• Journal of the Korean Academy of Clinical Electrophysiology
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• v.5 no.2
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• pp.61-72
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• 2007

INTRODUCTION: Local heat and cold application has been frequently used as means of muscle relaxation and blood circulation or reinforcing muscle strength, relaxing muscle tension in clinical situation. In particular, it has been known that long-term heat and cold application for relaxing muscle tension inhibits muscle spasticity or tension. But, it has been rarely reported that what influences of heat and cold application on activation of muscle action potential. Therefore, this study aims to analyze surface temperature and electromyography activities according to the heat and cold application. METHODE: Subjects of this research were 10 normal men and women (5 men, 5 women). Hot pack and cold pack was applied to vastus medialis muscle of thigh and rectus femoris muscle for 20 min. Surface temperature of vastus medialis muscle and rectus femoris muscle was measured, knee joint of subjects was in $45^{\circ}$ flexion, sitting on a chair, maximal isometric contraction was induced, surface electromyography (sEMG) signals were collected and root mean square (RMS) and median frequency (MOF) were analyzed. All measurements were conducted before and immediately after experiment, 10 min., 20 min. and 30 min. after experiment. Data were analyzed with SPSS 12.0 program, comparison of changes in superficial temperature and sEMG signals through repeated measurement was conducted with repeated measures ANOVA and significance level $\alpha$ was 0.05. RESULTS: Changes of surface temperature of vastus medialis muscle according to cold application were radically decreased immediately after application, but it was recovered after 30 min. of application and it showed significant difference (F4. 36=72.216, P<0.001). Surface temperature of rectus femoris also showed radical decrease immediately after application, but it was recovered after 30 min. of application and showed significant difference (F4. 36=88.930, P<0.001). Changes of surface temperature of vastus medialis muscle according to heat application were radically increased immediately after application, but it was recovered after 30 min. of application and it showed significant difference (F4. 36=27.267, P<0.001). Surface temperature of rectus femoris also showed radical decrease immediately after application, but it was recovered after 30 min. of application and showed significant difference (F4. 36=19.774, P<0.001). Changes of sEMG by heat and cold application were no statistical difference. Surface temperature of skeletal muscle after heat and cold application showed significant change for 30 min., but it was found that increase or decrease of surface temperature had not great influence on sEMG activities.

• Journal of Biosystems Engineering
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• v.34 no.2
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• pp.127-132
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• 2009

In the working population, muscle fatigue and musculoskeletal discomfort are common, which, in the case of insufficient recovery may lead to musculoskeletal pain. Workers suffering from musculoskeletal pains need to be rehabilitated for recovery. Isokinetic testing has been used in physical strengthening, rehabilitation and post-operative orthopedic surgery. Frequency analysis of electromyography (EMG) signals using the mean frequency (MNF) has been widely used to characterize muscle fatigue. During isokinetic contractions, EMG signals present strong nonstationarities. Hilbert-Haung transform (HHT) and autoregressive (AR) model have been known more suitable than Fourier or wavelet transform for nonstationary signals. Moreover, several analyses have been performed within each active phase during isokinetic contractions. Thus, the aims of this study were i) to determine which one was better suitable for the analysis of MNF between HHT and AR model during repetitive maximum isokinetic extensions and ii) to investigate whether the analysis could be repeated for sequential fixed epoch lengths. Seven healthy volunteers (five males and two females) performed isokinetic knee extensions at $60^{\circ}/s$ and $240^{\circ}/s$ until 50% of the maximum peak torque was reached. Surface EMG signals were recorded from the rectus femoris of the right thigh. An algorithm detecting the onset and offset of EMG signals was applied to extract each active phase of the muscle. Following the results, slopes from the least-square error linear regression of MNF values showed that muscle fatigue of all subjects occurred. The AR model is better suited than HHT for estimating MNF from nonstationary EMG signals during isokinetic knee extensions. Moreover, the linear regression can be extracted from MNF values calculated by sequential fixed epoch lengths (p> 0.0I).

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.143-150
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• 2016

In this paper, we propose Korean monophthong recognition method optimizing muscle mixing based on facial surface EMG signals. We observed that EMG signal patterns and muscle activity may vary according to Korean monophthong pronunciation. We use RMS, VAR, MMAV1, MMAV2 which were shown high recognition accuracy in previous study and Cepstral Coefficients as feature extraction algorithm. And we classify Korean monophthong by QDA(Quadratic Discriminant Analysis) and HMM(Hidden Markov Model). Muscle mixing optimized using input data in training phase, optimized result is applied in recognition phase. Then New data are input, finally Korean monophthong are recognized. Experimental results show that the average recognition accuracy is 85.7% in QDA, 75.1% in HMM.

