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김윤재,허정,박광석,김성완,Kim, Y.J.,Heo, J.,Park, K.S.,Kim, S. 대한의용생체공학회 2016 의공학회지 Vol.37 No.5
Recent technological advances in sensor fabrication and bio-signal processing enabled non-constraint and non-intrusive measurement of human bio-signals. Especially, non-constraint measurement of ECG makes it available to estimate various human health parameters such as heart rate. Additionally, non-constraint ECG measurement of wheelchair user provides real-time health parameter information for emergency response. For accurate emergency response with low false alarm rate, it is necessary to discriminate quality levels of ECG measured using non-constraint approach. Health parameters acquired from low quality ECG results in inaccurate information. Thus, in this study, a machine learning based approach for three-class classification of ECG quality level is suggested. Three sensors are embedded in the back seat, chest belt, and handle of automatic wheelchair. For the two sensors embedded in back seat and chest belt, capacitively coupled electrodes were used. The accuracy of quality level classification was estimated using Monte Carlo cross validation. The proposed approach demonstrated accuracy of 94.01%, 95.57%, and 96.94% for each channel of three sensors. Furthermore, the implemented algorithm enables classification of user posture by detection of contacted electrodes. The accuracy for posture estimation was 94.57%. The proposed algorithm will contribute to non-constraint and robust estimation of health parameter of wheelchair users.
로봇 팔의 뇌 신호로부터 유도된 3D 좌표 추적을 위한 Guidance Law 적용에 관한 연구
김윤재,박성우,김원식,염홍기,서한길,이용우,방문석,정천기,오병모,김준식,김유단,김성완,Kim, Y.J.,Park, S.W.,Kim, W.S.,Yeom, H.G.,Seo, H.G.,Lee, Y.W.,Bang, M.S.,Chung, C.K.,Oh, B.M.,Kim, J.S.,Kim, Y.,Kim, S. 대한의용생체공학회 2014 의공학회지 Vol.35 No.3
It is being tried to control robot arm using brain signal in the field of brain-machine interface (BMI). This study is focused on applying guidance laws for efficient robot arm control using 3D coordinates obtained from Magnetoencephalography (MEG) signal which represents movement of upper limb. The 3D coordinates obtained from brain signal is inappropriate to be used directly because of the spatial difference between human upper limb and robot arm's end-effector. The spatial difference makes the robot arm to be controlled from a third-person point of view with assist of visual feedback. To resolve this inconvenience, guidance laws which are frequently used for tactical ballistic missile are applied. It could be applied for the users to control robot arm from a first-person point of view which is expected to be more comfortable. The algorithm which enables robot arm to trace MEG signal is provided in this study. The algorithm is simulated and applied to 6-DOF robot arm for verification. The result was satisfactory and demonstrated a possibility in decreasing the training period and increasing the rate of success for certain tasks such as gripping object.
Nano-indentation 실험과 유한요소 해석을 연계한 재료의 탄소성 물성 평가법 개발
김윤재(Y.J Kim),송태광(T.K Song),박준협(J-H Park),한준희(J-H Hahn) 한국정밀공학회 2006 한국정밀공학회 학술발표대회 논문집 Vol.2006 No.5월
Determination of elastic properties of nano-scale materials using nano-indentation tests is well established, but that of plastic properties is not yet clear. This paper presents a method to extract plastic properties from nano-indentation test, together with results from detailed elastic-plastic FE analysis. It shows that the plastic properties determined from this method are not unique, in the sense that a number of different plastic properties can give the same load-displacement response from nano-indentation test. Possible ways to overcome such problems are discussed.
원전 매설 HDPE 배관의 응력에 대한 해석 변수 영향 고찰
김종성(J.S. Kim),김윤재(Y.J. Kim),이승건(S.G. Lee),박흥배(H.B. Park) 대한기계학회 2011 대한기계학회 춘추학술대회 Vol.2011 No.10
Recently, there has been trend to use HDPE material with buried piping in nuclear power plants. ASME B&PV Code, Code Case N-755, which is technical basis including design requirements for the nuclear safety class 3 buried HDPE piping, presents thickness calculation equation based on thin-walled piping equation, and doesnt consider thickness-directional temperature gradient and nonlinearity of Youngs modulus. HDPE piping is made of thick-walled piping because of low mechanical strength relative to steel, can have high temperature gradients along thickness due to low thermal condictivity, and the Youngs modulus of HDPE may have nonlinearity for strain. In this study, effect of analysis variables such as the thick-wall thickness, the thickness directional thermal gradient, and the nonlinearity of elastic modulus on stresses for the buried HDPE piping was investigated via finite element analysis.