• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.329-336
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• 2016

Deaf people using sign language are experiencing social inequalities and financial losses due to communication restrictions. In this paper, real-time pattern recognition algorithm was applied to distinguish American Sign Language using an armband sensor(8-channel EMG sensors and one IMU) to enable communication between the deaf and the hearing people. The validation test was carried out with 11 people. Learning pattern classifier was established by gradually increasing the number of training database. Results showed that the recognition accuracy was over 97% with 20 training samples and over 99% with 30 training samples. The present study shows that sign language recognition using armband sensor is more convenient and well-performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.667-676
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• 2021

Recently, adolescents in Korea are exposed to the risk of postural imbalance due to overuse of smartphones and lack of physical activity due to the amount of learning. In addition, the need for effective non-face-to-face exercise services is increasing due to Corona 19. With this in mind, this study proposes an exercise service using an EMG sensor to overcome the limitations of non-face-to-face services while providing the effect of improving round shoulders for adolescents. An exercise program that can improve round shoulders was constructed, and an application in conjunction with an EMG sensor was implemented to exercise effectively. The exercise program was configured to alternately exercise the target muscle area for 4 weeks, and the function to provide feedback was added by measuring the EMG values that change accordingly. Through this study, we intend to provide the basis for exercise-based posture correction digital service, and improve the unbalanced body through this, thereby promoting the possibility of health promotion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5440-5445
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• 2014

Many studies have examined robot control using human bio signals but complicated signal processing and expensive hardware are necessary. This study proposes a method to recognize a human's hand motion using a low-cost EMG sensor and Flex sensor. The method to classify movement of the hand and finger is determined from the change in output voltage measured through MCU. The analog reference voltage is determined to be 3.3V to increase the resolution of movement identification through experiment. The robotic hand is designed to realize the identified movement. The hand has four fingers and a wrist that are controlled using pneumatic cylinders and a DC servo motor, respectively. The results show that the proposed simple method can realize human hand motion in a remote environment using the fabricated robotic hand.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.369-376
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• 2007

Recently, obesity that is increasingly becoming a major cause of various diseases is emerging as a serious social problem. In order to solve this problem, the necessity of measurement systems for overweight management has increased. This paper is a study on the measurement system for obesity management that can offer right medical services everywhere and allways by analyzing EMG (electromyograph) of the abdomen and then checking one's health state. For analyzing EMG signals of the abdomen, algorithms for energy detection, signal feature extraction, classification and recognition are presented. This paper proposes a system that provides an appropriate an estimation on the health status by evaluating the obesity degree and muscular strength of the abdomen through the system applying these algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.161-164
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• 2008

A realization for EMG signal sensing and vertical control system of robotizing arm is presented in this paper. The system is realized that a fine EMG bio-signals of humans' arm muscle are detected by surface electrode sensor, making a high performance amplifier and filtering, converting analog into digital signal and driving a servomotor for robotizing arm. The system is experimented by monitoring multiple step vertical control angles of robotizing arm corresponding to EMG signals in moving arm muscles. The experimental result are that the vertical control level is measured to around 2 degrees and mean error is 5% approximately.

• 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.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.240-244
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• 2008

This paper presents an EMG-based wireless and wearable computer interface. The wearable device contains 4 channel EMG sensors and is able to acquire EMG signals using signal processing. Obtained signals are transmitted to a host computer through wireless communication. EMG signals induced by the volitional movements are acquired from four sites in the lower limb to extract a user's intention and six classes of wrist movements are discriminated by employing an artificial neural network (ANN). This interface could provide an aid to the limb disabled to directly access to computers and network environments without conventional computer interface such as a keyboard and a mouse.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1031-1033
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• 2017

본 논문에서는 EMG(Electromyogram) 신호 기반의 재활 치료용 VR(Virtual Reality) 플랫폼을 제안한다. EMG 신호는 근육의 움직임을 확인할 수 있는 생체 신호로, EMG 신호를 활용하면 근육에 직접적인 움직임이 없어도 환자의 행동 의도를 확인할 수 있다. 본 논문에서는 EMG 신호를 이용하여 환자의 근육 움직임을 확인하며, 해당 움직임을 나타내는 VR 콘텐츠에 대한 제안과 실제 제작 콘텐츠를 소개한다. 실험 결과는 실제 근육 움직임에 대한 인식률을 확인하였다.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.41-50
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• 2023

This study aims to develop electromyography (EMG) textile electrodes and assess their performance and signal stability by examining variations in layer count and fabric types. We fabricated the electrodes through layering and pressing techniques, focusing on configurations with different layer counts (Layer-0, Layer-1, and Layer-2). Our findings indicate that layer presence significantly influences muscle activation measurements, with enhanced performance correlated with increased layer numbers. Subsequently, we created electrodes from five distinct fabrics (neoprene, spandex cushion, 100% polyester, nylon spandex, and cotton canvas), each maintaining a Layer-2 structure. In performance tests, nylon spandex fabric, particularly heavier variants, outperformed others, while the spandex cushion electrodes showed superior stability in muscle activation signal acquisition. This research elucidates the connection between electrode performance and factors like layer number and electrode-skin contact area. It suggests a novel approach to electrode design, focusing on layer properties and targeted pressure application on specific sensor areas, rather than uniformly increasing sleeve pressure.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.128-133
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• 2002

We developed a electronic music glove (BMG) system that plays musical scores in real time processing. The EMG system interfaces with the signal coming from the controller to the sound card in the computer, The computer, according to the status of the fingers and foot switches, generates the sound signals and sends them to the speaker systems through the application C++ program and MIDI message. The EMG systems control the velocity and duration of sound and several musical performance expressions such as chorus, reverberation, rhythm, and volume. Finally, we implemented the digital drum set using: the EMG system as example.