• Journal of Korean Physical Therapy Science
• /
• v.10 no.1
• /
• pp.83-89
• /
• 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 Korean Institute of Industrial Engineers
• /
• v.19 no.4
• /
• pp.87-96
• /
• 1993

Spectrum analysis of surface electromyogram (FMG) signals is an effective approach to the study of localized muscular fatigue during isometric contraction. Many investigators have con firmed the frequency of the EMG signals being lowered during sustained contaction. In this study, the cyclic loading tasks were performed, and a comparison was made for the median power frequency shift pattern of the EMG signals with the sustained contraction of the same load. The median power frequency shift of the EMG signals for the cyclic loading task was found to be a part of that for the sustained contraction. Based on this result, a new muscle fatigue index was computed by normalizing the duration of the sustained contraction. A fatigue index was obtained as a function of exertion level and the work/rest schedule. With the proposed fatigue index, it is possible to evaluate or predict the degree of muscular fatigue for a physically demanding task.

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

• Korean Journal of Applied Biomechanics
• /
• v.21 no.4
• /
• pp.429-436
• /
• 2011

In this study, we have experimented with 9 players at the national delegate level. Although there were some differences in the average effects of 3 types of one-two straight movements after the application of wheel axle, there were no statistical differences in the case of surface reacting forces, electromyograms, and impact forces. When the right fist was impacted using the one-two straight movements and the wheel axle was applied with 3 segmentations, high impact forces were obtained for the pronation in the following order-72.01 $m/s^2$ (type 2), 70.93 $m/s^2$ (type 3), and 58.19 $m/s^2$ (type 1). Higher values of the surface reacting force were found for type 1 that did not exhibit pronation in the left foot, whereas in the case of the vertical direction of the right foot, type 2 with pronation exhibited higher values and impact forces. In the right electromyogram, high impact forces due to the activation of the muscular electric potential were obtained for lumbar erector (LE) spinae and triceps brachii (TB) with type 1; LE spina, latissimus dosi (LD), and upper trapezius (UT) with type 2; and brachioradialis (BR), UT, and rectus abdominal (RA) with type 3. Due to pronation and complex motions of the 3 pronation segmentations, the efficiency was higher for impacts due to one-two straight movements.

• The Journal of Korean Physical Therapy
• /
• v.24 no.3
• /
• pp.186-190
• /
• 2012

Purpose: The purpose of this study was to investigate the lumbar erector spinea and rectus abdominis activations, according to the different gait velocities in young healthy adults. Methods: We recruited 6 young male and 10 young female (mean age=21.43 years; range 19~23) in this study. We used a wireless surface electromyogram (Telemyo 2400T G2, Noraxon, USA) and a treadmill unit for the experiment. EMG activity from the lumbar erector spinea, and rectus abdominis of the dominant side was record with surface electrodes. On different day, all subjects gaited on 2.7 km/h, 4.5 km/h, and 6.3 km/h of speed in random order. They gaited at the same velocity, three times, on the treadmill unit. To reduce fatigue, sufficient rests were given between the measurements. Results: As the gait speed increased, lumbar erector spinea and rectus abdominis activations were significantly increased (p<0.05). Conclusion: In the current study, we found lumbar erector spinea and rectus abdominis activations were changed, according to the gait velocity. We suggested that rehabilitation intervention should be focused on the exercise velocity for the patients with problem of the trunk control.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.46 no.6
• /
• pp.38-43
• /
• 2009

We provide a method to infer finger flexing motions using a 4-channel surface electromyogram (sEMG). Surface EMGs are harmless to the human body and easily acquired. However, they do not reflect the activity of specific nerves or muscles, unlike invasive EMGs. On the other hand, the non-invasive type is difficult to use for discriminating various motions while using only a small number of electrodes. Surface EMG data in this study were obtained from four electrodes placed around the forearm. The motions were the flexion of the thumb, index, middle, ring, and little linger. One subject was trained with these motions and another left was untrained. The maximum likelihood estimation was used to infer the finger motion. Experimental results have showed that this method could be useful for recognizing finger motions. The average accuracy was as high as 95%.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.1
• /
• pp.49-55
• /
• 2002

