• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.59-62
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• 1997

In this paper, we used Wavelet Transform to analyze EMG signals. Wavelet transform has an advantage of dividing the nonstationary signals into the high frequency and low frequency band effectively. For determining the characterized value of EMG signals, it was wavelet-transformed, absoluted, and integral-calculated. As the result, we acquired characterized value of each signals, and acknowledged the differences among them. It was concluded that the results of this study using wavelet transform could be used to powerful tool or analysis of EMG signals.

• Journal of Engineering Education Research
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• v.19 no.1
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• pp.31-36
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• 2016

These days, ICT-related products are pouring out due to development of mobile technology and increase of smart phones. Among the ICT-related products, wearable devices are being spotlighted with the advent of hyper-connected society. In this paper, a body-attached type wearable device using EMG(electromyography) sensors is studied. The research field of EMG sensors is divided into two parts. One is medical area and another is control device area. This study corresponds to the latter that is a method of transmitting user's manipulation intention to robots, games or computers through the measurement of EMG. We used commercial device MYO developed by Thalmic Labs in Canada and matched up EMG of arm muscles with gesture controller. In the experiment part, first of all, various arm motions for controlling devices are defined. Finally, we drew several distinguishing kinds of motions through analysis of the EMG signals and substituted a joystick with the motions.

• The Journal of Korean Physical Therapy
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• v.25 no.6
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• pp.411-416
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• 2013

Purpose: The purpose of the present study was to determine the effects of activation of gluteus maximus (Gmax) and abdominal muscle using EMG biofeedback on lumbosacral and tibiocalcaneal angles in standing position. Methods: Fourteen healthy subjects with normal feet participated in the present study. Electromyographic (EMG) biofeedback using visual cue was used to activate the external oblique (EO) and Gmax. The lumbosacral and tibiocalcalcaneal angles were measured by electronic goniometers. All the subjects were instructed to activate the Gmax and EO monitoring increasing amounts of the muscle activities in each muscle. The lumbosacral and tibiocalcaneal angles were collected in three trials during resting and activation of each muscle using EMG biofeedback in standing position. The mean value of three trials was used in the data analysis. A paired-t test was used to compare the lumbosacral and tibiocalcaneal angles between resting and activation of the Gmax and EO using EMG biofeedback. Results: The lumbosacral and tibiocalcaneal angles were significantly less in the resting compared to activation using EMG biofeedback (p<0.05). Conclusion: The activaition of Gmax and abdominal muscles using EMG biofeedback play role to control the pronation of subtalar joint during the weight-bearing.

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.755-765
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• 2016

Recently, interest in monitoring health and sports is growing because of the emphasis on wellness, which is accelerating the development and commercialization of smart clothing for biosignal monitoring. In addition to exerciseeffect monitoring clothing that tracks heart rate and respiration, recently developed clothing makes it possible to monitor muscle balance using electromyogram (EMG). The electrode for EMG have to attached to an accurate location in order to obtain high-quality signals in surface EMG measurement. Therefore, this study develops monitoring clothing suitable for different types of human bodies and aims to extract suitable range of EMG according to movements in order to develop self-fitness monitoring clothing based on EMG measurement. This study identified and attached electrodes on six upper muscles and two lower muscles of ten males in their 20s. After selecting six main motions that create a load on muscles, the 8-ch wireless EMG system was used to measure amplitude value, noise, SNR and SNR (dB) in each part and statistical analysis was conducted using SPSS 20.0. As a result, the suitable range for EMG measurement to apply to clothing was identified as four parts in musculus pectoralis major; three parts in muscle rectus abdominis, two parts each in shoulder muscles, backbone erector, biceps brachii, triceps brachii, and musculus biceps femoris; and four part in quadriceps muscle of thigh. This was depicted diagrammatically on clothing, and the EMG-monitoring sensing locations were presented for development of self-fitness monitoring.

