• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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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.

• Journal of Sensor Science and Technology
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• v.25 no.5
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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.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.3
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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.

• Journal of Sensor Science and Technology
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• v.12 no.2
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• pp.88-94
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• 2003

Electromyogram (EMG) is the bioelectric signal induced by motor nerves. Analyzing EMG with the movement produced by muscle contraction, we can provide input commands to a computer as a man-machine interface as well as can evaluate the patient's motional abnormality. In this paper, we developed an integrated miniaturized device which acquires and transmits the surface EMG of an interested muscle. Developed system measures $60{\times}40{\times}25mm$, weighs 100g. Using an amplifier circuitry on the electrodes and the radio frequency transmission, the developed system dispenses with the use of cables among the electrodes, amplifier, and the post processing system (personal computer). The wiring used in conventional systems can be obstacle for natural motion and source of motion artifacts. In results, the developed system improves not only the signal-to-noise ration in dynamic EMG measurement, but also the user convenience. We propose a new human-computer interface as well as a dynamic EMG measurement system as a possible application of the developed system.