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저출력 레이저의 치료 효과 규명을 위한 근전도 신호의 피로도 해석 연구
김지현,최효훈,윤종인,Kim, Ji-Hyun,Choi, Hyo-Hoon,Youn, Jong-In 대한의용생체공학회 2011 의공학회지 Vol.32 No.4
Skeletal muscle fatigue is defined as a 'any reduction in the maximal capacity to generate force or power output', and is the reduction of oxygen consumption and by-product of metabolism. For the muscle fatigue therapy, low level laser has been introduced that leads the mitochondrial respiratory and attributes the muscle fatigue recovery. This study analyzed the muscle fatigue signals from electromyography(EMG) during low-level laser therapy (LLLT). Healthy subjects performed voluntary elbow flexion-extension excercise and received placebo LLLT and active LLLT using a 830 nm laser diode. Then, EMG were measured for the evaluation of muscle fatigue. The acquired EMG data were analyzed with median frequency and short time fourier transform methods. The results showed that the LLLT had a significant symptomatic relief of muscle fatigue based on the EMG frequency analysis. Therefore, the muscle fatigue analysis with EMG signals can be applied to quantitative evaluation for the monitoring of LLLT effects.
최학남(Xuenan Cui),박은수(Eunsoo Park),최효훈(Hyohoon Choi),김학일(Hakil Kim) 한국정보과학회 2010 한국정보과학회 학술발표논문집 Vol.37 No.1C
본 논문에서는 거리변환 기반의 정밀한 fiducial 마크 정렬 알고리즘을 제안한다. 거리변환은 물체의 중심에 가중치를 가지는 특성이 있는데 이는 AOI 공정에서 에칭, 이동과 같은 다양한 요소들로부터 획득되는 타겟영상에 대하여 강인하게 물체의 중심으로 매칭할 수 있도록 한다. 제안한 방법은 우선 입력 타겟영상에 대하여 이진화를 진행하고, 다음 모델과 타겟영상에 대하여 거리변환을 이용하여 거리특징을 추출하고, 추출된 모델과 타겟영상에 대한 거리특징을 NCC(Normalized Cross Correlation)를 이용하여 매칭한 후, 매칭 스코어에 대하여 Sub-pixel 분석을 진행하여 sub-pixel 레벨의 정확도를 가지도록 한다. 실험결과로부터 제안한 거리특징을 이용한 매칭 알고리즘이 기존의 픽셀 밝기 값을 이용한 매칭보다 강인하고 정확하게 매칭됨을 확인할 수 있었다.
잡음과 회전에 강인한 SIFT 기반 PCB 영상 정렬 알고리즘 개발
김준철(Jun-Chul Kim),최학남(Xue-nan Cui),박은수(Eun-Soo Park),최효훈(Hyo-hoon Choi),김학일(Hakil Kim) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.7
This paper presents an image alignment algorithm for application of AOI (Automatic Optical Inspection) based on SIFT. Since the correspondences result using SIFT descriptor have many wrong points for aligning, this paper modified and classified those points by five measures called the CCFMR (Cascade Classifier for False Matching Reduction) After reduced the false matching, rotation and translation are estimated by point selection method. Experimental results show that the proposed method has fewer fail matching in comparison to commercial software MIL 8.0, and specially, less than twice with the well-controlled environment’s data sets (such as AOI system). The rotation and translation accuracy is robust than MIL in the noise data sets, but the errors are higher than in a rotation variation data sets although that also meaningful result in the practical system. In addition to, the computational time consumed by the proposed method is four times shorter than that by MIL which increases linearly according to noise.