• Physical Therapy Korea
• /
• v.8 no.3
• /
• pp.11-26
• /
• 2001

In rehabilitation programs involving muscle re-education and endurance exercise, it is necessary to confirm when fatigue occurs. It is also necessary to quantify fatigue, to confirm whether the muscle has been exercised sufficiently. In general, as fatigue occurs, the force-generating ability of the muscle is reduced. If the median frequency (MDF) obtained from electromyogram (EMG) power spectrum is correlated highly with work, then the timing and degree of fatigue may be confirmed. This study examined the relationship between work and MDF obtained from the EMG power spectrum during repetitive isokinetic exercise. Surface EMG signals were collected from biceps brachii and vastus lateralis of 52 normal subjects (26 males, 26 females) at $120^{\circ}/sec$ and $60^{\circ}/sec$ while performing an isokinetic exercise. The exercise was finished at 25% of peak work. MDF data was obtained using a moving fast Fourier transformation (FFT), and random noise was removed using the inverse FFT, then a new MDF data was obtained from the main signal. There was a high correlation between work and MDF during repetitiv isokinetic exercise in the biceps brachii and vastus lateralis of males and the biceps brachii of females (r=.50~.77). However, there was a low correlation between work and MDF in the vastus lateralis of females (r=.06~.19).

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.5
• /
• pp.757-762
• /
• 2012

In this paper, the multi feature extraction algorithm for estimation of wrist movements based on Electromyogram(EMG) is proposed. For the extraction of precise features from the EMG signals, the difference absolute mean value(DAMV), the mean absolute value(MAV), the root mean square(RMS) and the difference absolute standard deviation value(DASDV) to consider amplitude characteristic of EMG signals are used. We figure out a more accurate feature-set by combination of two features out of these, because of multi feature extraction algorithm is more precise than single feature method. Also, for the motion classification based on EMG, the linear discriminant analysis(LDA), the quadratic discriminant analysis(QDA) and k-nearest neighbor(k-NN) are used. We implemented a test targeting twenty adult male to identify the accuracy of EMG pattern classification of wrist movements such as up, down, right, left and rest. As a result of our study, the LDA, QDA and k-NN classification method using feature-set with MAV and DASDV showed respectively 87.59%, 89.06%, 91.75% accuracy.

• Journal of Korean Medicine Rehabilitation
• /
• v.19 no.4
• /
• pp.203-217
• /
• 2009

Objectives : We have evaluated the effects of conservative treatment on two patients who were diagnosed to lumbosacral radiculopathy. Methods : Two patients were diagnosed as lumbosacral radiculopathy through needle electromyoram. We used acupuncture therapy, Cox technique to the patients. We measured visual analog scale(VAS) and needle electromyogram before and after treatment. Results : After treating acupuncture therapy, Cox technique in the cases, We find out that the patients were improved, and changed of needle electromyogram result. Conclusions : These results suggest that Cox thechnique and acupuncture therapy were effective to lumbosacral radiculopathy and reduced the low back pain and the leg myasthenic.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.05a
• /
• pp.953-954
• /
• 2010

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.7 no.2
• /
• pp.69-74
• /
• 2013

In this paper, we propose the pattern classification algorithm of recognizing wrist movements based on electromyogram(EMG) to raise the recognition rate. We consider 30 characteristics of EMG signals wirh the root mean square(RMS) and the difference absolute standard deviation value(DASDV) for the extraction of precise features from EMG signals. To get the groups of each wrist movement, we estimated 2-dimension features. On this basis, we divide each group into two parts with mean to compare and promote the recognition rate of pattern classification effectively. For the motion classification based on EMG, the k-nearest neighbor(k-NN) is used. In this paper, the recognition rate is 92.59% and 0.84% higher than the study before.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.910-916
• /
• 2018

In this paper, we developed a shoulder rehabilitation exercise device and monitoring system to remotely provide rehabilitation system for the ones who need shoulder exercises including the patients with rotator cuff rupture. In order to evaluate the severity of shoulder muscle injury, a total of 4 shoulder rehabilitation exercises ((3) shoulder abduction, (2) shoulder flexion, (3) shoulder abduction with elbow flexion, (4) shoulder extension with elbow flexion) were selected and instructed to be performed with a 3 kg dumbbell for 5 times. For EMG (electromyogram) signal analysis, each subject's maximum voluntary contraction (MVC) was measured. EMG signals reflect the activation level of contracting muscles during dynamic exercises. Six participants' muscle activation levels in posterior deltoid, middle deltoid, upper trapezius, and infraspinatus were measured and compared. The mean power spectrum values in the time and frequency domains were compared between two age-matched groups (20s and 50s). The results showed lower muscle activation in the elderly subjects (n=3) compared to that of the ones in their twenties (n=3).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.478-480
• /
• 2011

