• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.379-386
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• 2023

When patients suffer from finger injuries, their finger joints can become stiff and inflexible due to decreased ability to exercise the finger tendons. This can lead to a loss of strength and difficulty using their hands. To address this, it is important to provide patients with consistent rehabilitation treatment that can help restore finger flexibility and strength simultaneously. In this study, we propose wearable gloves that use FSRs (force sensitive resistors) for finger strength training. The glove is designed to be adjustable using rubber bands and a custom PCB is designed for signal acquisition. For the evaluation of finger strength training, the result was analyzed in four cases. We suggest a vector that represents the center of five finger forces, and the result shows that the vector can indicate the level of force balance.

• Korean Journal of Applied Biomechanics
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• v.26 no.1
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• pp.93-99
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• 2016

Objective: The purpose of this study was to investigate the effect of transcutaneous electrical nerve stimulation (TENS) treatment on maximum voluntary force (MVF) production. Methods: Ten healthy, young subjects (5 males and 5 females) participated in the study. MVF was recorded after a fifteen minute session of TENS stimulation under two conditions: low frequency (4 Hz) at maximum tolerable level and high frequency (110 Hz) at maximum tolerable level. TENS was provided simultaneously via self-adhesive electrodes placed on the finger pads of the index, middle, ring and little fingers. MVF was also recorded in a baseline condition with no TENS treatment. Data were collected in three different sessions on three consecutive days at the sametime of the day. Results: Results from the study show that on an average, MVF increasesby 25% for the index, middle and little fingers for TENS treatment with 4 Hz frequency as compared to the baseline condition. However, the 110 Hz condition did not result in a significantly different MVF than the baseline condition during individual finger pressing tasks. In addition, while producing MVF with all the four finger stogether, MVF was 30% higher for the 4 Hz conditionin comparison to the baseline condition, and 15% higher for the 110 Hz condition in comparison to the baseline condition respectively. Conclusion: The results suggest that stimulation ofafferent fibers onthe glabrous skinwith TENS could have a net facilitatory effect on the maximum motoroutput.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.10
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• pp.865-871
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• 2015

This study was conducted in order to develop a finger exoskeleton system using ionic polymer metal composites (IPMCs) as the actuator and sensor in a hybrid structure. To use the IPMC as an actuator producing large force, a first order transfer function was obtained using results from a block force for DC excitation that applied to two IPMCs of 20mm-width, 50mm-length, and 2.4mm thickness together. After which the validation of 200gf control with anti-windup PI controller was confirmed. A 5mm-width, 50mm-length, 0.6mm-thickness of IPMC was also modeled as a sensor for tip displacement. As a result, the IPMC sensor could been utilized as a trigger role for the actuator. Finally, an IPMC sensor and actuator were installed on the joint of a single DOF exoskeleton in the hybrid structure, and test for the control of 40gf of block force and predefined sequence of motion was performed.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.94-103
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• 2019

The optimal grasping point of the object varies depending on the shape of the object, such as the weight, the material, the grasping contact with the robot hand, and the grasping force. In order to derive the optimal grasping points for each object by a three fingered robot hand, optimal point and posture have been derived based on the geometry of the object and the hand using the artificial neural network. The optimal grasping cost function has been derived by constructing the cost function based on the probability density function of the normal distribution. Considering the characteristics of the object and the robot hand, the optimum height and width have been set to grasp the object by the robot hand. The resultant force between the contact area of the robot finger and the object has been estimated from the grasping force of the robot finger and the gravitational force of the object. In addition to these, the geometrical and gravitational center points of the object have been considered in obtaining the optimum grasping position of the robot finger and the object using the artificial neural network. To show the effectiveness of the proposed algorithm, the friction cone for the stable grasping operation has been modeled through the grasping experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.221-222
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.1305-1306
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• 2012

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.891-894
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• 2005

