TY  - BOOK
AU  - Aida Safwah binti Haji Ali
ED  - Universiti Teknologi Brunei
TI  - An Electromyography Signal Enhancement for Upper Limb Rehabilitation Robot Manipulator System
PY  - 2023///
CY  - Brunei Darussalam
PB  - Universiti Teknologi Brunei
KW  - Thesis
KW  - Universiti Teknologi Brunei
KW  - Electromyography
KW  - Data processing
KW  - Signal processing
KW  - Digital techniques
KW  -  Robotic arms
KW  -  Control systems
N1  - Submitted in fulfillment of the requirements for the degree of Master of Science in Engineering; Abstract
The development of new diagnostic techniques and therapeutic approaches is a continuous process in the medical area. Patients with stroke-related upper limb impairments should engage in rehabilitation activities to speed their recovery and return to normal daily activities. Robots can aid patients in doing actual exercises or training movements utilizing the manipulators or other tools that rehabilitation therapists use, which can help free up therapists' time to care for other patients. Nowadays, technology is becoming more vital in healthcare. It is therefore critically necessary in this area of medicine to build a cooperative robot-assisted upper limb rehabilitation exercise prototype that can generate specialized training programs that the patients may safely complete with the robot.
In this study, the right deltoids, right biceps, and right triceps of nine healthy volunteers were examined for their patterns of EMG signals. For a run of 30 seconds, the participants were instructed to carry out horizontal abductions and adductions as well as elbow flexions and extensions. The results demonstrated that the signals generated by the rehabilitation robot arm were comparable to those generated free-handed, and that there was a significant, if very little, reduction in signal voltage when employing the robot arm.
This demonstrates that these prescribed movement sequence criteria are suitable for upper limb stroke rehabilitation and are established as effective strategies for rehabilitation, and can be improved by trial with patients with upper limb injuries for more accurate results. Future research can focus on evaluating the feasibility and analysis of the practicality of integrating EMG sensor technology into existing rehabilitation programs for post-stroke patients in the future, and the potential benefits of enhanced therapy capacity and optimized exercise customization; Thesis ( Degree of Master of Science in Engineering ); Includes bibliography references
ER  -