• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2073-2078
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• 2015

This study is investigated for angle of elbow joint influence on grasp strength, confirm change of grasp strength and brachioradialis thickness according to angle of elbow joint in standing. Thirty male and female university students, who participated with agreement in this study, using for electronic dynamometer and convertible ultrasound measure maximum grasp strength and brachioradialis thickness after elbow joint $0^{\circ}$, $90^{\circ}$, $135^{\circ}$ positioning in standing. In average grasp strength was strongest at elbow joint $0^{\circ}$, as the angle of elbow joint increased, was decreased grasp strength, no significant statistically(p<.05). In average brachioradialis thickness was lowest at elbow joint $0^{\circ}$, as the angle of elbow joint increased, was increased brachioradialis thickness, significant statistically(p<.05). These result may indicated that change of elbow joint angle not influence on grasp strength, but influence on brachioradialis thickness.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.14 no.2
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• pp.25-33
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• 2008

Purpose : This study was investigated the effect on grasp and pinch strength according to degree of flexion in elbow joint. Methods : Thirty male and thirty female students, aged 20 to 31 years were tested for using opened positioning with their shoulder abduction at $55^{\circ}$ and shoulder horizontal adduction at $30^{\circ}$ in four elbow flexion($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$). An electronic dynamometer(E-LINK V900s Evaluation System)and goniometer were used to measure grasp and pinch strength. Results : The average grasp strength of the dominant hand was strongest at elbow $45^{\circ}$ however, weakest at elbow $135^{\circ}$ flexion in both of male and female. The average pinch strength of the dominant hand was strongest at elbow $135^{\circ}$ flexion in both of male and female. The average pinch strength of dominant hand was weakest at elbow $45^{\circ}$ flexion in both of male and female. According to degree of elbow flexion in both of male and female, grasp and pinch strength was no significant statistically. In analyzing correlations, the grasp strength of male showed the most significant difference at elbow $45^{\circ}$ & $90^{\circ}$ flexion, and the pinch strength was most significant difference at elbow $0^{\circ}$ & $45^{\circ}$ flexion. Conclusion : In analyzing correlations, the grasp strength of female showed the most significant difference at elbow $90^{\circ}$ & $135^{\circ}$ flexion, and the pinch strength was most significant difference at elbow $45^{\circ}$ & $90^{\circ}$ flexion.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.54-64
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has mainly analyzed with either unknown objects 2-dimensionally by vision sensor or known objects, such as cylindrical objects, 3-dimensionally. As extending the previous work, in this study we propose an algorithm to analyze grasp of unknown objects 3-dimensionally by using vision sensor. This is archived by two steps. The first step is to make a 3-dimensional geometrical model for unknown objects by using stereo matching. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand which has the characteristic of multi-finger hand and is easy to model. To find the optimal grasping points, genetic algorithm is employed and objective function minimizes the admissible force of finger tip applied to the objects. The algorithm is verified by computer simulation by which optimal grasping points of known objects with different angle are checked.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.927-932
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• 2001

When people write a character with a pen stably, proper compliance planning is necessary. In this paper, after investigating the property of character writing task, we propose a fundamental grasp model for character writing and also analyze compliance characteristics for effective character writing using multi-fingered hands. For this, the general stiffness relation of multi-fingered hand is firstly described. Next, we investigate the grasp configurations for grasping a pen and then, we analyze the conditions of the specified stiffness matrix in the operational space to successfully and more effectively achieve the given character writing task. Through the analysis, an effective grasp modeling for successful character writing is shown. And also, we conclude that the operational compliance characteristics should be properly planned for character writing, stably and precisely.

• Journal of Korean Physical Therapy Science
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• v.2 no.3
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• pp.707-725
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• 1995

The hand is an integral part of normal hand functioning. The ability of the hand to grasp and manipulate objects or tools is necessary for accom-plishing many tasks of daily living. Therefore it is important to improve hand function for patient with hand impairment. The objectives of this article are to review the developmental process of hand function and to described the types of grasp, grip, pinch, and prehension. Developmental process of hand function is based on general developmental theory as Vojta, Bobath and Ayres. There are many kinds of classification of prehension, grasp, and pinch. This review include the classification by Malick, Kiel, Melvin, Sollrman & Sperling, Pedretti & Zoltan, Tyldesley & Grieve' book, Norkin & Levangie' book. This article hope to give the information for application in physical and occupational therapy practice.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.258-263
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• 2014

An adaptive robot hand (AR-Hand) has a stable grasp of different objects in unstructured environments. In this study, we propose an AR-Hand based on a tendon-driven mechanism which consists of 4 fingers and 12 DOFs. It weighs 0.5 kg and can grasp an object up to 1 kg. This hand based on the adaptive grasp mechanism is able to provide a stable grasp without a complex control algorithm or sensor system. The fingers are driven by simple tendon structures with each finger capable of adaptively grasping the objects. This paper presents a method to decide the joint stiffness. The adaptive grasping is verified by various grasping experiments involving objects with different shapes and sizes.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1929-1930
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• 2006

Human like robot arm posture for grasping by considering the shape of the target object is quite a challenge in the field of robotics. In this paper, an optimized grasp posture with respect to the shape of the object considering the wrist joint angle and elbow elevation angle, in order to verify that the grasp posture is human like has been proposed. Given a target object, the candidates for grasp are computed by the method described in this paper. For each candidate, the closed loop inverse kinematics has been solved for the corresponding hand position and orientation. From the obtained joint angles through inverse kinematics, the elbow elevation angle has been computed and compared with the elbow elevation angle obtained through human movement data by the characteristic equation. After considering all the candidates, the hand position and orientation with minimum wrist joint and difference in elbow elevation angles has been utilized as the optimized grasp posture. Simulation results are presented.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.3
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• pp.119-124
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• 2014

Let G = (V, E) be a graph. Maximum Bipartite Subgraph Problem is to convert a graph G into a bipartite graph by removing minimum number of edges. This problem belongs to NP-complete; hence, in this research, we are suggesting a new metaheuristic algorithm which combines Tabu search and GRASP.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.133-142
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• 2011

Overhead facility design problem(OFDP) is one of the shortest rectilinear flow network problem(SRFNP)[4]. Genetic algorithm(GA), artificial immune system(AIS), population management genetic algorithm (PM) and greedy randomized adaptive search procedures (GRASP) were introduced to solve OFDP. A path matrix formed individual was designed to represent rectilinear path between each facility. An exchange crossover operator and an exchange mutation operator were introduced for OFDP. Computer programs for each algorithm were constructed to evaluate the performance of algorithms. Computation experiments were performed on the quality of solution and calculations time by using randomly generated test problems. The average object value of PM was the best of among four algorithms. The quality of solutions of AIS for the big sized problem were better than those of GA and GRASP. The solution quality of GRASP was the worst among four algorithms. Experimental results showed that the calculations time of GRASP was faster than any other algorithm. GA and PM had shown similar performance on calculation time and the calculation time of AIS was the worst.