This paper describes a human finger model driven by shape memory alloy(SMA) wires. The finger model has three joints that are similar to human finger. Each joint is actuated with two wires in the antagonistic manner and six wires are used to actuate three finger joint. In order to obtain the desirable finger motion, the diameters of the SMA wires are designed with different diameters by considering the required actuating force and response time. The rotary sensors are used to measure the angle positions of the joints and PWM control using PID algorithm is used to achieve desired angle positions of the finger joints. After estimating the control performance of each finger joint for the desired angle position, the antagonistic motion control of the finger model is experimentally evaluated.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.190-194
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• 2002

Human uses sight, tactile sense to evaluate Total Hand Value(FUUAI) of textile fabrics. Tactile sense is important factor which decided the Total Hand Value of a textile fabric. When human feels the FUUAI, physical and physiological phenomena are occurred in finger. We first found out physical variable that is happened in fingertip when human is feeling the FUUAI. Such physical variable means characteristic of action tactual motion of finger such as moving range, tactile time, moved distance, speed of finger and applied force by finger. We study the relationship between action tactual motion and the ability in which the human distinguishes the textile fabric. As a result, we could know the characteristics of the tactual motion of fingertip to get high distinguishable ability. The characteristics were different in men and women respectively. In the case of man, touched time and moving range influenced to distinguish, and moving range, and the moving speed of finger influenced, in woman's case.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.175-181
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• 2016

Objective: The aim of this study was to investigate age-related changes of multi-finger synergy during a constant force production task with and without an additional mechanical constraint. Method: Fourteen elderly subjects (age: $78.50{\pm}4.63yrs$, height: $157.29{\pm}8.97cm$, weight: $65.13{\pm}6.93kg$) and 14 young subjects (age: $21.13{\pm}1.35yrs$, height: $171.57{\pm}8.43cm$, weight: $70.29{\pm}16.77kg$) participated in this study. The subjects were asked to place their index and middle fingers on two force transducers fixed on a small non-moving teeterboard and produce 10 N by pressing the sensors while watching force feedback on a computer screen under the no additional constraint condition (NAC). The subjects also performed the same task with an additional mechanical constraint (AC) where the subjects were asked to balance a teeterboard that could be rotated by finger forces. An uncontrolled manifold approach was used to calculate within-trial and between-trial multi-finger synergy indices, variance in uncontrolled subspace ($V_{UCM}$), and variance in subspace orthogonal to UCM subspace ($V_{ORT}$). Two-way repeated measured ANOVA was performed with the within-factor of task condition (with and without an additional constraint) and the between factor of groups (elderly and young). Results: The elderly group showed significantly increased within-trial $V_{ORT}$ in AC compared with NAC (p < .05) while the young group showed no significant difference between AC and NAC. There was no significant group difference for within-trial $V_{UCM}$. Between-trial $V_{ORT}$ remained unchanged between groups and conditions. However, between-trial $V_{UCM}$ for the elderly group significantly decreased in AC as compared to NAC, along with no significant difference for the young group. For multi-finger synergy, there was no significant group difference of within-trial synergy. However, between-trial synergy for the elderly group significantly decreased in AC as compared to NAC (p < .05). Conclusion: Our results indicate that aging decreased consistency (i.e., ability to perform the task on a moment-to-moment basis) with an additional mechanical constraint. In addition, aging was associated with decreased multi-finger synergy on a trial-to-trial basis.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.51-58
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• 2004

This paper describes the development of a small 6-axis force/moment sensor for robot's finger, which measures farces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In order to safely grasp an unknown object using the robot's gripper, and accurately perceive the position of it in the gripper, it should measure the force in the gripping direction, the force in the gravity direction and the moments each direction, and perform the force control using the measured forces and moments. Also, it should detect the moments Mx (x-direction moment), My and Mz to accurately perceive the position of the object in the grippers. Thus, the robot's gripper should be composed of 6-axis force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In this paper, the small 6-axis force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test for the developed sensor was performed, and the result shows that intereference errors of the developed sensor are less than 4.23％. Thus, the developed small 6-axis force/moment sensor may be used a robot's gripper.