Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)

The Institute of Electronics and Information Engineers (대한전자공학회)
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EMG Pattern Recognition based on MFCC-HMM-GMM for Prosthetic Arm Control

의수 제어를 위한 MFCC-HMM-GMM 기반의 근전도(EMG) 신호 패턴 인식

  • Kim, Jung-Ho (Dept of Computer Engineering, Tongmyong University) ;
  • Hong, Joon-Eui (Dept of Computer Engineering, Tongmyong University) ;
  • Lee, Dong-Hoon (Dept of Computer Engineering, Tongmyong University) ;
  • Choi, Heung-Ho (Dept. of Biomedical Engineering, Inje University) ;
  • Kwon, Jang-Woo (Dept of Computer Engineering, Tongmyong University)
  • 김정호 (동명대학교 컴퓨터공학과) ;
  • 홍준의 (동명대학교 컴퓨터공학과) ;
  • 이동훈 (동명대학교 컴퓨터공학과) ;
  • 최흥호 (인제대학교 의용공학과) ;
  • 권장우 (동명대학교 컴퓨터공학과)
  • Published : 2006.06.21
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Abstract

In this paper, we proposed using MFCC coefficients(Mel-Scaled Cepstral Coefficients) and a simple but efficient classifying method. Many other features: IAV, zero crossing, LPCC, $\ldot$ and their derivatives are also tested and compared with MFCC coefficients in order to find the best combination. GMM and HMM (Discrete and Continuous Hidden Markov Model), are studied as well in the hope that the use of continuous distribution and the temporal evolution of this set of features will improve the quality of emotion recognition.

Keywords