• Journal of the Korean Society of Safety
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• v.10 no.4
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• pp.103-108
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• 1995

This study was performed to investigate a relationship between a biomechanical analysis of compressive force at L5/S1 and electromyographic analysis of erector spinae muscle during lifting task. In the experiment, isometric contractions at 25, 50, 75, 100%MVC for short duration and sustained isometric contractions at 50%MVC were performed. For muscle recruitment patten and compressive force analysis, rectified EMG amplitudes analysis and computerized biomechanical analysis were used. To achieve data, angles of neck, shoulder, elbow, wrist, hip, knee, ankle and length of body segments were measured. Results shows that trends of initial EMG rectified amplitude were similar to those of biomechanical calculation value and for sustained isometric contraction at 50%MVC EMG rectified amplitude of erector spinae muscle after 40seconds was increased up to level of 75%MVC. Based on the results of this study, biomechanical analysis should be supplemented considering muscle fatigue, and it is also suggested that work-rest cycle critera and the evaluation of back-pain injuries should include muscle fatigue.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.643-644
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• 2008

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2895-2898
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• 2003

In this study, our primary goal is to classify the EMG(electromyographic) signals including the specific patterns related to hand motions in an arm. To do this, the EMG recognition method based on the LP coefficients and delay between multi-channels obtained by cross-correlation function is presented. The study consists of three functional parts, which are pans for obtaining the EMG signals from am muscle, analyzing LP coefficients and delay parameter obtained by cross-correlation function, and recognizing specific patterns. In the experiment, the result of the present method is compared with the results of the conventional methods. We expect that the results of this study is very effective in the mobile computer and wearable computer environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.115-115
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• 2000

A gait pattern classification method using electromyography(EMG) signal is presented. The gait pattern with four stages such as stance, heel-off, swing and heel-strike is analyzed and classified using feature parameters such as zero-crossing, integral absolute value and variance of the EMG signal. The EMG signal from Tibialis Anterior and Gastrocnemius muscles was obtained using the surface electrodes, and low-pass filtered at 10kHz. The filtered analog signal was sampled at every 0.5msec and converted to digital signal with 12-bit resolution. The obtained data is analyzed and classified in terms of feature parameters. Analysis results are given to show that the gait patterns classified by the proposed method are feasible.

• Journal of Korean Physical Therapy Science
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• v.18 no.3
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• pp.63-69
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• 2011

Purpose : The purpose of study is activation of lumbar multifidus muscle by needle EMG during shoulder flexion in chronic low back pain patients. The subject were consisted of 10 women patients with chronic low back pain and healthy asymtomatic subject 10 women. Methods : 10 women patients with chronic low back pain and healthy asymptomatic subject 10 women is voluntary participated for the research. Subjects were positioned in standing. The needle EMG were measured activation of multifidus. Needle electrode was used to 28 gauge. The shoulder flexion movement used to activate the multifidus was then measured. Results : Results of the analysis showed that asymptomatic subjects had significantly larger multifidus muscle activation compared with CLBP subjects during shoulder flexion. Conclusion : This study will be used as multifidus measurement method of patient with chronic LBP. The multifidus muscle in chronic LBP patient clinical significance. Most of chronic LBP patients have multifidus contraction pattern. Therefore chronic LBP patients necessary multifidus activation measurement with needle EMG.

• Journal of Biomedical Engineering Research
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• v.33 no.2
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• pp.65-71
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• 2012

In this paper, the Gaussian Mixture Model(GMM) which is very robust modeling for pattern classification is proposed to classify wrist motions using surface electromyograms(EMG). EMG is widely used to recognize wrist motions such as up, down, left, right, rest, and is obtained from two electrodes placed on the flexor carpi ulnaris and extensor carpi ulnaris of 15 subjects under no strain condition during wrist motions. Also, EMG-based feature is derived from extracted EMG signals in time domain for fast processing. The estimated features based in difference absolute mean value(DAMV) are used for motion classification through GMM. The performance of our approach is evaluated by recognition rates and it is found that the proposed GMM-based method yields better results than conventional schemes including k-Nearest Neighbor(k-NN), Quadratic Discriminant Analysis(QDA) and Linear Discriminant Analysis(LDA).