincenzo Parenti Castelli, and Hongliu Yu
Mech. Sci., 16, 61–73, https://doi.org/10.5194/ms-16-61-2025,https://doi.org/10.5194/ms-16-61-2025, 2025
Short summary
Design of a soft bionic elbow exoskeleton based on shape memory alloy spring actuators
Qiaolian Xie, Qiaoling Meng, Wenwei Yu, Rongna Xu, Zhiyu Wu, Xiaoming Wang, and Hongliu Yu
Mech. Sci., 14, 159–170, https://doi.org/10.5194/ms-14-159-2023,https://doi.org/10.5194/ms-14-159-2023, 2023
Short summary
Bionic design and analysis of a multi-posture wheelchair
Qiaoling Meng, Mingpeng Jiang, Zongqi Jiao, and Hongliu Yu
Mech. Sci., 13, 1–13, https://doi.org/10.5194/ms-13-1-2022,https://doi.org/10.5194/ms-13-1-2022, 2022
Short summary
An innovative equivalent kinematic model of the human upper limb to improve the trajectory planning of exoskeleton rehabilitation robots
Qiaolian Xie, Qiaoling Meng, Qingxin Zeng, Hongliu Yu, and Zhijia Shen
Mech. Sci., 12, 661–675, https://doi.org/10.5194/ms-12-661-2021,https://doi.org/10.5194/ms-12-661-2021, 2021
Short summary

Cited articles

Bai, J., Song, A., Wang, T., and Li, H.: A novel backstepping adaptive impedance control for an upper limb rehabilitation robot, Comput. Electr. Eng., 80, 106465, https://doi.org/10.1016/j.compeleceng.2019.106465, 2019. 
Bertani, R., Melegari, C., De Cola, M. C., Bramanti, A., Bramanti, P., and Calabrò, R. S.: Effects of robot-assisted upper limb rehabilitation in stroke patients: a systematic review with meta-analysis, Neurol. Sci., 38, 1561–1569, https://doi.org/10.1007/s10072-017-2995-5, 2017. 
Brahmi, B., Saad, M., Luna, C. O., Archambault, P. S., and Rahman, M. H.: Passive and active rehabilitation control of human upper-limb exoskeleton robot with dynamic uncertainties, Robotica, 36, 1757–1779, https://doi.org/10.1017/S0263574718000723, 2018. 
Büsching, I., Sehle, A., Stürner, J., and Liepert, J.: Using an upper extremity exoskeleton for semi-autonomous exercise during inpatient neurological rehabilitation-a pilot study, J. Neuroeng. Rehabil., 15, 1–7, https://doi.org/10.1186/s12984-018-0415-6, 2018. 
Cao, W., Zhang, F., Yu, H., Hu, B., and Meng, Q.: Preliminary research of a novel center-driven robot for upper extremity rehabilitation, Technol. Health Care., 26, 409–420, https://doi.org/10.3233/Thc-171060, 2018. 
Download
Short summary
This paper proposes a novel EMG-based motion compensation controller in active training control to improve patients’ active participation. After proposing an upper limb rehabilitation robot and doing the path plan, the EMG compensation experiments and the active training control experiment are done to prove that the method can control the robot in providing auxiliary force according to patients’ motion intents. The robot can guide the patients in implementing reference tasks in active training.
Share