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KMID : 1137820060270050237
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의공학회지
2006 Volume.27 No. 5 p.237 ~ p.244
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Performance Improvement of EMG-Pattern Recognition Using MFCC-HMM-GMM
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Choi Heung-Ho
Kim Jung-Ho
Kwon J.W.
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Abstract
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This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)’s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.
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KEYWORD
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EMG(Electromyogram), MFCC(Mel-Frequency Cepstral Coefficients), HMM(Hidden Markov Models), GMM(Gaussian Mixture Models), pattern recognition
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