期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2019
卷号：17
期号：1
页码：537-548
DOI：10.12928/telkomnika.v17i1.11600
出版社：Universitas Ahmad Dahlan
摘要：In the developing countries, the need for prosthetic hands is increasing. In general, transradial
amputee patients use prosthetic hands that are passive like a body-powered prosthesis. This research
proposes a low-cost myoelectric prosthetic hand based on 3D printing technology. Hand and finger size
were designed based on the average size of human hands in Indonesia. The proposed myoelectric hand
employs linear actuator combined with the tendon-spring mechanism. Myoelectric hand was developed
with five modes of grip pattern to perform various objects grasping in activity of daily living. Control strategy
had been developed for controlling the motion of flexion and extension on the hand and saving the energy
consumed by the actuators. The control strategy was developed under MATLAB/Simulink environment and
embedded to Arduino Nano V3 using Simulink Support Package for Arduino Hardware. Surface
electromyography (EMG) sensor was used in this research for reading the muscle activity of the
user/wearer. The proposed myoelectric hand had been tested in object grasping test and was
implemented on a study participant with transradial amputee.
其他摘要：In the developing countries, the need for prosthetic hands is increasing. In general, transradial amputee patients use prosthetic hands that are passive like a body-powered prosthesis. This research proposes a low-cost myoelectric prosthetic hand based on 3D printing technology. Hand and finger size were designed based on the average size of human hands in Indonesia. The proposed myoelectric hand employs linear actuator combined with the tendon-spring mechanism. Myoelectric hand was developed with five modes of grip pattern to perform various object grasping in activity of daily living. Control strategy had been developed for controlling the motion of flexion and extension on the hand and saving the energy consumed by the actuators. The control strategy was developed under MATLAB/Simulink environment and embedded to Arduino Nano V3 using Simulink Support Package for Arduino Hardware. Surface electromyography (EMG) sensor was used in this research for reading the muscle activity of the user/wearer. The proposed myoelectric hand had been tested in object grasping test and was implemented on a study participant with transradial amputee.
