• The Journal of Korean Physical Therapy
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• v.27 no.4
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• pp.270-274
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• 2015

Purpose: The purpose of this study was to examine the electromyographic (EMG) activity of the abdominal muscles and to compare the activity ratios of the bilateral rectus abdominis (RA) to oblique abdominal muscles during shoulder abduction in opposite directions with single leg raising (SLR) performed in the supine position on a foam roller. Methods: Fifteen healthy subjects were recruited to the study. Each subject lay on the foam roller and performed left single leg raising with right or left shoulder $90^{\circ}$ abduction (Abd); performed in a random order. Surface EMG recordings of selected abdominal muscles (i.e., the RA, external oblique abdominis [EO], internal oblique abdominis [IO], and transverse abdominis [TrA]) were normalized to maximum voluntary isometric contraction. EO/RA and IO and TrA/RA ratios were determined with surface EMG. Data were analyzed by Independent t-test. The statistical significance level was p<0.05. Results: The results were as follows: (1) the right RA, left EO, and right IO and TrA muscle activities increased significantly at the left SLR with left Abd compared to the left SLR with right Abd (p<0.05); and (2) the ratio of right EO/RA activity increased significantly at the left SLR with right Abd compared to left Abd (p<0.05). Conclusion: These findings suggest that left SLR with left Abd on a foam roller is an appropriate exercise for activation of specific oblique abdominal muscles.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.3
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• pp.224-229
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• 2009

An experimental study was conducted to investigate the effects of turtle neck syndrome, so called, on muscular fatigue and muscle activity. Six subjects (males) participated and performed the prolonged casual computer work in the study. EMG signals from six muscles of the dominant neck-back region were acquired and recorded for 10 seconds at the beginning and the end of three hours computer work. EMG was recorded from six muscles by using a computerized data recording and analysis system. Power spectrum function of EMG was calculated off-line by means of a signal processing software package. Power spectrum functions were smoothed with a moving average filter of 21 points and normalized with respect to the maximal value achieved during the trials. Muscle activity and median frequencies of Sternocleidomastoid(SCM) in turtle neck posture was approximately 51%, which were less than those in normal neck posture. SCM also showed the biggest decrease in median frequency. Results will provide the insight into the neck-back injury mechanism of turtle neck patients. Furthermore, they will be helpful in developing rehabilitation programs for restoring patients' neck-back functions.

• Journal of Korean Physical Therapy Science
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• v.19 no.4
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• pp.1-6
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• 2012

Purpose : The current research examines the muscle activity that happens during scaling practice subject to 20 dental hygienic students with musculoskeletal pain and then propose a basic data according to the working attitude of the Dental Hygienist. Method : The Nordic-style questionnaire is used to define experimental group with musculoskeletal pain and control group. During the scaling the surface EMG device is used to measure the muscle activity of experimental and control group. Study design : The surface EMG is measure RMS(root mean square) of suboccipital muscle, biceps brachii, upper trapezius, and brachioradialis muscle activity. Results : In the experimental group, the RMS of upper trapezius and brachioradialis is increased during scaling practice(p<0.05), but the control group's RMS is not changed(p>0.05). Conclusion : Musculoskeletal pain may contribute to increase muscle activity of neck & arm during scaling practice. In the future we think there is a need to raise the office efficiency by subjecting to dental hyginiest that are in the clinics and performing experiments.

