• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1842-1848
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• 2017

Recently, user motion estimation methods using various wearable devices have been actively studied. In this paper, we propose a motion estimation system using Myo, which is one of the wearable devices, using two Myo and their dependency relations. The estimated motion is used as a command for remotely controlling the robot. Myo's Orientation and EMG signals are used for motion estimation. These two type data sets are used complementarily to increase the accuracy of motion estimation. We design and implement the system according to the proposed method and analyze the results through experiments. As a result of comparison with previous studies, the accuracy of motion estimation can be improved by about 12.3%.

• 로봇학회논문지
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• 제18권2호
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• pp.189-196
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• 2023

An abdominal brace is a recommended treatment for patients with lumbar spinal disorders. However, due to the nature of the static brace, it uniformly compresses the lumbar region, which can weaken the lumbar muscles or create a psychological dependence that worsens the condition of the spine when worn for an extended period of time. Due to these issues, doctors limit the wearing time when prescribing it to patients. In this paper, we propose a device that can dynamically provide abdominal pressure and support according to the lumbar motion. The proposed device is a wearable robot in the form of a brace, with actuators and a driving unit mounted on the brace. To enhance wearability and reduce the weight of the device, worm gears actuator and a multi-pulley mechanism were adopted. Based on the spinal motion of the wearer measured by the Inertia measurement unit sensors, the drives wire by driving pulley, which provide tension to the multi-pulley mechanism on both sides, dynamically tightening or loosening the device. Finally, the device can dynamically provide abdominal pressure and support. We describe the hardware and system configuration of the device and demonstrate its potential through basic control experiments.

• 한국의류학회지
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• 제48권2호
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• pp.312-327
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• 2024

In this study, a rehabilitation 3D printed wearable device was developed by combining an assembly-type robot hand and an integral-type robot hand through fused deposition 3D printing manufacturing with various hardness TPU (Thermoplastic Polyurethane) filaments. The hardware configuration of the robot hand includes a controller designed with four motors, one small servo motor, and a circuit board. In the case of the assembly-type robot hand model, a 3D printed robot hand was assembled using samples printed with TPU of hardness 87A and 95A. It was observed that TPU with a hardness of 95A was suitable for use due to shape stability. For the integrated-type robot hand model, the external sample using TPU of hardness 95A could be modified through a cutting method, and the hardware configuration is the same as the assembly-type. The system structure of the 3D printed robot hand was improved from an individual control method to a simultaneous transmission method.Furthermore, the system architecture of an integrated 3D printed robotic hand rehabilitation device and the application of the rehabilitation device were developed.

• 정보과학회지
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• 제24권3호
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• pp.71-76
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• 2006

• 제어로봇시스템학회논문지
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• 제21권5호
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• pp.421-426
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• 2015

Need to develop human body's posture supervised robots, gave the push to researchers to think over dexterous design of exoskeleton robots. It requires to develop quantitative techniques to assess human motor function and generate the command to assist in compliance with complex human motion. Upper limb rehabilitation robots, are one of those robots. These robots are used for the rehabilitation of patients having movement disorder due to spinal or brain injuries. One aspect that must be fulfilled by these robots, is to cope with uncertainties due to different patients, without significantly degrading the performance. In this paper, we propose chattering free sliding mode control technique for this purpose. This control technique is not only able to handle matched uncertainties due to different patients but also for unmatched as well. Using this technique, patients feel active assistance as they deviate from the desired trajectory. Proposed methodology is implemented on seven degrees of freedom (DOF) upper limb rehabilitation robot. In this robot, shoulder and elbow joints are powered by electric motors while rest of the joints are kept passive. Due to these active joints, robot is able to move in sagittal plane only while abduction and adduction motion in shoulder joint is kept passive. Exoskeleton performance is evaluated experimentally by a neurologically intact subjects while varying the mass properties. Results show effectiveness of proposed control methodology for the given scenario even having 20 % uncertain parameters in system modeling.

• 한국군사과학기술학회지
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• 제18권3호
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• pp.309-315
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• 2015

This paper presents a lower-limb exoskeleton testbed and its control method. An exoskeleton is a wearable robotic system that can enhance wearer's muscle power or assist human's movements. Among a variety of its applications, especially for military purpose, a wearable robot can be very useful for carrying heavy loads during locomotion by augmenting soldiers' mobility and endurance. The locomotion test on a treadmill was performed up to maximum 4km/h walking speed wearing the lower-limb exoskeleton testbed with a 45kg backpack load.

• 한국정밀공학회지
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• 제26권7호
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• pp.7-14
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• 2009

• 한국지능시스템학회논문지
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• 제26권3호
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• pp.176-181
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• 2016

본 논문은 EMG(Electromyogram) 신호 기반의 웨어러블 기기를 이용하여 화재 감지 자율 주행 로봇을 제어하는 시스템을 제안하였다. 사용자의 EMG 신호를 읽어내기 위한 기기로는 Myo armband를 이용하였다. EMG 신호의 데이터를 블루투스 통신을 이용하여 컴퓨터로 전송한 후 동작을 분류하였다. 그 후 다시 블루투스를 이용하여 분류한 데이터 값을 uBrain 로봇으로 전송해 로봇이 움직일 수 있도록 구현하였다. 로봇을 조종 가능한 명령으로는 직진, 우회전, 좌회전, 정지를 구성하였다. 또한 로봇이 사용자로부터의 블루투스 신호를 받아오지 못하거나 사용자가 주행모드 변경의 명령을 내리면 로봇이 자율 주행을 하도록 하였다. 로봇이 주변을 돌아다니면서 적외선 센서로 화재를 감지하면 LED를 깜빡여 로봇 주변의 상황을 확인할 수 있도록 하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.263-264
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• 2012

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1751-1768
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• 2011

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.