• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.799-804
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• 1991

This paper is concerned with the artificial control of prosthetic devices using the electromyographic(EMG) activities of biceps and triceps in human subject during isometric contraction adjustments at the elbow. And it was analysised about recognition of EMG signals and dynamic characteristics at arm movements of human. For this study the error signal of autoregressive(AR) model were used to discriminate arm movement patterns of human. Interaction of dynamic characteristics (Position, Velocity, Acceleration) and EMG of biceps and triceps at arm movements of human was measured.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1951-1958
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• 2011

The objective of this study is to analyze the performance of digital low-pass differentiators(LPD) and then to provide a method to select effective LPD filter, for detecting spikes of surface motor unit action potentials(MUAP). The successful spike detection of MUAPs is a first important step for EMG signal decomposition. The performances of simple and weighted LPD(SLPD and WLPD) filters are analyzed based on different filter lengths and varying MUAPs from simulated surface EMG signals. The SNR improving coefficient and effective MUAP duration range from the analysis results can be used to select proper LPD filters under the varying conditions of surface EMG.

• Proceedings of the KOSOMBE Conference
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• v.1985 no.06
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• pp.5-8
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• 1985

This paper describes the use of power spectral densing in the examination of the electromogram (EMG). The EMG signals were obtained with surface electrodes from the biceps brachii muscle. Shifts of the high-energy regions of the power spectra can be inferred from the changes in the mean frequency. This paper is consistent with result that most information of EMG signal is located 10-200 Hz.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.306-309
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• 2000

We developed an electronic music glove (EMG) system that could play 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 finger and foot switches, generates the signals to the speaker systems using the application C++ program by making use of MIDI message. The EMG systems can control up to several octave notes and duration of sound, and several musical performance expressions such as chorus, reverberation, rhythm, and volume. Finally, our EMG could play the performance of simple music depending on the choice of any kind of musical instruments in the sound card in computer systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.493-494
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• 2013

본 논문에서는 컬-덤벨 운동의 연속, 반복적인 근 수축/이완 동작에 대한 전환 시점을 검출하기 위한 EMG(Electromyogram) 신호 분석 모듈을 설계하였으며 이에 대한 안드로이드 플랫폼 기반의 테스트 프로그램을 구현하였다. 제안하는 모듈로는 무산소 운동 분석에의 활용도가 높은 EMG 신호를 기반으로 근 수축/이완의 전환 시점을 95% 검출하며, 이를 개선 및 확장함으로써 현재 상용화 및 보급화된 운동 가이드 시스템에서 제공할 수 없었던 무산소 운동의 체계적 가이드를 제공할 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.631-632
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• 2013

본 논문에서는 EMG 신호를 기반으로 컬-덤벨 운동의 운동량을 분석하고 각 근육별 최적 운동량을 정의하여 운동을 가이드(guide)하는 방법을 제안한다. 제안하는 방법으로 운동 체육학 분야에서의 EMG 신호 분석 및 활용 범위를 넓힐 수 있으며, 사용자는 컬-덤벨 운동 중 각 근육별 운동량 및 이에 대한 적절성을 안내받아 올바른 자세를 유지함으로써 컬-덤벨의 운동 효과를 극대화할 수 있다.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.175-181
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• 2003

Studies of muscle fatigue have mostly been checked under isometric exercise. However EMG signals from isotonic exercise generate uncontrollable noise, so there were difficulties in gathering reliable median frequency and muscle fatigue index if frequency analysis was equally applied in isometric exercise. This study tried to compare the differences of muscle fatigue determinant variables in terms of median frequency searching methods of EMG signal, which was estimated in isotonic exercise. To accomplish this, we determined median frequency by using different FFT intervals and overlapping ration of consecutive FFT sections under the same EMG signal, and then searched for a linear regression line, and compared initial median frequency, slope, and muscle fatigue index which were variables under the linear regression line. In result of comparison, initial median frequency was more elevated as FFT exercise interval became larger. The slope of the linear regression line showed distinguishable decreasing tendency as FFT intervals were larger and overlapping sections were smaller. Significant tendency of muscle fatigue index in FFT interval was shown by high muscle fatigue index in specific FFT intervals.

• 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.

• 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.