• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
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• pp.65-68
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• 2001

In the rehabilitation robotic arm systems for the disabled with spinal code injury, EMG signals are used in the control of the robotic arm. EMG signals are corrupted by many kinds of noises such as ECG signal, power noise and contact noise of electrode. Noise rejection improves the performance of the EMG pattern classification. In this paper, a variable bandwidth filter (VBF) and wavelet transform are used for the noise rejection of EMG signals and the comparison of SNR is given. Also, some statistical characteristics of features are investigated.

• 대한의용생체공학회:의공학회지
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• 제22권3호
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• pp.249-257
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• 2001

본 논물에서는 척수 손상으로 인하여 암이 수축 및 이완시 미약한 근전도, 신호를 발생시키는 환자로부터 명확한 수축 및 이완 패턴을 추출하기 위한 신호 처리 기법을 제안하였다. 제안한 방법은 비선형 고정 필터의 일종인 FatBear 필터를 이용하여 거대 운동단위 활동전위로 의심되는 충격 잡음을 제거하고 웨이브렛 평면에서 비선형 멀티 스케일 필터링 기법을 이용하여 가산 잡음을 제거하는 것으로서 횡단성 척수염으로 인한 마미 증후근을 보이는 환자들에게 적용하여 명확한 수축 및 이완 패턴을 추출할 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• 대한의생명과학회지
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• 제24권1호
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• pp.43-49
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• 2018

Electrocardiogram (ECG) is a widely used method to diagnose electrical activity of heart. Although it is a reliable and easy method, ECG could be interfered by electrical signals. One of the interfering signals is electromyogram (EMG) that is caused by muscle contraction in any parts of the body except heart. To avoid the EMG noise, an examinee is advised to be relaxed on supine position while measuring ECG. Sometimes, patients who can't put their arms and legs down on bed due to some reasons such as cast on arms or legs necessarily have the EMG noise. But detailed information about how much of the noise could be induced by positional change of arms and legs has not been reported. Here we examined the noise by analyzing ECG data from 14 candidates, 7 males and 7 females. The ECG data was obtained using the standard 12 lead ECG. EMG noise was induced by raising arms and legs at $90^{\circ}$, $60^{\circ}$ or $30^{\circ}$. Because arms are located close to the heart, noise by the raised arms was analyzed toward left or right arm separately. All of the examinees showed similar pattern of the EMG noise. EMG noise by positional change of left or right arm was clearly monitored in different limb leads. Change of leg positions induced the noise that was monitored in aVF of augmented leads and II and III of limb leads. There was a difference in degree of the noise between male and female examinees. In addition to the EMG noise, decrease of PR interval was monitored in particular positional changes, which was prominent in male examinees. These results will enlarge fundamental understanding about EMG noise in ECG.

• 한국소음진동공학회논문집
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• 제21권10호
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• pp.934-939
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• 2011

This paper experimentally deals with the relationship between the ankle electromyogram(EMG) and walking motion in order to activate the ankle joint of a walking-assistance robot for rehabilitation. Based on the anatomical structure and motion pattern of an ankle joint, major muscles were selected for EMG measurements. Surface EMG signals were monitored for several human bodies at various stride distances and stride frequencies. Root-mean-squared magnitude of EMG signals were related with the walking conditions. It appeared that the magnitude of the ankle EMG signal was linearly proportional to the stride distance and stride frequency, and thus to the walking speed.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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• pp.417-422
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• 2005

This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.398-401
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• 1997

The EMG signal of spinal cord injured patient is very feeble because that the information from central nervous system is not sufficiently transmitted to molter neuron or muscle fiber. Therefore the observer can not observe contraction and relaxation movement of muscle from the raw EMG signal. In this paper, we propose the muscle contraction and relaxation pattern analysis method of spinal cord injured patient whose EMG signal is composed of the sum of motor unit action potential train with additive white Gaussian noise and impulsive noise. From the EMG model, we denoise impulsive noise using median filter which is a kind of nonlinear filter and the output of median filter is transformed to wavelet transform domain for denoising additive white Gaussian noise using threshold level removal technique. As a result, we can obtain the clear contraction and relaxation pattern.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권6호
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• 감성과학
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• 제6권1호
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• pp.27-32
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• 2003

본 연구에서는 스포츠웨어용 나일론 직물 소리가 심한 소음으로 인해 불쾌감을 주므로 이를 감소시키기 위한 방안으로, 5개의 나일론 직물소리를 녹음하여 이를 피험자에게 들려주면서 EMG와 주관적 감각을 측정함으로써, 직물소음이 근전도와 주관적 감각에 미치는 영향을 고찰하였다. 근전도는 상완이두근과 전완근에서 측정하였고, 주관적 평가는 자유식 크기평가법(Free Modulus Magnitude Estimation)을 이용하였다. 직물 소리에 대한 상완이두근의 근전도 값은 전완근의 근전도값보다 컸으며, 소리자극 유무시의 차이값도 상완이두근에서 크게 나타났다. 직물의 소리가 부드럽고 유쾌할수록 근전도값은 무자극시보다 감소하는 경향을 보였으나, 직물의 소리가 시끄럽고 날카로울수록 근전도값은 무자극시보다 증가하였다. 직물의 소리는 상완이두근의 근전도 값에 영향을 미쳐, 직물 소음의 크기, 날카로움 등과 정적인 관계를 보이는 것을 볼 수 있었다. 직물소리의 물리적 특성과 근전도로부터 나일론 직물 소리에 대한 감각ㆍ감성 예측식에서는 높은 예측력을 보였다. 맑고, 거칠고, 높은 소리감각을 제외한 예측식에서 소리특성 외에 생리신호인 근전도 가 포함되어 직물소리 감성을 예측하는 의미있는 파라미터임을 알 수 있었다.

• 전기학회논문지
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• 제66권5호
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• pp.843-850
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• 2017

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is utilized as the control input to artificial prosthetic limbs. This paper describes an application of the optimal EMG amplitude estimator to the surface EMG signals recorded during constant isometric %MVC (maximum voluntary contraction) for 30 seconds and reports on assessing performance of the amplitude estimator from the application. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction. To examine the estimator performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that ARV(average rectified value) and RMS(root mean square) amplitude estimation with forth order whitening filter and 250[ms] moving average window length are optimal and showed the mean SNR improvement of about 50%, 40% and 20% for each 20%MVC, 50%MVC and 80%MVC surface EMG signals, respectively.