• Journal of KIISE
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• v.42 no.12
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• pp.1544-1550
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• 2015

Recently, the development of practical wearable robot interfaces has resulted in the emergence of wearable robots such as arm prosthetics or lower-limb exoskeletons. In this paper, we propose a novel method of wrist movement intention estimation based on a regression technique using electromyography of human bio-signals. In daily life, changes in user arm position changes cause decreases in performance by modulating EMG signals. Therefore, we propose an estimation method for robust wrist movement intention for arm position changes, combining several movement intention models based on the regression technique trained by different arm positions. In our experimental results, our method estimates wrist movement intention more accurately than previous methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.1181-1182
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.867-868
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• 2013

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.124-131
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• 2017

This paper present a novel approach to control the lower body power assistive exoskeleton system of a HEXAR-CR35 aimed at improving a muscular strength. More specifically the control of based on the human intention is crucial of importance to ensure intuitive and dexterous motion with the human. In this contribution, we proposed the detection algorithm of the human intention using the MCRS which are developed to measure the contraction of the muscle with variation of the circumference. The proposed algorithm provides a joint motion of exoskeleton corresponding the relate muscles. The main advantages of the algorithm are its simplicity, computational efficiency to control one joint of the HEXAR-CR35 which are consisted knee-active type exoskeleton (the other joints are consisted with the passive or quasi-passive joints that can be arranged by analyzing of the human joint functions). As a consequence, the motion of exoskeleton is generated according to the gait phase: swing and stance phase which are determined by the foot insole sensors. The experimental evaluation of the proposed algorithm is achieved in walking with the exoskeleton while carrying the external mass in the back side.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.132-143
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• 2017

While working in an industrial environment which requires extended periods of upright posture; workers tend to develop muscle fatigue due to the constant load on lower-limb muscles. In addition, when working while bending knees; muscle fatigue of lower back and hamstrings is increased due to the abnormal posture. This can lead to damage of muscles, induce musculoskeletal disorders, and reduce long-term working efficiency. Recent medical studies have shown that long-term working in an upright posture can induce musculoskeletal disorders such as foot fatigue, edema, pain and varicose veins. Likewise, medical and rehabilitation expenses have grown due to the increase in musculoskeletal conditions suffered by workers. For this problem, we aim to develop a device that can reduce the physical fatigue on the lower limbs by supporting the weight of workers during the extended periods of upright and bending postures in the industrial environments. In this paper, we have designed and manufactured a wearable weight support system; with a user intention algorithm that the users can maintain various postures. For validation of the developed system, we measured the muscle activity of the users wearing the system with EMG sensors.

• 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.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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.825-837
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• 2017

This paper describes a novel type of a walking rehabilitation robot that applies robot technologies to crutches used by patients with walking difficulties in the lower body. The primary features of the developed robot are divided into three parts. First, the developed robot is worn on the patient's chest, as opposed to the conventional elbow crutch that is attached to the forearm; hence, it can effectively disperse the patient's weight throughout the width of the chest, and eliminate the concentrated load at the elbow. Furthermore, it allows free arm motion during walking. Second, the developed robot can recognize the walking intention of the patient from the magnitude and direction of the ground reactive forces. This is done using three-axis force sensors attached to the feet of the robot. Third, the robot can perform a stair walking function, which can change vertical movement trajectories in order to step up and down a single stair according to the floor height. Consequently, we experimentally showed that the developed robot can effectively perform walking rehabilitation assistance by perceiving the walking intention of the patient. Moreover we quantitatively verified muscle power assistance by measuring the electromyography (EMG) signals of the muscles of the lower limb.