• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.769-776
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• 2007

This paper proposes the human arm motion tracking algorithm based on the signal processing for surface EMG (electromyogram) sensors attached on both upper arm and shoulder. The signals acquired by using surface EMG sensors are processed with choosing the maximum in a short period, taking the absolute value, and filtering noises out with a low-pass filter. The processed signals are directly used for the motion generation of virtual arm in real time simulator. The virtual arm of simulator has two degrees of freedom and complies with the flexion and extension motions of elbow and shoulder. Also, we show the validity of the suggested algorithms through the experiments.

• 센서학회지
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• 제25권5호
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• pp.365-370
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• 2016

The study about VR (Virtual Reality) has been done from the 1960s, but technical limits and high cost made VR hard to commercialize. However, in recent, high resolution display, computing power and 3D sensing have developed and hardware has become affordable. Therefore, normal users can get high quality of immersion and interaction. However, HMD devices which offer VR environment have high latency, so it disrupts the VR environment. People are usually sensitive to relative latency over 20ms. In this paper, as adding the Electromyogram (EMG) sensors to typical IMU sensor only system, the latency reduction method is proposed. By changing software and hardware components, some cases the latency was reduced significantly. Hence, this study covers the possibility and the experimental verification about EMG sensors for reducing the latency.

• 한국정밀공학회지
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• 제25권3호
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• pp.141-146
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• 2008

The purpose of this study is to develop the algorithm which can control muscle power assist robot especially for elderly. Recently, wearable robots for power assistance are developed by many researchers, and its application fields are also variable such as for medical or military equipment. However, there are many technical barriers to develop the wearable robot. This study suggest a control method improving performance of a wearable robot system by using a EMG signal of major muscles and a force sensor signal as command signal of system. The result of the robot Prototype efficiency experiment, the case of Maximum Isometric motion it suggest 100% power of muscle, the man need only 66% of MVIC(Maximum Voluntary Isometric Contraction) to lift 5kg dumbbell without robot assist. However the man needs only 52% of MVIC to lift 5kg dumbbell with robot assist. Therefore 20% muscle power increased with robot assist. Also, we designed light weight robot mechanism that extract the command signal verified and drive the wanted motions.

• 센서학회지
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• 제12권2호
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• pp.88-94
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• 2003

근전도는 근육의 수축을 관장하는 신경다발의 전기적 흥분에 의해 생기는 생체전기신호이다. 따라서 근육운동에 따라 발생하는 근전도 신호를 측정, 분석하면 운동기능의 정상여부를 판단할 수 있을 뿐 아니라 사용자의 동작에 의해 컴퓨터나 전자장치를 작동시키는 인간-기계 인터페이스(man-machine interface)용 입력신호로도 사용할 수 있다. 본 연구에서는 사용자의 일상생활에서의 자연스러운 동작과 관련된 근전도 신호를 측정할 수 있는 소형의 무선 생체신호 측정시스템을 개발하였다. 기존의 근전도 측정 시스템에서 전극과 증폭기 사이에 존재하는 전선은 동적잡음의 원인이 되고 사용자의 동작을 방해할 수 있으므로 소형의 증폭회로를 전극 바로 위에 일체형으로 제작하였고 증폭기와 컴퓨터 사이에 무선 데이터 전송을 사용하여 사용자의 일상적인 원활한 동작을 가능케 하였다. 개발된 측정 시스템의 크기는 $60{\times}40{\times}25mm$이고 무게는 100g이다. 개발된 시스템에 대한 성능 평가결과 컴퓨터를 위한 새로운 인터페이스 장치, 운동선수의 훈련결과 분석, 환자의 재활훈련 성과 측정 그리고 가상현실 입력장비 등의 용도로 사용될 수 있음을 확인하였다.