• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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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.

• Korean Journal of Applied Biomechanics
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• v.28 no.2
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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.

• Journal of the Ergonomics Society of Korea
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• v.24 no.4
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1489-1490
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• 2011

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.30-37
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• 2011

This paper proposes a language set of hand motions for enhancing the performance of vision-based hand signal recognizer. Based on the statistical analysis of the angular tendency of hand movements in sign language and the hand motions in practical use, we construct four motion primitives as building blocks for basic hand motions. By combining these motion primitives, we design a discernable 'fundamental hand motion set' toward increasing the hand signal recognition. To demonstrate the validity of proposed designing method, we develop a 'fundamental hand motion set' recognizer based on hidden Markov model (HMM). The recognition system showed 99.01% recognition rate on the proposed language set. This result validates that the proposed language set enhances discernaility among the hand motions such that the performance of hand signal recognizer is improved.

• Journal of Industrial Technology
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• v.28 no.A
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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.

• The Journal of Korea Robotics Society
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• v.18 no.4
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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.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.