• Korean Journal of Applied Biomechanics
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• v.17 no.2
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• pp.197-205
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• 2007

The purpose of this study is to analyze the muscle activations and Ground Reaction Force(GRF) in university judo players, and provide the guide of training in Judo. Using surface electrode electromyography(EMG), we evaluated muscle activity in 5 university judo players during the Judo Uke Movements. Surface electrodes were used to record the level of muscle activity in the Tibialis Anterior, Rectus Femoris, Elector Spinae, Gluteus Maximus, Gastrocnemius muscles during the Uke. These signals were compared with %RVC(Reference voluntary contraction) which was normalized by IEMG(Integrated EMG). The Uke was divided into four phases : Kuzushi-1, Kuzushi-2, Tsukuri, Kake. The results can be summarized as follows: 1. The effective Uke Movements needs to short time in the Kake Phase 2. The Analysis of Electromyography of Uke Movements in Supporting Leg; TA(Tibialis anterior) had Higher %RVC in the Kuzushi Phase, RF(Rectus Femoris) had Higher %RVC in the Tsukuri Phase, GM(Gluteus Maximus) had Higher %RVC in the Kake Phase 3. The ground reaction force for Z(vertical) direction was showed increase tendency in Kuzushi phase, Tsukuri phase and decrease tendency in Kake phase.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.6
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• pp.663-669
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• 2011

This paper examines methods to estimate torque and angle in shoulder flexion from surface electromyography(sEMG) signals for intuitive and delicate control of robotic assistance device. Five muscles on the upper arm, three for shoulder flexion and two for shoulder extension, were used to offer favorable sEMG recording conditions in the estimation. The methods tested were the mean absolute value (MAV) with linear regression and the artificial neural network (ANN) method. An optimal condition was sought by varying combination of muscles used and the parameters in each method. The estimation performance was evaluated using the correlation values and normalized root mean square error values. In addition, we discussed their possible use as an estimation of motion intent of a user or as a command input in a physical human-machine interaction system.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.418-421
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• 2009

This paper presents a human-machine interaction based on a realtime upper limb motion prediction method using surface electromyography (sEMG). The motions were predicted using an artificial neural network algorithm and sEMG signals which are acquired from five muscles, and then a manipulator was controlled to follow after the predicted motions. Upper limb motions were restricted to 2D vertical plane with the contact condition between a user and an end-effector of manipulator. In order to demonstrate the feasibility of the proposed method, experiments using developed method and using a goniometer were performed. The results showed that the proposed real-time motion prediction method can be implemented a human-machine interaction system.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.67-73
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• 2012

In this paper, Artificial Neural Network(ANN) based motion classification algorithm is proposed to classify wrist motions using surface electromyograms(sEMG). surface EMGs are obtained from two electrodes placed on the flexor carpi ulnaris muscle and extensor carpi ulnaris muscle of 26 subjects under no strain condition during wrist motions and used to recognize wrist motions such as up, down, left, right, and rest. Feature is extracted from obtained EMG signals in time domain for fast processing and used to classify wrist motions using ANN. DAMV, DASDV, MAV, and RMS were used as features and accuracies of motion classification based on ANN were 98.03% for DAMV, 97.97% for DASDV, 96.95% for MAV, 96.82% for RMS.

• Korean Journal of Applied Biomechanics
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• v.15 no.1
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• pp.197-206
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• 2005

The purpose of this study was to quantify the maximum EMG levels and determine if there are differences in these EMG levels with respect to different knee flexion angles. Eight university students with no known musculoskeletal disorders were recruited as the participants. The maximum voluntary isometric knee extensions and flexions were taken from each participant sat on the isokinetic exercise machine (Cybex 340) at five different knee flexion angles ($10^{\circ}$, $30^{\circ}$, $50^{\circ}$, $70^{\circ}$, $90^{\circ}$) After surface electrodes were attached to rectus femoris, vastus medialis, vastus laterlis, biceps femoris, and semitendinosus, maximum EMG levels at five different knee flexion angles were measured. The results showed that there was no significant difference in maximum EMG levels among five different knee flexion angles. Although there was no significant difference in EMG levels and were some variations among different knee flexion angles, the EMG signals of quadriceps in extension and biceps femoris in flexion were the greatest at $30^{\circ}$. It seems that different joint angles or relative locations of body segments might affect the magnitude of EMG levels. Because the maximum EMG levels could change with a different knee flexion angle, an attempt should be made to more accurately measure these values. If then, %MVIC measure provides more reliable data and is most appropriate for EMG normalization.

• Speech Sciences
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• v.11 no.1
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• pp.55-64
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• 2004

This study was to determine the effects of a massage and oro-facial exercise program on spastic dysarthric patients' lip muscle function using an electromyogram (EMG). Three subjects with Spastic Dysarthria participated in the study. The surface electrodes were positioned on the Levator Labii Superior Muscle (LLSM), Depressor Labii Inferior Muscle (DLIM), and Orbicularis Oris Muscle (OOM). To examine lip muscle function improvement, the EMG signals were analyzed in terms of RMS (Root Mean Square) values and Median Frequency. In addition, the diadochokinetic movements and the rate of sentence reading were measured. The results revealed that the RMS values were decreased and the Median Frequency moved to a high frequency area. Diadochokinesis and sentence reading rates were improved.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.3
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• pp.335-342
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• 1988

In this paper, we proposed a new algorithm for EMG low frequency analysis. Through the power spectrum analysis of Gaussian's, Gamma's and Erlang's PDF(probability density function) based on the proposed algorithm, the proper PDF of IPI (inter pulse interval) representing the firing rate of muscle was suggested. In order to verify the proposed algorithm EMG signals of masseter and biceps muscle were detected by surface electrode and its power spectrum analysis was performed. The experimental results are compared with the computer simulaiton. As a result, the masseter muscle's IPI was fitted by Gamma PDF, having a 10Hz fundamental frequency including n(1+\ulcornerfp high harmnic frequency on 10% MVC(maximum voluntary contaraction). And the biceps muscle's IPI was fitted by Gaussian PDF, also it have a 14Hz fundamental frequency.