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The Virtual Robot Arm Control Method by EMG Pattern Recognition using the Hybrid Neural Network System  

Jung, Kyung-Kwon (동국대학교 전자공학과)
Kim, Joo-Woong (동국대학교 전자공학과)
Eom, Ki-Hwan (동국대학교 전자공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.10, no.10, 2006 , pp. 1779-1785 More about this Journal
Abstract
This paper presents a method of virtual robot arm control by EMG pattern recognition using the proposed hybrid system. The proposed hybrid system is composed of the LVQ and the SOFM, and the SOFM is used for the preprocessing of the LVQ. The SOFM converts the high dimensional EMG signals to 2-dimensional data. The EMG measurement system uses three surface electrodes to acquire the EMG signal from operator. Six hand gestures can be classified sufficiently by the proposed hybrid system. Experimental results are presented that show the effectiveness of the virtual robot arm control by the proposed hybrid system based classifier for the recognition of hand gestures from EMG signal patterns.
Keywords
LVQ; SOFM; EMG; Pattern recognition; Virtual robot arm;
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