TY - GEN
T1 - Controlling Robot Manipulators as Prototype of Prosthetic Arm using Electromyography Signal Based on Embedded System
AU - Maulana, Rizal
AU - Halimah, Hanifa Nur
AU - Setyawan, Gembong Edhi
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/9/13
Y1 - 2021/9/13
N2 - The arm is a part of the upper limb that plays a significant role in daily activities. Unfortunately, some people are less fortunate due to arms limitations. This limitation can be in incomplete arm organs, such as the absence of the forearm caused by amputation or congenital anomalies. A prosthetic arm is one of the most critical assistive technology they require. In this research, we propose a prosthetic arm system that can be controlled based on the movement of the remaining arm part of the body. Since the prosthetic arm is a wearable device, the designed system will be implemented on an embedded system. This system uses input from the acquisition of electrical activity that occurs in the upper arm muscles. The data were acquired using an Electromyography (EMG) sensor. There are five types of arm movement designed that can be classified based on the amplitude value of the EMG signal. The prosthetic arm performs the motion according to the classification results. The proposed system has an accuracy of 87% in the suitability of the robot's arm motion.
AB - The arm is a part of the upper limb that plays a significant role in daily activities. Unfortunately, some people are less fortunate due to arms limitations. This limitation can be in incomplete arm organs, such as the absence of the forearm caused by amputation or congenital anomalies. A prosthetic arm is one of the most critical assistive technology they require. In this research, we propose a prosthetic arm system that can be controlled based on the movement of the remaining arm part of the body. Since the prosthetic arm is a wearable device, the designed system will be implemented on an embedded system. This system uses input from the acquisition of electrical activity that occurs in the upper arm muscles. The data were acquired using an Electromyography (EMG) sensor. There are five types of arm movement designed that can be classified based on the amplitude value of the EMG signal. The prosthetic arm performs the motion according to the classification results. The proposed system has an accuracy of 87% in the suitability of the robot's arm motion.
KW - assistive technology
KW - electromyography
KW - embedded system
KW - prosthetic arm
UR - https://www.scopus.com/pages/publications/85118900453
U2 - 10.1145/3479645.3479697
DO - 10.1145/3479645.3479697
M3 - Conference contribution
AN - SCOPUS:85118900453
T3 - ACM International Conference Proceeding Series
SP - 56
EP - 62
BT - Proceedings of 2021 International Conference on Sustainable Information Engineering and Technology, SIET 2021
PB - Association for Computing Machinery
T2 - 6th International Conference on Sustainable Information Engineering and Technology, SIET 2021
Y2 - 13 September 2021 through 14 September 2021
ER -