As the recent games industry grows slowly, the consumers come to have interests in new types of games which has different types from the conventional games. While the conventional games play with a simple interfaces such as a joystick and buttons, the new games are designed to have acceleration sensors, infrared sensors and video motion detection sensing using several types of sensors and allow users to play more actively. In this paper, we propose a method which uses the electromyogram(EMG) signals in interface.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.60
• /
• pp.37-46
• /
• 2000

A biomechanical model of lower extremity in seated postures was developed to assess muscular activities of lower extremity involved in a variety of foot pedal operations. The model incorporated four rigid body segments with the twenty-four muscles to represent lower extremity This study deals with quasi-static movement to investigate dynamic movement effect in seated foot operation. It is found that optimization method which has been used for modeling the articulated body segments does not predict the forces generated from biarticular muscles and antagonistic muscles reasonably. So, the revised nonlinear optimization scheme was employed to consider the synergistic effects of biarticular muscles and the antagonistic muscle effects from the stabilization of the joint. For the model validation, three male subjects performed the experiments in which EMG activities of the nine lower extremity muscles were measured. Predicted muscle forces were compared with the corresponding EMG amplitudes and it showed no statistical difference. For the selection of optimal seated posture, a physiological meaningful criterion was developed for muscular load sharing developed. For exertion levels, the transition point of type F motor unit of each muscle is inferred by analyzing the electromyogram at the seated postures. Also, for predetermined seated foot operations exertion levels, the recruitment pattern is identified in the continuous exertion, by analyzing the electromyogram changes due to the accumulated muscle fatigue.

• Biomedical Science Letters
• /
• v.24 no.1
• /
• pp.43-49
• /
• 2018

Electrocardiogram (ECG) is a widely used method to diagnose electrical activity of heart. Although it is a reliable and easy method, ECG could be interfered by electrical signals. One of the interfering signals is electromyogram (EMG) that is caused by muscle contraction in any parts of the body except heart. To avoid the EMG noise, an examinee is advised to be relaxed on supine position while measuring ECG. Sometimes, patients who can't put their arms and legs down on bed due to some reasons such as cast on arms or legs necessarily have the EMG noise. But detailed information about how much of the noise could be induced by positional change of arms and legs has not been reported. Here we examined the noise by analyzing ECG data from 14 candidates, 7 males and 7 females. The ECG data was obtained using the standard 12 lead ECG. EMG noise was induced by raising arms and legs at $90^{\circ}$, $60^{\circ}$ or $30^{\circ}$. Because arms are located close to the heart, noise by the raised arms was analyzed toward left or right arm separately. All of the examinees showed similar pattern of the EMG noise. EMG noise by positional change of left or right arm was clearly monitored in different limb leads. Change of leg positions induced the noise that was monitored in aVF of augmented leads and II and III of limb leads. There was a difference in degree of the noise between male and female examinees. In addition to the EMG noise, decrease of PR interval was monitored in particular positional changes, which was prominent in male examinees. These results will enlarge fundamental understanding about EMG noise in ECG.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.3
• /
• pp.28-39
• /
• 2010

In this paper, a new method to estimate MU (motor unit) location in the short head of BIC (biceps brachii) muscle using surface EMG (electromyogram) is proposed. The SMUAP (single motor unit action potential) is generated from a MU located at certain depth from the skin surface. The depth is referred as MU location. For estimating muscle force precisely, the information of the MU location is required. The reference SMUAPs are simulated based on anatomical structure of human muscle, and compared with acquired real EMG signals using 3-channel surface EMG electrode. The proposed method was compared with the results of previous researchers and verified its accuracy by computer simulation. From the simulation result in case of the MU located in 8[mm], the average estimation error of proposed method was 0.01[mm]. But the average estimation error of Roeleveld's method was 2.33[mm] and Akazawa's method was 1.70[mm]. Therefore the proposed method was more accurate than the methods of previous researchers.