MFCC-HMM-GMM을 이용한 근전도(EMG)신호 패턴인식의 성능 개선
Performance Improvement of EMG Pattern Recognition Using MFCC-HMM-GMM
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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 for EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when learning based on the EMG data for each motion.
참고문헌 (14)
- "The EMG-force model of electrically stimulated muscle Dependence on control strategy and predominant fiber composition", moshe solomo 34(w et al), pp.692~703 (1987)
- "Biomedical Digital Signal Processing", pp.1993~, Prentice Hall International Editions
- "A hybrid segmental neural net", hidden Markov model system for continuous speech recognition, 1994., pp.2, 151~152
- "Estimating hidden Markov model parameters so as to maximize speech recognition accuracy", 1(1), pp.77~78 (1993)
- "Probabilistic-neural pattern classifier and muscle force estimation", sandiego, pp.~1993
- "The application of counterpropagation neural networks for EMG pattern classification", rio-dejanerio, pp.~1994
- "Digital Processing of Speech Signals", pp.1978~, Prentice-Hall
- "Fundamentals of Speech Recognition", pp.1993~, Prentice-Hall International
- "Speaker-independent phone recognition using hidden Markov models", signal processing(37), pp.~11
- "Robust speech recognition in additive and channel noise environments using GMM and EM algorithm . IEEE International Conference on Acoustics", 1. (2004)
- "Text-inde-pendent speaker recognition by combining speaker-specific GMM with speaker adapted syllable-based HMM . IEEE International Conference on Acoustics", 1. (2004)
- "From a gaussian mixture model to additive fuzzy systems", 13, pp.303~316 (2005)
- "A new strategy for multifunction myoelectric control IEEE Trans on Biomedical EnGineering", 40.(1. 1993.)
- "The theoretical development of a multichannel time-Series myopeocessor for simultaneous limb function detection and muscle force estimation", 36, pp.~10 (1989)