• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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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.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.2
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• pp.37-44
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• 2018

Purpose : The aim of this study is to compare the trunk muscle activities in trunk stabilization on the stable and unstable supporting surfaces using by sEMG. Methods : The subjects of this study include seventeen male. We measured sEMG activities of rectus abdominis and erector spine in subjects during trunk stabilization such as plank exercise, quadruped position, quadruped position with rising hand and foot on the stable and unstable surface. Results : sEMG activities in plank exercise was significantly higher in left rectus abdominis and left erector spine on unstable surface then stable surface (p<.05). sEMG activities of left rectus abdominis and left erector spine in quadruped position was significantly higher in unstable surface than stable surface (p<.05). In comparison with posture, Plank exercise showed a significant difference increase other postures (p<.05). Conclusion : sEMG activities of muscle in trunk stabilization was significantly higher in unstable surface than stable surface and plank exercise. So, we suggest that trunk stabilization on the unstable supporting surface and plank exercise were more effective method than stable surface to improve trunk muscles activities.

• Journal of Oral Medicine and Pain
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• v.46 no.4
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• pp.143-149
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• 2021

Purpose: Oromandibular dystonia is a neurological disorder that affects the jaw and lower face muscles, often resulting in abnormal repetitive movement of the jaw and perioral structures. The purpose of this study was to assess the effectiveness of surface electromyography (EMG) in evaluating the treatment outcome of oromandibular dystonia. Methods: Based on a retrospective review of medical records, we analyzed the data of four patients who received medication or botulinum toxin injection, as well as surface EMG of the jaw muscles before and after treatment. We assessed the patients' clinical characteristics and the results of surface EMG before and after treatment. Results: The case series included one female and three males, and the age range was 65-78 years. Based on the clinical features, two subjects were classified as jaw deviation and the remaining two were as jaw closing. Dystonic patterns revealed by surface EMG varied, including phasic, tonic, and mixed contraction patterns. EMG amplitude after treatment was lower than pre-treatment value in all four subjects, suggesting improved clinical signs and symptoms. One subject who received clonazepam and another who received botulinum toxin injection showed a remarkable reduction in EMG amplitude within a normal range. Conclusions: Surface EMG can be used to effective evaluate treatment outcomes in patients with oromandibular dystonia. It could be considered as an adjunctive diagnostic tool in managing patients with dystonia.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.211-220
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• 2023

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.124-130
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• 2018

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is of high relevance not only in biomechanical studies but also more and more in clinical applications. This paper presents a new approach to estimate surface EMG amplitude by using the mean spike and mean turn amplitude(MSA and MTA) variables. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction and performance of the MSA and MTA variables applied to amplitude estimation of the EMG signals were investigated. To examine the performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that MSA and MTA amplitude estimations with first order whitening filter and 300[ms]-350[ms] moving average window length are optimal and show better performance(mean SNR improvement of 6%-15%) than the most frequently used variables(ARV and RMS).

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.10 no.1
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• pp.24-29
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• 1999

Extrinsic laryngeal muscles are well known to be important for the classical singers. We tried to elucidate any differences in the function of above muscles between trained and untrained singers by non-invasive surface electromyography(EMG). Four trained sopranos and four untrained singers sang vowel /i/ at different pitch(E3, G3, C4, E4, G4, C5, E5, G5, C6). The EMG activities of the suprahyoid, infrahyoid and omohyoid muscles were measured using surface electrodes. In trained singers, infrahyoid muscle activities increased more than those of suprahyoid in most of pitch. To the contrary, in untrained singers, the pattern of EMG activities were variable among each subjects and the EMG activities of suprahyoid muscles were relatively greater than those of infrahyoid.