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A Virtual Robot Arm Control by EMG Pattern Recognition of Fuzzy-SOFM Method  

이정훈 (동국대학교 전자공학과)
정경권 (동국대학교 전자공학과)
이현관 (호남대학교 인터넷프로그램학과)
엄기환 (동국대학교 전자공학과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.40, no.2, 2003 , pp. 9-16 More about this Journal
Abstract
We proposed a method of a virtual robot arm controlled by the EMG pattern recognition using an improved SOFM method. The proposed method is simple in that the EMG signals are used as SOFM's input directly without preprocessing but nevertheless input patterns are reliably classified and then used for fuzzy logic systems to automatically tune the neighborhood and the learning rate. In order to verify the effectiveness of the proposed method, we experimented on EMG pattern recognition of 6 movements from the shoulder, wrist, and elbow. Experimental results show that the proposed SOFM method has 21.7% higher recognition rate than the general SOFM method, the average number of learning iterations has been decreased, and then the virtual robot arm is controlled by EMG pattern recognition.
Keywords
fuzzy; SOFM; pattern recognition; EMG signal; virtual robot arm;
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