• Title/Summary/Keyword: EMG Signals

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근전도에 기반한 근력 추정 (EMG-based Prediction of Muscle Forces)

  • 추준욱;홍정화;김신기;문무성;이진희
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2002년도 추계학술대회 논문집
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    • pp.1062-1065
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    • 2002
  • We have evaluated the ability of a time-delayed artificial neural network (TDANN) to predict muscle forces using only eletromyographic(EMG) signals. To achieve this goal, tendon forces and EMG signals were measured simultaneously in the gastrocnemius muscle of a dog while walking on a motor-driven treadmill. Direct measurements of tendon forces were performed using an implantable force transducer and EMG signals were recorded using surface electrodes. Under dynamic conditions, the relationship between muscle force and EMG signal is nonlinear and time-dependent. Thus, we adopted EMG amplitude estimation with adaptive smoothing window length. This approach improved the prediction ability of muscle force in the TDANN training. The experimental results indicated that dynamic tendon forces from EMG signals could be predicted using the TDANN, in vivo.

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재활 로봇 팔 제어를 위한 근전도 신호의 잡음제거에 관한 연구 (Noise Rejection of EMG Signals for the Control of Rehabilitation Robotic Am System)

  • 오승환;백승은;나승유;이희영
    • 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.

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등척성 일정 자의 수축 시에 기록한 표면근전도 신호에 대한 근전도 진폭 추정기의 정량적 분석 (Quantitative Analysis of EMG Amplitude Estimator for Surface EMG Signal Recorded during Isometric Constant Voluntary Contraction)

  • 이진
    • 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.

표면근전도 신호의 정상성 검사를 위한 Run-검증과 RA-검증의 정확도 분석 (An Accuracy Analysis of Run-test and RA(Reverse Arrangement)-test for Assessing Surface EMG Signal Stationarity)

  • 이진
    • 전기학회논문지
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    • 제63권2호
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    • pp.291-296
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    • 2014
  • Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of weak stationarity. The purpose of this study is to analyze the accuracy of the Run-test, modified Run-test, RA(reverse arrangement)-test, and modified RA-test for assessing surface EMG signal stationarity. Six stationary and three non-stationary signals were simulated by using sine wave, AR(autoregressive) modeling, and real surface EMG. The simulated signals were tested for stationarity using nine different methods of Run-test and RA-test. The results showed that the modified Run-test method2 (mRT2) classified exactly the surface EMG signals by stationarity with 100% accuracy. This finding indicates that the mRT2 may be the best way for assessing stationarity in surface EMG signals.

HMM-Based Automatic Speech Recognition using EMG Signal

  • Lee Ki-Seung
    • 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.

Walking Motion Detection via Classification of EMG Signals

  • Park, H.L.;H.J. Byun;W.G. Song;J.W. Son;J.T Lim
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.84.4-84
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    • 2001
  • In this paper, we present a method to classify electromyogram (EMG) signals which are utilized to be control signals for patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for dierent walking motions are classied via adequate filtering, real EMG signal extraction, AR-modeling, and modified self-organizing feature map (MSOFM). More efficient signal processing is done via a data-reducing extraction algorithm. Moreover, MSOFM classifies and determines the classified results are presented for validation.

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경추 회전제한 검사 결과에 따른 근전도 신호 변화: 증례보고 (Study on the EMG Signal Changes Depending on the Results of Restricted Cervical Rotation Test: Case Series Report)

  • 최광호;이소민;정의민;권오상;이영준;정지연
    • 턱관절균형의학회지
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    • 제6권1호
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    • pp.1-4
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    • 2016
  • FCST의 턱관절 불균형 진단은 검사자 및 환자의 주관에 의존하여 이루어지기 때문에 객관적인 진단 방법에 대한 고찰이 필요하다. 본 증례에서는 FCST 진단 방법 중 경추회전제한 검사에 대한 객관적인 검증 방법으로 표면 근전도 측정이 가능성이 있음을 관찰하였다.

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표면 근전도 신호 피이크 검출을 위한 디지털 분수 차수 저역통과 미분기 (Digital Fractional Order Low-pass Differentiators for Detecting Peaks of Surface EMG Signal)

  • 이진;김성환
    • 전기학회논문지
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    • 제62권7호
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    • pp.1014-1019
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    • 2013
  • Signal processing techniques based on fractional order calculus have been successfully applied in analyzing heavy-tailed non-Gaussian signals. It was found that the surface EMG signals from the muscles having nuero-muscular disease are best modeled by using the heavy-tailed non-gaussian random processes. In this regard, this paper describes an application of digital fractional order lowpass differentiators(FOLPD, weighted FOLPD) based on the fractional order calculus in detecting peaks of surface EMG signal. The performances of the FOLPD and WFOLPD are analyzed based on different filter length and varying MUAP wave shape from recorded and simulated surface EMG signals. As a results, the WFOLPD showed better SNR improving factors than the existing WLPD and to be more robust under the various surface EMG signals.

표면근전도 신호의 정상성 검사를 위한 수정된 Run-검증과 RA-검증에 최적인 신호분할 길이 (Optimal Signal Segment Length for Modified Run-test and RA(reverse arrangement)-test for Assessing Surface EMG Signal Stationarity)

  • 이진
    • 전기학회논문지
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    • 제63권8호
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    • pp.1128-1133
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    • 2014
  • Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of the weak stationarity. The purpose of this study is to find optimal segment length of surface EMG signal for assessing stationarity with the modified Run-test and RA-test. Ten stationary surface EMG signals were simulated by AR(autoregressive) modeling, and ten real surface EMG signals were recorded from biceps brachii muscle and then modified to have non-stationary structures. In condition of varying segment length from 20ms to 100ms, stationarity of the signals was tested by using six different methods of modified Run-test and RA-test. The results indicate that the optimal segment length for the surface EMG is 30ms~35ms, and the best way for assessing surface EMG signal stationarity is the modified Run-test (Run2) method using this optimal length.

표면 근전도 신호 해석에 의한 내부 근육 근전도 신호의 추정 (Intramuscular EMG signal estimation using surface EMG signal analysis)

  • 왕문성;변윤식;박상희
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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    • pp.641-642
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    • 1986
  • We present a method for the estimation of intramuscular electromyographic(EMG) signals from the given surface EMG signals. This method is based on representing the surface EMG signal as an autoregressive(AR) time model with a delayed intramuscular EMG signal as an input. The parameters of the time series model that transforms the intramuscular signal to the surface signal are identified. The identified model is then used in estimating the intramuscular signal from the surface signal.

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