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안면근육 표면근전도 신호기반 근육 조합 최적화를 통한 단모음인식
이병현(Byeong-Hyeon Lee),류재환(Jae-Hwan Ryu),이미란(Mi-Ran Lee),김덕환(Deok-Hwan Kim) 대한전자공학회 2016 전자공학회논문지 Vol.53 No.3
본 논문에서는 안면근육 표면근전도를 기반으로 근육 조합 최적화를 통한 한국어 단모음 인식 방법을 제안한다. 표면근전도신호는 한국어 단모음 발음에 따라 서로 다른 패턴과 근육 활성도를 보였다. 이전 연구에서 높은 인식 정확도를 보였던 RMS, VAR, MMAV1, MMAV2와 Cepstral Coefficients를 특징 추출 알고리즘으로 사용하였으며, QDA(Quadratic Discriminant Analysis)와 HMM(Hidden Markov Model)으로 한국어 단모음을 분류하였다. 트레이닝 단계에서 입력 받은 데이터로 근육조합을 최적화하고, 최적화 결과를 인식단계에 적용한다. 이때, 새로운 근전도 신호를 입력받고 한국어 단모음을 최종 인식한다. 실험결과 제안한 방법의 인식 정확도가 QDA에서 평균 85.7%, HMM에서 평균 75.1%를 보였다. In this paper, we propose Korean monophthong recognition method optimizing muscle mixing based on facial surface EMG signals. We observed that EMG signal patterns and muscle activity may vary according to Korean monophthong pronunciation. We use RMS, VAR, MMAV1, MMAV2 which were shown high recognition accuracy in previous study and Cepstral Coefficients as feature extraction algorithm. And we classify Korean monophthong by QDA(Quadratic Discriminant Analysis) and HMM(Hidden Markov Model). Muscle mixing optimized using input data in training phase, optimized result is applied in recognition phase. Then New data are input, finally Korean monophthong are recognized. Experimental results show that the average recognition accuracy is 85.7% in QDA, 75.1% in HMM.
안면근육 표면근전도 신호기반 특징 및 근육 선별을 통한 단모음인식
이병현(Byeong-Hyeon Lee),류재환(Jaehwan Ryu),이미란(Miran Lee),김상호(Sangho Kim),Md Zia Uddin,김덕환(Deok-Hwan Kim) 대한전자공학회 2015 대한전자공학회 학술대회 Vol.2015 No.6
In this paper, we propose monophthong recognition method using feature and muscle selection based on facial surface EMG signals. We observed that EMG signal patterns may vary according to Korean monophthong pronunciation. The proposed method can recognize Korean monophthong and improve recognition accuracy by selecting muscle and feature rather than by using all of them. Experimental results show that the recognition accuracy of the proposed method using best muscle and best, second features set is better than that using all of muscles and features. The improved average accuracies are 29.13% in kNN, 34.52% in LDA.
구상흑연주철의 저주기 피로수명에 미치는 흑연입자수의 영향
김민건(Min Gun Kim),이병현(Byeong Hyeon Lee) 대한금속재료학회 ( 구 대한금속학회 ) 2002 대한금속·재료학회지 Vol.40 No.9
The behavior of crack nucleation and propagation during low cycle fatigue of ductile the cast irons with different nodule counts and similar nodule size have been compared. In spite of similar nodule size, the fatigue life of ductile cast iron with lower nodule count was longer than that with higher one. This fact shows that not only the nodule size but also the nodule count is the factor governing the fatigue life. Meanwhile, the crack nucleation density of the former was notably increased in the early stage of stress cycling, but the increasing rate was diminished greatly in the middle one. Therefore, difference in fatigue life of these specimens could not be explained with the crack nucleation behaviors only. The difference in fatigue life of these specimens can be explained by the easiness of crack coalescence which depends upon the nodule count. Consequently, the effect of the nodule count on the fatigue life was significant because of the importance of crack coalescence and propagation.
저사이클 피로수명에 영향을 미치는 구상흑연주철의 흑연입자수의 영향
김민건(Kim Min Gun),이병현(Lee Byeong Hyeon),유병호(Yoo Byung Ho) 강원대학교 산업기술연구소 2000 産業技術硏究 Vol.20 No.1
Low cycle fatigue life of spheroidal graphite cast iron is determined by the morphological parameters of internal graphite. The aim of this study is to clarify the effect of the number of nodular grain of spheroidal graphite cast iron on low cycle fatigue life. Two specimens that have identical average nodular grain size by changing nodular grain volume fraction and different number of nodular grain count was tested. In this paper, the parameter governing fatigue life through fatigue test, the number of nodular grain seriously affect fatigue life and nodular grain size is no longer governing parameter of it.