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Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes
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Human-robot coupling dynamic modeling and analysis for upper limb rehabilitation robots.

Qiaolian Xie1,2,3, Qiaoling Meng1,2,3, Yue Dai1,2,3

  • 1Rehabilitation Engineering and Technology Institute, University of Shanghai for Science and Technology, Shanghai, China.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
|January 2, 2021
PubMed
Summary

Accurate human-robot coupling (HRC) dynamics modeling improves control for upper limb rehabilitation robots. This study demonstrates HRC torque is more precise than robot torque for enhanced rehabilitation robot performance.

Keywords:
Human-robot coupling (HRC) dynamicsdynamic modelparameter identificationrehabilitation robotics

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Area of Science:

  • Robotics
  • Rehabilitation Engineering
  • Biomechanics

Background:

  • Upper limb rehabilitation robots are crucial for stroke recovery.
  • Human-robot coupling (HRC) dynamics significantly impact rehabilitation robot control and human-robot interaction.

Purpose of the Study:

  • To develop and analyze HRC dynamics modeling for precise control of upper limb rehabilitation robots.
  • To enhance dynamic control accuracy in robotic-assisted rehabilitation.

Main Methods:

  • Analyzed force interactions between human arm and robot to derive HRC torque.
  • Utilized Lagrangian equations and step-by-step parameter identification for a 2-DOF robot (FLEXO-Arm).
  • Calculated HRC torque and robot torque using identified dynamic parameters.

Main Results:

  • Parameter identification yielded HRC and robot torques with approximately 10% root mean square (RMS) error.
  • HRC torque demonstrated higher accuracy compared to robot torque when validated against sensor measurements.
  • The error in robot torque was over twice that of the HRC torque.

Conclusions:

  • The developed HRC dynamics modeling enables more accurate dynamic control of upper limb rehabilitation robots.
  • This advancement can lead to improved effectiveness in stroke rehabilitation through enhanced robot-human interaction.