• Journal of Life Science
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• v.20 no.11
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• pp.1704-1710
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• 2010

The purpose of this study was to describe the biomechanical characteristics of stroke patients. These characteristics were obtained during walking on a Zebris system, cinematography system and EMG system. Seven female stroke patients participated in this study. The magnitude of the profiles (joint peak angle, joint peak moments, foot pressure COP, EMG data) correlated with rehabilitation training duration using t-test. The significance level selected for this study was p<0.05, t-test. Joint analysis identified significant differences in hip joint peak angle and hip joint peak moment. Foot pressure verified significant differences in gait line length of COP. The EMG signal proved significant differences in rectus femoris and vastus lateralis.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.46 no.5
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• pp.321-327
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• 2020

Objectives: This study is aimed to evaluate and compare the effect of moist heat fomentation therapy with ultrasound therapy in patients with the masticatory myalgia. Materials and Methods: The study was conducted on 42 patients with masticatory myalgia, dividing them into two groups; Group A (21 patients), received moist heat therapy and Group B (21 patients), received ultrasound therapy for seven effective days. Prior and after the treatment the numeric rating scale (NRS) and the electromyography (EMG) scores were recorded and compared. The observations were analyzed clinically and statistical support was taken to assess the NRS and EMG data. Results: Irrespective of the groups, patients testified a significant reduction in pain after the treatment. From the EMG readings; even though the standard deviation for each group was varied considerably, EMG recorded an improved muscle activity. Statistical analysis was used to assess and identify the best treatment methodology between the two modalities. Conclusion: From the statistical analysis, it is concluded that, though both the therapies had significantly reduced the symptomatic response, it is moist heat fomentation that improved muscle activity both statistically and clinically in comparison to ultrasound.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.156-162
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• 2024

The purpose of this study was to investigate the muscle activity of internal oblique, rectus femoris, and multifidus according to knee posture and foot bar angle during pilates reformer high flank exercise. Twelve women in their 20s were recruited within six months of their experience as pilates instructors. The subjects performed six types of high flanks according to knee posture and foot bar angle. EMG signals of internal oblique, rectus femoris, and multifidus during exercise were measured and analyzed by integral EMG. The collected data were processed by repeated measures two-way ANOVA. In this paper it shows the following results. First, internal oblique iEMG was not significantly different according to knee posture and foot bar angle. Second, the rectus femoris had an interaction effect according to knee posture and foot bar angle. Third, there was no significant difference in multifidus according to knee posture and foot bar angle. In conclusion, according to the exercise method, the activity of the rectus femoris was the highest in the knee bending and high foot-bar angle high plank exercise, and there was no difference between the internal oblique and multifidus.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.152-158
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• 2005

Commercial lower limb prostheses or orthotics help patients achieve a normal life. However, patients who use such aids need prolonged training to achieve a normal gait, and their fatigability increases. To improve patient comfort, this study proposed a method of predicting gait angle using neural networks and EMG signals. Experimental results using our method show that the absolute average error of the estimated gait angles is $0.25^{\circ}$. This performance data used reference input from a controller for the lower limb orthotic or prosthesis controllers while the patients were walking.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.55-64
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• 2004

Conventional bipolar surface electromyography(EMG) technique detects only the superimposed electromyographic activity of a large number of motor units due to its low spatial resolution. For the diagnosis of neuromuscular disorder, the information of single MU is required. In this paper, 9 channel array surface electrode system was as designed and MLoG filter was proposed. Also the MCPT(modified convolution processing technique)method was proposed for the improvement of MUAP resolution. For performance evaluation, power spectrum analysis of random data and raw EMG signal comparison of MUAP shape and quantitative estimation of SNR were executed. As a result, the MUAP resolution improvement of 32％ was obtained from the standpoint of the signal-to-noise ratio(SNR).

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1491-1499
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• 2019

Insufficient sleep time and bad sleep quality causes many illnesses and it's research became more and more important. The most common method for measuring sleep quality is the polysomnography(PSG). The PSG is a test used to diagnose sleep disorders. The most common PSG data is obtained from the examiner, which attaches several sensors on a body and takes sleep overnight. However, most of the sleep stage classification in PSG are low accuracy of the classification. In this paper, we have studied algorithm for sleep level classification based on machine learning which can replace PSG. EEG, EOG, and EMG channel signals are studied and tested by using CNN algorithm. In order to compensate the performance, a mixed model using both CNN and DNN models is designed and tested for performance.