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of the exoskeltal robot system using multiple fuzzy-neuro controllers based on biological signals that reflect the human subject's intention. Skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been used as input information of the controller. Since the activation level of working muscles tends to vary in accordance with the flexion angle of elbow, multiple fuzzy-neuro controllers are applied in the proposed method. The multiple fuzzy-neuro controllers are moderately switched in accordance with the elbow flexion angle. Because of the adaptation ability of the fuzzy-neuro controllers, the exoskeletal robot is flexible enough to deal with biological signal such as EMG. The experimental results show the effectiveness of the proposed controller.

• The korean journal of orthodontics
• /
• v.22 no.3 s.38
• /
• pp.617-626
• /
• 1992

This study was conducted for the assessment of the usefulness of masseteric silent period on electromyogram as a diagnostic method for temporomandibular disorder. Of students and dentists in Dental College of Yonsei University and patients, 36 experimental subjects with symptoms such as clicking bound, pain in the temporomandibular joint area and limitation of jaw movement, and 33 control subjects without such symptoms were selected for this study. On each subject electromyographic masseter muscle silent period followed by mention tap was recorded with surface electrodes and analysed with computerized system. The following results were obtained: 1. The mean silent period was $36.97{\pm}9.23$ msec in experimental group, and $25.62{\pm}5.24$ msec in control group respectively. 2. There were no statistically significant differences in silent period between male and female in either experimental and control group. 3. Silent periods in experimental group were more prolonged than those of control group. (P < 0.01) Taken all together, electromyographic masseter muscle silent period may be useful for diagnosis and evaluation of temporomandibular disorder.

• Journal of the Ergonomics Society of Korea
• /
• v.21 no.2
• /
• pp.25-33
• /
• 2002

The purpose of study is to investigate the relationship between the trunk muscle fatigue and recovery time during repetitive extension by using a surface electromyogram(EMG). Ten healthy subjects particioated in a simulated lifting task with five levels of recovery time and three levels of sub-maximal contraction. EMG signals of the L1(Lumbar 1st Vertebrae) and L3(Lumbar 3rd Vertebrae) level of the erector spinae muscle were recorded. and analyzed in terms of MPF(mean power frequency) parameter to quantify the level of muscle fatigue. It was found that MPF significantly (p<0.05) decreased during repetitive extension task at 50% and 75% sub-maximal contractions. Then it took minutes for the trunk muscle to recover from fatigue during 50% sub-maximal contraction. and it took five minutes during 75% sub-maximal contraction. and it took five minutes during 75% sub-maximal contraction. The recovery time estimated by the maximum force needs to be re-evaluated for the trunk muscle to fully recover from fatigue. In conclusion. the work/rest cycle needs to be studied based upon the information of muscle fatigue in order to prevent workers from musculoskeletal injuries during repetitive lifting task.

• The Journal of Korea Robotics Society
• /
• v.15 no.1
• /
• pp.62-69
• /
• 2020

This paper proposes a pattern recognition and classification algorithm based on a circular structure that can reflect the characteristics of the sEMG (surface electromyogram) signal measured in the arm without putting the placement limitation of electrodes. In order to recognize the same pattern at all times despite the electrode locations, the data acquisition of the circular structure is proposed so that all sEMG channels can be connected to one another. For the performance verification of the sEMG pattern recognition and classification using the developed algorithm, several experiments are conducted. First, although there are no differences in the sEMG signals themselves, the similar patterns are much better identified in the case of the circular structure algorithm than that of conventional linear ones. Second, a comparative analysis is shown with the supervised learning schemes such as MLP, CNN, and LSTM. In the results, the classification recognition accuracy of the circular structure is above 98% in all postures. It is much higher than the results obtained when the linear structure is used. The recognition difference between the circular and linear structures was the biggest with about 4% when the MLP network was used.