Design and Development of a Smart IoT-Based Robotic Solution for Wrist Rehabilitation
Yassine Bouteraa1,2, Ismail Ben Abdallah2, Khaled Alnowaiser1
1Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.
Micromachines
|June 24, 2022
Summary
This study introduces an IoT robot for wrist rehabilitation, using EMG signals and a fuzzy classifier to estimate muscle fatigue and dynamically adjust therapy. This innovative approach personalizes rehabilitation by accounting for patient effort and fatigue during exercises.
Area of Science:
- Robotics
- Biomedical Engineering
- Rehabilitation Technology
Background:
- Wrist rehabilitation often lacks personalized feedback regarding muscle fatigue.
- Existing robotic systems may not dynamically adapt to a patient's changing physical state during therapy.
Purpose of the Study:
- To develop an IoT-based robotic system for wrist rehabilitation.
- To introduce a novel protocol for assessing injured muscle states and dynamic model parameters.
- To integrate electromyography (EMG) signal analysis for real-time muscle fatigue estimation and adaptive control.
Main Methods:
- An IoT-based robot was designed for wrist rehabilitation exercises.
- A new protocol was established to determine subject-specific parameters (axis offset, inertial parameters, passive stiffness, damping).
- Electromyography (EMG) signals were extracted and processed using a fuzzy classifier to estimate muscle fatigue.
- A control architecture was implemented to dynamically update patient torque based on estimated fatigue and robot-generated resistance.
Main Results:
- The system successfully estimated muscle fatigue and updated patient torque during rehabilitation sessions.
- The protocol allowed for the determination of crucial wrist model parameters and interaction torque.
- Initial testing on three subjects demonstrated promising outcomes for the developed robotics-based solution.
Conclusions:
- The proposed IoT-based robotic system and rehabilitation protocol offer a promising approach for personalized wrist therapy.
- Dynamic adjustment of therapy based on EMG-sensed muscle fatigue can enhance rehabilitation effectiveness.
- The integration of robotics and intelligent control systems holds significant potential for improving patient recovery.
