• 한국정밀공학회지
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• 제31권8호
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• pp.697-703
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• 2014

This paper is study of solving vibration problem occurred in moving hand of wafer transfer robot in semiconductor manufacturing line. Long settling time for decreasing vibration makes low production rate, and moreover the excessive vibration of hand sometimes breaks the wafer in a cassette. The ways of reducing the moving speed and changing the type of motion profile did not help for lessening vibration. Therefore, we analyzed the mechanical property of the hand such as natural frequency, and frequency component of the motion profile currently used in the manufacturing line. In several conditions of motion profile, we found the best condition of which the frequency component in near of natural frequency of the hand is minimal and this induced small vibration in moving hand. The results were verified theoretically and experimentally using frequency analysis.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.309-318
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• 2001

In this paper, we describe methods that analyze a human gesture. A human interface(HI) system for analyzing gesture extracts the head and hand regions after taking image sequence of and operators continuous behavior using CCD cameras. As gestures are accomplished with operators head and hands motion, we extract the head and hand regions to analyze gestures and calculate geometrical information of extracted skin regions. The analysis of head motion is possible by obtaining the face direction. We assume that head is ellipsoid with 3D coordinates to locate the face features likes eyes, nose and mouth on its surface. If was know the center of feature points, the angle of the center in the ellipsoid is the direction of the face. The hand region obtained from preprocessing is able to include hands as well as arms. For extracting only the hand region from preprocessing, we should find the wrist line to divide the hand and arm regions. After distinguishing the hand region by the wrist line, we model the hand region as an ellipse for the analysis of hand data. Also, the finger part is represented as a long and narrow shape. We extract hand information such as size, position, and shape.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1203-1210
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• 2007

Robots have begun to perform various tasks on replacing the human in the daily life such as cleaning, entertainments etc. In order to accomplish the effective performance of intricate and precise tasks, robot hand must have special capabilities, such as decision making in given condition, autonomy in unknown situation and stable manipulation of object. In this study, we addresses the development of a 3-fingered humanoid robot hand system. We execute static analysis, vibration analysis and flexible dynamics to reserve stability at the design. Grasp motion of the finger uses a linear actuator and gears. Motion can be distinguished into four parts depending on the grasping thin paper, sphere, and column. In each motion, we compare the displacement of the case to be rigid with the case to be flexible. As a result, manufactured and feasibility of the robot hand is validated through preliminary experiments.

• 한국운동역학회지
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• 제28권2호
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• pp.109-117
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• 2018

Objective: To compare head and hand movement patterns during squash forehand motions between experts and less-skilled squash players. Method: Four experts and four less-skilled squash players participated in this study. They performed squash forehand swings and a VICON motion analysis system was used to obtain displacement and velocity data of the head and right hand during the movement. Mann-Whitney U-tests were performed to compare head and hand range of motion and peak velocity, and cross-correlation was performed to analyze the head-hand coordination pattern between groups in three movement directions. Results: In terms of head and hand kinematic data, experts had greater head range of motion during down swings than less-skilled squash players. Experts seemed to reach peak hand velocity at impact by reaching peak head velocity followed by hand peak velocity within a given temporal sequence. In terms of head-hand coordination patterns, both groups revealed high positive correlations in the medial-lateral direction, indicating a dominant allocentric coordination pattern. However, experts had uncoupled coordination patterns in the vertical direction and less-skilled squash players had high positive correlations. These results indicate that the head-hand movement pattern likely an important factor squash forehand movement. Conclusion: Analysis of head and hand movement patterns could be a key variable in squash training to reach expert-level performance.

