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Performance Improvement of EMG-Pattern Recognition Using MFCC-HMM-GMM

MFCC-HMM-GMM을 이용한 근전도(EMG)신호 패턴인식의 성능 개선

  • Choi, Heung-Ho (Dept. of Biomedical Engineering, College of Bioscience Engineering, Inje University) ;
  • Kim, Jung-Ho (Dept. of Computer Engineering, College of IT, Tongmyong University) ;
  • Kwon, Jang-Woo (Dept. of Computer Engineering, College of IT, Tongmyong University)
  • 최흥호 (인제대학교 의용공학과 의용초음파 연구실팀) ;
  • 김정호 (동명대학교 컴퓨터공학과 인공지능연구실) ;
  • 권장우 (동명대학교 컴퓨터공학과 인공지능연구실)
  • Published : 2006.10.31

Abstract

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.

Keywords

References

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