• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.17-18
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• 2014

현대사회와 미래사회는 가속화되어지는 IT기술에 의해서 융합되어진 작업의 효율 및 성능의 발전이 이슈화되고 있다. 따라서 1990년대부터는 군사 및 재활분야와 함께 제조업 및 유통업 등 전반적인 산업 모두에서 근력보조기구에 대한 연구가 활발히 진행되고 있다. 과거에는 일반인이 무거운 짐을 운반하는 것을 완전한 로봇이 대체하거나 몸이 불편한 사회적 약자가 휠체어 및 지팡이 또는 전동 휠체어와 같은 보조 개념이 아닌 완전한 대체의 개념을 가지고 있었다. 그러나 웨어러블이 대두됨에 따라 기계와 인체가 합쳐지는 상호작용 근력보조기구가 탄생했다. 근력보조기구는 힘/토크 센서를 통한 인간과 로봇간의 상호작용에 의해 인간의 다양한 상지 및 하지 동작을 구현할 수 있는 근력 강화용 웨어러블 로봇 등이 있다.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.79-85
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• 2021

Soft fluidic actuators (SFAs) are widely utilized in various areas such as wearable systems due to the inherent compliance which allows safe and flexible interaction. However, SFA-driven systems generally require a large pump, multiple valves and tubes, which hinders to develop a miniaturized system with small range of motion. Thus, a highly integrated soft actuator needs to be developed for implementing a compact SFA-driven system. In this study, we propose an electro-hydraulic soft zipping actuator that can be used as a miniature pump. This actuator exerts tactile force as a dielectric liquid contained inside the actuator pressurized its deformable part. In addition, the proposed actuator can estimate the internal dielectric liquid thickness by using its self-sensing function. Besides, the electrical characteristics and driving performance of the proposed system were verified through experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.824-825
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• 2023

본 연구는 동물을 위한 웨어러블 로봇을 개발하고, 이를 상황에 따라 적절한 보행을 제어할 수 있도록 강화학습(DQN 알고리즘)을 적용한다. 다양한 센서를 동물에 부착하여 얻은 데이터를 DQN 알고리즘에 입력으로 사용한다. 이 알고리즘은 수집된 데이터를 분석하여 어떤 상황에서 어떤 종류의 보행이 가장 적절한지를 판단하고, 이를 로봇에 적용하여 동물의 보행을 자연스럽게 구현한다

• Physical Therapy Rehabilitation Science
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• v.11 no.4
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• pp.478-487
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• 2022

Objective: This study was conducted to analyze the effect of wearable complex muscle support system on energy efficiency during walking in elderly. Design: Cross sectional study Methods: Twenty healthy elderly participated in this study. All subjects performed a 6 minuteswalk test(6MWT) and stair climbing test in dual, slack and no suit conditions. In each condition, oxygen consumption(VO₂), metabolic equivalents(METs), energy expenditure measures(EEm), physiological cost index(PCI), walking velocity and heartrate were measured. Through repeated measured ANOVA, it was investigated whether there was a statistically significant difference in the measurement results between the three conditions. Results: In over-ground walking, VO₂, METs and EEm showed significant differences between no suit and slack conditions(p<0.05). In stair climbing, VO₂ showed significant difference between slack and dual conditions(p<0.05). Also, METs and EEm showed significant differences between no suit and slack, and between slack and dual conditions(p<0.05). Conclusions: Wearing the wearable complex muscle support system for elderly does not have much benefit in energy metabolism efficiency in over-ground, but there is a benefit in stair walking.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1106-1114
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• 2012

To achieve synchronized motion between a wearable robot and a human user, the redundancy must be resolved in the same manner by both systems. According to the seven DOF (Degrees of Freedom) human arm model composed of the shoulder, elbow, and wrist joints, positioning and orientating the wrist in space is a task requiring only six DOFs. Due to this redundancy, a given task can be completed by multiple arm configurations, and thus there exists no unique mathematical solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and their effect on the redundancy resolution of the human arm based on a seven DOF manipulator model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing different cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid for the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each two consecutive points along the task space trajectory. As a first step, the redundancy based on the kinematic criterion will be thoroughly studied based on the motion capture data analysis. Experimental results indicate that by using the proposed redundancy resolution criterion in the kinematic level, error between the predicted and the actual swivel angle acquired from the motor control system is less than five degrees.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.868-871
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• 2016

Recently, Unmanned vehicle and Wearable Technology using iot research is being carried out. The unmanned vehicle is the result of it technology. Robots, autonomous navigation vehicle and obstacle avoidance, data communications, power, and image processing, technology integration of a unmanned vehicle or an unmanned robot. The final goal of the unmanned vehicle manual not autonomous by destination safely and quickly reaching. This paper managed to cover One of the key skills of unmanned vehicle is to image processing. Currently battery technology of unmanned vehicle can drive for up to 1 hours. Therefore, we use the Raspberry Pi 3 to reduce power consumption to a minimum. Using the Raspberry Pi 3 and to develop an image recognition system. The goal is to propose a system that recognizes all the objects in the image received from the camera.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1201-1216
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• 2017

In this study, we described the development of a methodology to measure tip-pinch strength on the paretic hand rehabilitation device and aimed to investigate reliability of the device. FSR sensors were embedded on the device, and tip pinch strength was estimated with data collected from the sensors using a developed equation while participants were demonstrating tip pinch. Reliability tests included inter-rater, test-retest, and inter-instrument reliability. B&L Engineering pinch gauge was utilized for the comparison. Thirty-seven healthy students participated in the experiment. Both inter-rater and test-retest reliability were excellent as Intraclass Correlation Coefficients (ICCs) were greater than 0.9 (p<0.01). There were no statistically significant differences in tip-pinch strengths. Inter-instrument reliability analysis confirmed good correlation between the two instruments (r = 0.88, p < 0.01). The findings of this study suggest that the two instruments are not interchangeable. However, the tip-pinch mechanism used in the paretic hand rehabilitation device is reliable that can be used to evaluate tip pinch strength in clinical environment and can provides a parameter that monitors changes in the hand functions.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.240-247
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• 2020

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.182-188
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• 2023

Due to the acceleration of an aging society, the need for lower limb exoskeletons to assist gait is increasing. And for use in daily life, it is essential to have technology that can accurately estimate gait phase even in the walking environment and walking speed of the wearer that changes frequently. In this paper, we implement an LSTM-based gait phase estimation learning model by collecting gait data according to changes in gait speed in outdoor level ground and stair environments. In addition, the results of the gait phase estimation error for each walking environment were compared after learning for both max hip extension (MHE) and max hip flexion (MHF), which are ground truth criteria in gait phase divided in previous studies. As a result, the average error rate of all walking environments using MHF reference data and MHE reference data was 2.97% and 4.36%, respectively, and the result of using MHF reference data was 1.39% lower than the result of using MHE reference data.