• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.161-164
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• 2008

본 논문은 근전도 신호를 검출하고 로봇팔의 수직제어시스템을 구현하기 위한 연구이다. EMG 신호는 사람의 팔 근육에 흐르는 미세한 생체신호가 표면전극센서에 의해서 사용하여 검출되고 고성능 증폭, 필터링, ADC과 로봇팔의 서보 모터 구동 시스템으로 구현된다. 실험은 팔근육 움직임에 따른 EMG신호와 로봇팔의 다단계 수직제어 각도를 모니터링 한다. 시스템의 실험결과 수직제어각도는 2도 정도이며 평균오차는 5%이다.

• 전기학회논문지
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• 제60권10호
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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.

• 한국정보통신학회논문지
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• 제10권10호
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• pp.1779-1785
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• 2006

본 논문은 근전도 패턴 인식에 의한 가상 로봇팔 제어 방식을 제안한다. 고차원의 근전도 신호를 정밀하게 분류하기 위하여 혼합형 신경 회로망 방식을 사용한다. 혼합형 신경회로망은 SOFM과 LVQ로 구성되고, 고차원의 EMG 신호를 2차원 데이터로 변환한다. 3개의 표면 전극을 이용하여 EMG 신호를 측정 한다. 제안한 혼합 시스템을 이용하여 한글 자음 6개의 수화 신호를 분류한다. 가상 로봇팔 실험을 통해서 제안한 혼합 시스템을 이용한 수신호의 EMG 패턴 인식의 유용성을 확인하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.35-38
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• 1997

A new approach to the measurement of muscle fiber conduction velocity by surface electro-myography(EMG) is developed, based upon a robust time-delay estimation algorithm. Unlike previously reported methods, it does not require the Gaussian assumption of raw EMG signal, and can be applied accurately in non-gaussian impulsive EMG signal. For ive healthy subjects the conduction velocity in the biceps brachii and vastus medialis was measured and compared with various other techniques. As a result, the average muscle fiber conduction velocity was $4.59{\pm}0.20m/s$ in case of biceps brachii and $5.67{\pm}0.33m/s$ in vastus medialis.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권7호
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• pp.344-351
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• 2006

The fatigue of back muscle in the repetitive lifting motion was studied using multiple parameters(FFT_MDF, RMS, 2C, NT) in this study. Recent developments in the time-frequency analysis procedures to compute the IMDF(instantaneous median frequency) were utilized to overcome the nonstationarity of EMG signal using Cohen-Posch distribution. But the above method has a lot of computation time because of its complexity. So, in this study, FFT_MDF(median frequency estimation based on FFT) algorithm was used for median frequency estimation of back muscle EMG signal during muscle work in uniform velocity portion of lumbar movement. The analysis period of EMG signal was determined by using the run test and lumbar movement angle in dynamic task, such as lifting. Results showed that FFT_MDF algorithm is well suited for the estimation of back muscle fatigue from the view point of computation time. The negative slope of a regression line fitted to the median frequency values of back muscle EMG signal was taken as an indication of muscle fatigue. The slope of muscle fatigueness with FFT_MDF method shows the similarity of 77.8% comparing with CP_MDF(median frequency estimation based on Cohen Posch distribution) method.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권5호
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• pp.380-388
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• 2004

This study proposed an improved spike detection algorithm which automatically detects suitable spike threshold on the amplitude of surface electromyography(SEMG) signal during isometric contraction. The EMG data from the low back muscles was obtained in six channels and the proposed signal processing algorithm is compared with the median frequency and Gabriel's spike parameter. As a result, the reliability of spike parameter was inferior to the median frequency. This fact indicates that a spike parameter is inadequate for analysis of multi-channel EMG signal. Because of uncertainty of fixed spike threshold, the improved spike detection algorithm was proposed. It automatically detects suitable spike threshold depending on the amplitude of the EMG signal, and the proposed algorithm was able to detect optimal threshold based on mCFAR(modified Constant False Alarm Rate) in the every EMG channel. In conclusion, from the reliability points of view, neither median frequency nor existing spike detection algorithm was superior to the proposed method.

• 대한의용생체공학회:의공학회지
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• 제27권3호
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• pp.101-109
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• 2006

It has been known that there is strong relationship between human voices and the movements of the articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The EMG signals were acquired from three articulatory facial muscles. Preliminary, 10 Korean digits were used as recognition variables. The various feature parameters including filter bank outputs, linear predictive coefficients and cepstrum coefficients were evaluated to find the appropriate parameters for EMG-based speech recognition. The sequence of the EMG signals for each word is modelled by a hidden Markov model (HMM) framework. A continuous word recognition approach was investigated in this work. Hence, the model for each word is obtained by concatenating the subword models and the embedded re-estimation techniques were employed in the training stage. The findings indicate that such a system may have a capacity to recognize speech signals with an accuracy of up to 90%, in case when mel-filter bank output was used as the feature parameters for recognition.

• Journal of Electrical Engineering and Technology
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• 제7권3호
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• pp.451-458
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• 2012

The voluntary EMG (vEMG) signal from electrically stimulated muscle is very useful for feedback control in functional electrical stimulation. However, the recorded EMG signal from surface electrodes has unwanted stimulation artifact and M-wave as well as vEMG. Here, we propose an event-synchronous adaptive digital filter for the suppression of stimulation artifact and M-wave in this application. The proposed method requires a simple experimental setup that does not require extra hardware connections to obtain the reference signals of adaptive digital filter. For evaluating the efficiency of this proposed method, the filter was tested and compared with a least square (LS) algorithm using previously measured data. We conclude that the cancellation of both primary and residual stimulation artifacts is enhanced with an event-synchronous adaptive digital filter and shows promise for clinical application to rehabilitate paretic limbs. Moreover because this algorithm is far simpler than the LS algorithm, it is portable and ready for real-time application.

• 대한의용생체공학회:의공학회지
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• 제13권1호
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• pp.9-18
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• 1992

This paper describes a quantitative analysis of electromyography (EMG) measured from seven subjects performing four seated dynamic tasks. EMG signals were mom- bored using 15 surface electrodes which were placed on selected trunk and lower extrmity muscles of the right side of the body. Each EMG signal was then processed through rectification, integration, and filtering. Based on the maximum level of the processed EMG, it was found that the trunk and ankle muscles play an important role on the postural control during the seated tasks.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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• pp.55-64
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• 2004

Conventional bipolar surface electromyography(EMG) technique detects only the superimposed electromyographic activity of a large number of motor units due to its low spatial resolution. For the diagnosis of neuromuscular disorder, the information of single MU is required. In this paper, 9 channel array surface electrode system was as designed and MLoG filter was proposed. Also the MCPT(modified convolution processing technique)method was proposed for the improvement of MUAP resolution. For performance evaluation, power spectrum analysis of random data and raw EMG signal comparison of MUAP shape and quantitative estimation of SNR were executed. As a result, the MUAP resolution improvement of 32％ was obtained from the standpoint of the signal-to-noise ratio(SNR).