• Journal of Korean Physical Therapy Science
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• v.10 no.1
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• pp.83-89
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• 2003

An electromyogram (EMG) using surface electrodes is one of the indirect tests most frequently used to ascertain muscle fatigue. An EMG can be used in two ways. The first technique determines the root mean square (RMS), which reflects the amplitude of the EMG signal. The second technique determines the median and mean power frequencies through EMG power spectrum analysis. The purpose of this article is for determine the correlation between work and percent root mean square(%RMS) and between work and MDF of EMG based on muscle contractions. It is used the %RMS, which reflects the amplitude of the EMG signal For MDF, it is used the frequency power spectrum analysis method, which involves the fast Fourier transformation (FFT) of the original Signals.

• Journal of the HCI Society of Korea
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• v.10 no.2
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• pp.21-26
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• 2015

NUI (Natural User Interface) system interprets the user's natural movement or the signals from human body to the machine. sEMG (surface electromyogram) can be observed when there is any effort in muscle even without actual movement, which is impossible with camera and accelerometer based NUI system. In sEMG based movement recognition system, the minimal number of electrodes is preferred to minimize the inconvenience. We analyzed the decrease in recognition accuracy as decreasing the number of electrodes. For the four kinds of movement intention without movement, extension (up), flexion (down), abduction (right), and adduction (left), the multilayer perceptron classifier was used with the features of RMS (Root Mean Square) from sEMG. The classification accuracy was 91.9% in four channels, 87.0% in three channels, and 78.9% in two channels. To increase the accuracy in two channels of sEMG, RMSs from previous time epoch (50-200 ms) were used in addition. With the RMSs from 150 ms, the accuracy was increased from 78.9% to 83.6%. The decrease in accuracy with minimal number of electrodes could be compensated partly by utilizing more features in previous RMSs.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.357-364
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• 2008

This study is to find training effect on EEG(Electroencephalography) and EMG(electromyogram) evoked by repetitive movement of a hand. Five university students participated in this study and were asked to perform repetitive movement of right hand for 5 seconds with rest for 10 seconds. They repeated the movement for 48 minutes and for 5 days. EEG and EMG were measured according to every movement. Coherence between EEG and EMG and power spectrum of EEG were analyzed and were tried to observe their changes within a day and between days of the repetitive movement. Training effect according the time of the movement was significantly found in mu and beta frequencies in EEG. However, training effect was not significant between the days of the movement and also, not in coherence between EEG and EMG.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.223-229
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• 2019

The number of knee-related disease patients and knee joint surgeries is steadily increasing every year, and for knee rehabilitation training for these knee joint patients, it is necessary to strengthen the muscle of vastus medialis and quadriceps femoris. However, because of the cost and time-consuming difficulties of receiving regular hospital treatment in the course of knee rehabilitation, we developed knee exoskeleton using rapid prototype for knee rehabilitation with feedback from the electromyogram (EMG) and inertia motion unit (IMU) sensor. The modules was built on the basis of EMG and an IMU sensor applied complementary filter, measuring muscle activity in the vastus medialis and the range of joint operation of the knee, and then performing the game based on this measurement. The IMU sensor performed up to 97.2% accuracy in experiments with ten subjects. The functional game contents consisted of an exergaming platform based on EMG and IMU for the real-time monitoring and performance assessment of personalized isometric and isotonic exercises. This study combined EMG and IMU-based functional game with knee rehabilitation training to enable voluntary rehabilitation training by providing immediate feedback to patients through biometric information, thereby enhancing muscle strength efficiency of rehabilitation.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.11
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• pp.1051-1058
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• 2014

In this study, we investigated the improvement effect of obesity by treatment with a developed low frequency electrical stimulation system. Thirty female in their 20's as an experiment subjects divided 3 groups(control, commercialized device, developed device) were treated with electrical stimulation on abdomen for 4 weeks. The body weight, body mass index(BMI), waist-hip ratio(WHR), muscle strength, muscle(transverse abdominis(TrA), internal obliquus abdominis(IO), external obliquus abdominis(EO)), fat thickness and abdominal surface temperature were measured by electromyogram(EMG), ultrasound and digital infrared thermal image(DITI). In the result, the body weight and BMI were decreased. Subcutaneous abdominal fat were significantly reduced after 4 weeks. The muscle strength and TrA muscle thickness was increased 13.2%(p<0.05), and 35.5%, respectively. The fat thickness showed decrease in abdomen (p<0.05). Infrared measurement on abdominal surface temperature as a parameter of improvement in blood circulation was significantly increased(p<0.05). Therefore, the low frequency stimulation showed positive effects on parameters of the obesity improvement.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• PNF and Movement
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• v.10 no.4
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• pp.25-31
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• 2012

Purpose : The purpose of present study was to investigate the effects of proprioceptive neuromuscular facilitation (PNF) lifting on contralateral leg muscle activities in a seated position. Methods : Twenty healthy subjects were recruited for this study. Lifting was performed from each of the three position. An surface electromyogram (EMG) was used to record the EMG activities from vastus medialis (VM), biceps femoris (BF), tibialis anterior (TA), and gastrocnemius medialis (GM) in contralateral leg muscle. The data were analyzed using a repeated measures of one-way analysis of variance (ANOVA) with post-hoc Bonferroni's correction to determine the statistical significance. Results : The results of this study were summarized as follows: In comparison to the start position, percentage maximal voluntary isometric contraction (%MVIC) values of the VM, TA and GM demonstrated a significantly higher activities in the end position(p<.05). Conclusion : The result shows that contralateral leg muscles activities significantly more increase in the end position when PNF lifting was applied. Therefore, this study will be used to prove effect of indirect approach for the stability and strengthening in patients with leg impairments.

• Journal of Biomedical Engineering Research
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• v.27 no.3
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.12
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• pp.1121-1127
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• 2013

This study deals with experimental studies on electromyogram (EMG) measurements and functional electrical stimulation (FES) for the rehabilitation of a shoulder-joint. Based on the structure, motion, and main functions of the musculoskeletal system in a shoulder-joint, the muscles playing a major role for the motion in the sagittal plane were selected for the experiment. First, the surface electromyogram of the main muscles was measured according to the joint angle. The results showed that the change in the surface EMG was linearly proportional to the change in the joint angle. Second, the joint angle was measured during FES at shoulder muscles. The results showed that the joint angle increased as the FES current increased in a certain range of FES. It was confirmed that the willingness of muscles to move could be detected by measuring EMG and that the generation of muscle tension could be assisted by FES for active rehabilitation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.10
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• pp.934-939
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• 2011

This paper experimentally deals with the relationship between the ankle electromyogram(EMG) and walking motion in order to activate the ankle joint of a walking-assistance robot for rehabilitation. Based on the anatomical structure and motion pattern of an ankle joint, major muscles were selected for EMG measurements. Surface EMG signals were monitored for several human bodies at various stride distances and stride frequencies. Root-mean-squared magnitude of EMG signals were related with the walking conditions. It appeared that the magnitude of the ankle EMG signal was linearly proportional to the stride distance and stride frequency, and thus to the walking speed.