• 대한의용생체공학회:의공학회지
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• 제13권1호
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• pp.1-8
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• 1992

In the field of prosthesis arm control, the pattern classification of the EMG signal is a required basis process and also the estimation of force from collected EMG data is another necessary duty. But unfortunately, what we've got is not real force but an EMG signal which contains the information of force. This is the reason why we estimate the force from the EMG data. In this paper, when we handle the EMG signal to estimate the force, spatial prewhitening process is applied from which the spatial correlation between the channels are removed. And after the orthogonal transformation which is used in the force estimation process, the transformed signal Is inputed into the probabilistic model for pattern classification. To verify the different results of the multiple channels, SNR(signal to noise ratio) function is introduced.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권2호
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• pp.103-110
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• 2004

This paper proposes a new method on the EMG AR(autoregressive) modeling in pattern recognition for various head motions. The proper electrode placement in applying AR or cepstral coefficients for EMG signature discrimination is investigated. EMG signals are measured for different 10 motions with two electrode arrangements simultaneously. Electrode pairs are located separately on dominant muscles(S-type arrangement), because the bandwidth of signals obtained from S-type placement is wider than that from C-type(closely in the region between muscles). From the result of EMG pattern recognition test, the proposed mIAR(modified integrated mean autoregressive model) technique improves the recognitions rate around 17-21％ compared with other the AR and cepstral methods.

• 한국정보전자통신기술학회논문지
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• 제2권1호
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• pp.17-22
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• 2009

본 연구에서는 근전도의 근피로와 관계된 특징인자인 영교차율 및 저대역에너지, 푸리에변환과 AR모델에 의한 중앙주파수를 추출하여 근피로에 이를 때까지의 변화를 평가해 봄으로써 근피로 정도나 시점까지의 변화 정도를 비교 및 고찰하고자 한다. 측정 대상으로 20대 남녀 각각 3인이 참여하였으며 상완 이두근의 등장성운동으로 소진할 때까지의 근전도를 측정 기록하여 실험하였다.

• 한국정보전자통신기술학회논문지
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• 제3권1호
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• pp.8-12
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• 2010

본 연구에서는 t-test와 ANOVA를 이용하여 근전도의 중앙주파수 추출을 위한 AR모델 차수결정 및 중앙주파수 비교에 관한 연구이다. 근전도의 근피로와 관계된 특징인자인 영교차율 및 저대역에너지, 중앙주파수를 추출하여 근피로에 이를 때까지의 변화를 평가해 봄으로써 근피로 정도나 시점까지의 변화 정도를 비교 및 고찰하였다.

• ETRI Journal
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• 제34권4호
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• pp.536-541
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• 2012

This paper aims to extend the transmission line matrix method with a hybrid symmetrical condensed node (HSCN) to model ferrite media in the time domain. To take into account the anisotropy and dispersive properties of ferrite media, equivalent current sources are incorporated into supplementary stubs of the original HSCN. The scattering matrix of the proposed HSCN is provided, and the validity of this approach is demonstrated for both transversely and longitudinally magnetized ferrites. Agreement is achieved between the results of this approach and those of the theoretical and the finite-difference time-domain method.

• 대한의용생체공학회:의공학회지
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• 제15권3호
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• 대한전기학회논문지
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• 제33권10호
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• pp.381-386
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• 1984

This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.807-812
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• 1995

In this study, comparisons were made among three representative methods for predicting compressive forces on the lumbosacral disc: LP-based model, double LP-based model and EMG-assisted model. Two subjects simulated lifting tasks that are normally performed in the refractories industry. In the refractories lifting tasks, vertical and horizontal distance, and weight of load were varied. To calculate the L5/Sl compressive forces, EMG signals from six trunk muscles were measured and postural data were recorded using the Motion Analysis System. The EMG-assisted model was shown to reflect well all three factors considered here. On the other hand, the compressive forces of the two LP-based models were only significantly affected by weight of load.

• 대한의용생체공학회:의공학회지
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• 제10권1호
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• pp.11-16
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• 1989

This paper describes the AR model of EMG signal during maximum voluntary contraction. By comparing the AR coefficients and the reflection coefficients of the AR model with the median frequency of power spectrum, it is proved that muscle fatigue can be measured by the AR and the reflection coefficients. In the estimation procedure of AR model parameter, the autocorrelation method is superior to the covariance method, and it is determined that the optimal order is six. As the muscle becomes fatigue, the median frequency of power spectrum is declined, and the AR coefficient [$a_1$] and the reflection coefficient [$k_1$] are also decreased. Therefore the muscle fatigue can be measured by the AR parameter.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1990년도 춘계학술대회
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• pp.73-78
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• 1990

In this study, LPC cepstrum coefficients are used as feature vector extracted from AR model of EMG signal, and a reduced-connection network which has reduced connection between nodes is constructed to classify and recognize EMG functional classes. The proposed network reduces learning time and improves system stability. Therefore it is shown that the proposed network is appropriate in recognizing the function of EMG signal.