• Journal of the Ergonomics Society of Korea
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• v.32 no.6
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• pp.511-516
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• 2013

Objective: The objective of this study is designing an optimal hand tool through maximum grip force study accordance to the hand grip span. Background: In order to prevent musculoskeletal diseases, studies on hand tool design are proceeding based on grip strength, finger force, and contribution of individual finger force on total grip strength. However, experimental apparatus using a tool that is actually used in work place was almost non-existent. Method: 19 males were participated in an experiment. Using the load cell inserted real plier, finger force, grip strength, and subjective discomfort rate of both hands (dominant and non-dominant) were measured in 5 different hand grip span(45mm, 50mm, 60mm, 70mm, and 80mm). Results: There was significant difference(p<0.001) of total grip strength, individual finger force and subjective discomfort rating according to various hand grip span(45, 50, 60, 70, and 80mm). Also, statistically significant different(p<0.001) was shown between the dominant hand and non-dominant hand. In addition, individual finger force in maximum grip was in order of middle finger, ring finger, index finger, and little finger. Conclusion: Optimal grip span of pliers that exerting maximum grip strength is 50~60mm. Application: This finding is expected to be used for designing proper pliers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.759-760
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• 2010

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.300-305
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• 2009

This paper describes the intelligent robot's hand with three-axis finger force sensors for an intelligent robot. In order to grasp an unknown object safely, it should measure the mass of the object, and determine the grasping force using the mass, then control the robot's fingers with the grasping force. In this paper, the intelligent robot's hand for an intelligent robot was developed. First, the three-axis finger force sensors were designed and manufactured, second, the intelligent robot's hand with three-axis finger force sensors were designed and fabricated, third, the high-speed control system was designed and manufactured using DSP( digital signal processor), finally, the characteristic test to grasp an unknown object safely was carried out. It was confirmed that the developed intelligent robot's hand could grasp an unknown object safely.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.89-96
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• 2009

This paper describes the intelligent robot's hand with three finger sensors for a humanoid robot. In order to grasp an unknown object safely, the intelligent robot's hand should measure the mass of the object, and determine the grasping force using the mass, finally control the grasping force using the finger sensors and the controller. In this paper, the intelligent robot's hand for a humanoid robot was developed. First, the six-axis force/moment sensor was manufactured. second, three finger force sensors were designed and fabricated, third, the high-speed controller was manufactured using DSP(digital signal processor), finally, the characteristic test for determining a grasping force and for grasping an unknown object safely It is confirmed that the hand could grasp an unknown object safely.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.11
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• pp.37-45
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• 2010

Stroke patients can't use their hands because of the paralysis of their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by grasping a spherical object. At present, the used object in hospital is only a spherical object, and can't measure the force of fingers. Therefore, doctors judge the rehabilitating extent by touching and watching at their fingers. So, the spherical object measuring system which can measure the force of their fingers should be developed. In this paper, the finger-force measuring system with a six-axis force/moment sensor which can measure the spherical-object grasping force is developed. The six-axis force/moment sensor was designed and fabricated, and the force measuring device was designed and manufactured using DSP (digital signal processing). Also, the grasping force test of men was performed using the developed finger-force measuring system, it was confirmed that the average force of men was about 120N.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.238-245
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• 2010

Stroke patients can't use their hands because of the paralysis of their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by grasping a spherical object. At present, the object used in hospital is only a spherical object, and can't measure the force of fingers. Therefore, doctors judge the rehabilitating extent by touching and watching at their fingers. So, the spherical object measuring system which can measure the force of their fingers should be developed. In this paper, the finger-force measuring system with a three-axis force sensor which can measure the spherical-object grasping force is developed. The three-axis force sensor is designed and fabricated, and the force measuring device is designed and manufactured using DSP(digital signal processing). Also, the grasping force test of men is performed using the developed finger-force measuring system, it was confirmed that the average force of men was about 120 N.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.67-76
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• 1997

In this paper, a theoretical study is presented for the force control of a miniature robotic manipulator which is driven by a pair of piezo-electric bimorph cells. In the theoretical analysis, one finger is modeled as a flexible cantilevers with a force sensor at the tip and the finger is a solid beam. The robotic finger is used to hold the objects with different stiffness such as an iron block and a living insect and a moving objcet. So it is very important to develop an adequate controller for the holding operation of the finger. The main problems in force controlling are overdamping, overshoot and unknown environment(such as the stiffness of object and unknown plant parameters). So, the main target is propose the new fuzzy compensation for unknown environment and incease the system performance. The fuzzy compensation is implemented by using PI-type fuzzy approach to identified unknown environment. And the result of proposed controller was compared with the conventaional PID and optimal controller.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• Journal of Technologic Dentistry
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• v.33 no.4
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• pp.331-337
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• 2011

Purpose: The purpose of this study was to impact of force system change in finger spring that add helical coil one round on orthodontic force. Methods: The following conclusions were drawn from the experiment conducted after bending 90 samples with a CNC wire forming machine while changing the height and lumen size to 1mm - 3mm - 5mm and 2mm - 3mm - 4mm respectively in the coil of the force system in finger spring added with one wheel of helical coil of 18-8 stainless steel round wire (${\Phi}0.5mm$, spring hard) from Jinsung Co. in domestic market under the following conditions: Laboratory name = Instron 5942; Temperature($deg^{\circ}C$) = 18.00; Humidity(%) = 50.00; Rate 1 = 10.00000 mm/min; Compressive extension = 5.0mm. Results: When Coil height is 1, 3, 5mm and lumen size is 2, 3, 4mm reduce finger spring as mean value of compressive extension occasion maximum load(mN) increases as coil height rises, and lumen size grows to 5.0mm. And was expose that compressive load(mN) increases as coil position of finger spring rises and increase as lumen size is decrescent. Conclusion: As the adherence height of coil was raised from 1mm through 3mm to 5mm, compressive load increased. As the lumen size increased from 2mm through 3mm to 4mm, compressive load decreased. Therefore, these results suggest that it is desirable to lower the coil height and enlarge the lumen size to enhance the biomechanical efficiency of finger spring when manufacturing the finger spring for removable orthodontic devices.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.127-133
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• 2014

This paper describes a design and manufacture of a two-axis force sensor and a single-axis force sensor for the fingers of an intelligent robot's hand. The robot's finger is composed of a two-axis force sensor, a first knuckle, a single-axis force sensor, a second knuckle, a spring, a motor of first knuckle, a motor of second knuckle, and so on. The two-axis force sensor attached to the first knuckle and the single-axis force sensor attached to the second knuckle were designed and manufactured, and the characteristics test of two sensors was carried out. As a test results, the interference error of the two-axis force sensor was less than 0.68%, the repeatability error of each sensor was less than 0.02%, and then the non-linearity was less than 0.03%. It is thought that the sensors can be used for the fingers of the intelligent robot's hand for rehabilitation exercise of finger patients.