Implementation of Exoskeleton Robots for Upper Limb Rehabilitation Based on Indonesian Anthropometry

An exoskeleton robot or robot exoskeleton can be called is an elec Exoskeleton robot or robot exoskeleton can be called is an electromechanical device. In this case, the robot is used as a rehabilitation aid. Assistive devices are needed in the rehabilitation process, so that patients can practice a...

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Bibliographic Details
Published in2022 2nd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA) pp. 139 - 143
Main Authors Wicaksono, Gabriel Aryo, Rosa, Muhammad Ridho, Barri, Muhammad Hablul
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.12.2022
Subjects
2 DOF
and PID
Anthropometry
Arms
Electromechanical devices
electromechanics
exoskeleton
Exoskeletons
inverse kinematics
Mouth
Robot sensing systems
servo
stepper
Torque
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Summary:An exoskeleton robot or robot exoskeleton can be called is an elec Exoskeleton robot or robot exoskeleton can be called is an electromechanical device. In this case, the robot is used as a rehabilitation aid. Assistive devices are needed in the rehabilitation process, so that patients can practice at home independently. Exoskeleton robots can be used as a tool for rehabilitation patients to carry out consistent rehabilitation and get the desired results. In this study, the developed exoskeleton robot aims to rehabilitate the upper limbs or upper limbs of post-stroke patients especially for Indonesian patient. This device can move the arm because it has 2 degrees of freedom or 2 DOF (degree of freedom). This device is placed on a chair, so that patients carry out rehabilitation in a relaxed. The results showed that the minimum torque calculation to determine the motor torque was appropriate. The actuators used are a stepper motor on theta 1 and a servo motor on theta 2. The MPU6050 angle sensor is also used as feedback for theta 1. The accuracy of the angle sensor reaches 99%.This is indicated by testing robots that are given orders to help make repeated feeding motions. The overall test shows that the accuracy of the robot in carrying out motions with a load of 83.33%.
DOI:10.1109/ICICyTA57421.2022.10037898