• 대한인간공학회지
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• 제24권4호
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• pp.1-5
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• 2005

A glove design which reflects the changes in hand surface by hand motion can reduce the undesirable effects of use of gloves on hand performance. The present study examined changes in hand length dimensions due to hand motion and identified significant factors affecting the length changes. Recruiting 120 males and females in their 20s and 30s having various hand lengths, this study measured 10 hand length dimensions, defined at 2 hand areas(phalangeal and metacarpal areas) for 5 digits, when the hand is stretched and in fist, and then calculated the percentage of length increase for each dimension. ANOVA and simple-effect analyses showed the length change percentages were mainly different depending on digit and hand area: 111-127% at the phalangeal area and 112-116% at the metacarpal area. The length change percentages of the index, middle, ring, and little fingers in the phalangeal area ascended in order and showed a high correlation(r = 0.94)with the ranges of motion of the fingers.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1489-1490
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• 2011

• 대한전자공학회논문지SP
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• 제48권4호
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• pp.30-37
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• 2011

본 논문에서는 수신호 인식기에 쓰이기 위한 분별성 있는 손동작을 만드는 방법을 제안한다. 기존의 수화DB에서 손의 움직임을 분석하여 기본 동작이 되는 4가지의 모션 프리미티브를 선정하였으며, 선정된 모션 프리미티브를 조합하여 구별성 있는 '기본 손동작 집합'을 제작하였다. 제안하는 '기본 손동작 집합' 의 구별성을 증명하기 위하여 '기본 손동작 집합' 인식기를 만들고 인식결과를 확인하였다. 사용된 인식기는 hidden Markov model (HMM) 을 기반으로 제작되었다. 기본 손동작 인식 task에 대한 성능평가 결과 99.01%로써 각 모델 간에 높은 구별성을 보이는 것을 확인할 수 있었다.

• 산업기술연구
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• 제28권A호
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• pp.155-161
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• 2008

Muscle force prediction in forward dynamic analysis of human motion depends many muscle parameters associated with muscle actuation. This research studies the effects of various parameters of Hill type muscle model using the simple hand raising motion. Motion analysis is carried out using motion capture system, and each muscle force is recorded for comparison with muscle model generated muscle force. Using Hill type muscle model, muscle force for generating the same hand rasing motion was setup adjusting 5 activation parameters. The test showed the importance of activation parameters on the accurate generation of muscle force.

• 로봇학회논문지
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• 제18권4호
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• pp.367-375
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• 2023

Most partial hand amputees experience limited wrist movement, which hinders the efficient functioning of upper limb, affecting hand-to-use coordination and the usability of the prosthetic hand. This limitation can lead to secondary musculoskeletal issues due to repetitive compensatory movement patterns. However, current partial hand prosthetic lack rotational wrist movement due to challenges in accommodating various hand shapes and limited space. In our study, we proposed a prosthetic hand with a wrist rotation module for partial hand amputees, aiming to reduce compensatory movement. To validate the proposed wrist rotation module, we conducted motion analysis during reach-to-grasp task. Furthermore, during the Jebsen-Taylor hand function test, we evaluated both the effect on upper limb movement and the usability of the prosthetic hand, comparing configurations with and without the wrist rotation module. The results showed that the prosthetic hand equipped with rotational wrist movements reduces compensatory movements and promotes efficient upper limb movement patterns. This finding highlights the value of incorporating a wrist rotation module in prosthetic hands to improve upper limb movement for partial hand amputees.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권5호
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• pp.621-625
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• 2010

본 논문에서는 스마트 폰, PDA와 같은 모바일 장치에 있는 카메라 기기를 이용한 손동작 제스처 인터페이스를 위한 손 움직임 추적 방법을 제안하고 이를 바탕으로 한 손 제스처 인식 시스템을 개발한다. 사용자의 손동작에 따라 카메라가 움직임으로써, 전역 optical flow가 발생하며, 이에 대한 우세한 방향 성분에 대한 움직임만 고려함으로써, 노이즈에 강인한 손움직임 추정이 가능하다. 또한 추정된 손 움직임을 바탕으로 속도 및 가속도 성분을 계산하여 동작위상을 구분하고, 동작상태를 인식하여 연속적인 제스처를 개별제스처로 구분한다. 제스처 인식을 위하여, 움직임 상태에서의 특징들을 추출하여, 동작이 끝나는 시점에서 특징들에 대한 분석을 통하여 동작을 인식한다. 추출된 특징점을 바탕으로 제스처를 인식하기 위하여 SVM(Support vector machine), k-NN(k-nearest neighborhood classifier), 베이시안 인식기를 사용했으며, 14개 제스처에 대한 인식률은 82%에 이른다.