Robotic-assisted systems have been gaining significant traction in supporting rehabilitation tasks, enabling patients to manipulate objects by using a robotic arm controlled by the means of biological signals. In this regard, electromyography (EMG) signals are key for detecting the patient’s intention of motion, that can be replicated by the robotic arm with higher accuracy and precision. In this paper, we present an integrated EMG-driven robotic system capable of performing manipulation tasks by understanding 3 hand gestures associated with certain pick and place commands. Comprehensive experimental tests were conducted to demonstrate that the proposed system can decode EMG-based commands with an accuracy \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$93\%$$\end{document}, undergoing precise robotic-assisted object manipulation.
EMG Driven Robotic-Aided Arm Rehabilitation
Mechan. Machine Science
International Conference on Robotics in Alpe-Adria Danube Region ; 2022 ; Klagenfurt, Austria June 08, 2022 - June 10, 2022
2022-04-23
8 pages
Article/Chapter (Book)
Electronic Resource
English
EMG Driven Robotic-Aided Arm Rehabilitation
TIBKAT | 2022
|Robotic-Assisted Rehabilitation
Springer Verlag | 2021
|A Robotic Rehabilitation Arm Driven by Somatosensory Brain-Computer Interface
BASE | 2014
|A Robotic Rehabilitation Arm Driven by Somatosensory Brain-Computer Interface
BASE | 2014
|Development of an active cable-driven, force-controlled robotic system for walking rehabilitation
BASE | 2021
|