Human-Exoskeleton Coupling Dynamics of a Multi-Mode Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

被引:12
|
作者
Xie, Qiaolian [1 ,2 ,3 ]
Meng, Qiaoling [1 ,2 ,3 ]
Zeng, Qingxin [1 ,2 ,3 ]
Fan, Yuanjie [4 ]
Dai, Yue [1 ,2 ,3 ]
Yu, Hongliu [1 ,2 ,3 ]
机构
[1] Univ Shanghai Sci & Technol, Rehabil Engn & Technol Inst, Sch Med Instrument & Food Engn, Shanghai 200093, Peoples R China
[2] Shanghai Engn Res Ctr Assist Devices, Shanghai 200093, Peoples R China
[3] Minist Civil Affairs, Key Lab Neural Funct Informat & Rehabil Engn, Shanghai 200093, Peoples R China
[4] Shanghai Elect Grp Cent Acad, Dept Rehabil Robot Prod, Shanghai 200070, Peoples R China
基金
中国国家自然科学基金;
关键词
Exoskeletons; Training; Robots; Mathematical model; Torque; Dynamics; Stroke (medical condition); Human-exoskeleton coupling dynamics; parameter identification; rehabilitation training; MODEL;
D O I
10.1109/ACCESS.2021.3072781
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The purpose of this study is to establish the human-exoskeleton coupling (HEC) dynamic model of the upper limb exoskeleton, overcome the difficulties of dynamic modeling caused by the differences of individual and disease conditions and the complexity of musculoskeletal system, to achieve early intervention and optimal assistance for stroke patients. This paper proposes a method of HEC dynamics modeling, and analyzes the HEC dynamics in the patient-active training (PAT) and patient-passive training (PPT) mode, and designs a step-by-step dynamic parameter identification method suitable for the PAT and PPT modes. Comparing the HEC torques obtained by the dynamic model with the real torques measured by torque sensors, the root mean square error (RMSE) can be kept within 13% in both PAT and PPT modes. A calibration experiment was intended to further verify the accuracy of dynamic parameter identification. The theoretical torque of the load calculated by the dynamic model, is compared with the difference calculated by parameter identification. The trends and peaks of the two curves are similar, and there are also errors caused by experimental measurements. Furthermore, this paper proposes a prediction model of the patient's height and weight and HEC dynamics parameters in the PPT mode. The RMSE of the elbow and shoulder joints of the prediction model is 9.5% and 13.3%. The proposed HEC dynamic model is helpful to provide different training effects in the PAT and PPT mode and optimal training and assistance for stroke patients.
引用
收藏
页码:61998 / 62007
页数:10
相关论文
共 50 条
  • [1] Human-exoskeleton coupling dynamics in the swing of lower limb
    Yan, Yao
    Chen, Zhenlei
    Huang, Cheng
    Chen, Li
    Guo, Qing
    APPLIED MATHEMATICAL MODELLING, 2022, 104 : 439 - 454
  • [2] Kinematics, Dynamics and Control of an Upper Limb Rehabilitation Exoskeleton
    Wu, Qingcong
    Shao, Ziyan
    MULTISENSOR FUSION AND INTEGRATION IN THE WAKE OF BIG DATA, DEEP LEARNING AND CYBER PHYSICAL SYSTEM, 2018, 501 : 284 - 298
  • [3] Development, Dynamic Modeling, and Multi-Modal Control of a Therapeutic Exoskeleton for Upper Limb Rehabilitation Training
    Wu, Qingcong
    Wu, Hongtao
    SENSORS, 2018, 18 (11)
  • [4] Identification and Analysis of Human-Exoskeleton Coupling Parameters in Lower Extremities
    Huang, Cheng
    Ji, Shuang
    Chen, Zhenlei
    Sun, Tianyi
    Guo, Qing
    Yan, Yao
    IEEE TRANSACTIONS ON HAPTICS, 2024, 17 (04) : 650 - 661
  • [5] A Robust Controller for Upper Limb Rehabilitation Exoskeleton
    Blanco-Ortega, Andres
    Vazquez-Sanchez, Luis
    Adam-Medina, Manuel
    Colin-Ocampo, Jorge
    Abundez-Pliego, Arturo
    Cortes-Garcia, Claudia
    Garcia-Beltran, Carlos Daniel
    APPLIED SCIENCES-BASEL, 2022, 12 (03):
  • [6] Adaptive hybrid-mode assist-as-needed control of upper limb exoskeleton for rehabilitation training
    Guo, Yida
    Tian, Yang
    Wang, Haoping
    Han, Shuaishuai
    MECHATRONICS, 2024, 100
  • [7] Modelling and RBF Control of Low-Limb Swinging Dynamics of a Human-Exoskeleton System
    Peng, Xinyu
    Zhang, Shujun
    Cai, Mengling
    Yan, Yao
    ACTUATORS, 2023, 12 (09)
  • [8] Characterization and Evaluation of Human-Exoskeleton Interaction Dynamics: A Review
    Massardi, Stefano
    Rodriguez-Cianca, David
    Pinto-Fernandez, David
    Moreno, Juan C.
    Lancini, Matteo
    Torricelli, Diego
    SENSORS, 2022, 22 (11)
  • [9] Human-Exoskeleton System Dynamics Identification Using Affordable Sensors
    Mallat, Randa
    Bonnet, Vincent
    Huo, Weiguang
    Karasinski, Patrick
    Amirat, Yacine
    Khalil, Mohamad
    Mohammed, Samer
    2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2018, : 6759 - 6765
  • [10] Mirror Adaptive Impedance Control of Multi-Mode Soft Exoskeleton With Reinforcement Learning
    Xu, Jiajun
    Huang, Kaizhen
    Zhang, Tianyi
    Zhao, Mengcheng
    Ji, Aihong
    Li, Youfu
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 6773 - 6785