Open AccessControlling hand robot using pattern recognition of finger movement
Author(s) -
Sumantri Kurniawan Risandriya,
Daniel Sutopo Pamungkas
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1450/1/012035
Subject(s) - computer science , electromyography , artificial intelligence , signal (programming language) , robot , movement (music) , artificial neural network , pattern recognition (psychology) , speech recognition , computer vision , motion (physics) , word error rate , physical medicine and rehabilitation , acoustics , medicine , physics , programming language
The system enables to mimic the movement of the subject up to 87.5 percent accuracy. Electromyography (EMG) is one of the methods to control a robot’s hand. This paper discusses the utilization of the signal EMG with a neural network algorithm to activate the fingers of the robot hand. The statistical analysis, which is the root mean square method, is used to train the patterns of the motion of the fingers of the user. Moreover, to sense the user’s EMG signal, Myo armband is used. The results obtained reach 92.68 percent using 0.9 learning rate, 0.00001 error tolerance, one hidden layer with five nodes.