• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.807-812
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• 1995

In this study, comparisons were made among three representative methods for predicting compressive forces on the lumbosacral disc: LP-based model, double LP-based model and EMG-assisted model. Two subjects simulated lifting tasks that are normally performed in the refractories industry. In the refractories lifting tasks, vertical and horizontal distance, and weight of load were varied. To calculate the L5/Sl compressive forces, EMG signals from six trunk muscles were measured and postural data were recorded using the Motion Analysis System. The EMG-assisted model was shown to reflect well all three factors considered here. On the other hand, the compressive forces of the two LP-based models were only significantly affected by weight of load.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.107-113
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• 1997

In this paper, an interfacing method to control rehabilitation assitance system with bio-signal is proposed. Controlling with EMG signals method has certain advantage on signal-collecting, but has some drawbacks in the function resolution of EMG signals because data-processing process is not efficient. To improve function-resolution and to increase the efficiency of EMG signal interfacing with rehabilitation assistance system, Multi-layer Perception which is highly effective with static signal and hidden-Markov model for dynamic signal resolving are fused together. In proposed method. The direction and average speed of the rehabilitation assitance system are controlled by the trajectory control and estimation of the moving direction result from the fused model. From the experiment, proposed GMM and 2-level MLP hybrid-classifier yielded 8.6% perception-error rate, improving function resolution. New acceleration control method constructed with 3 nested linear filter produced continuous acceleration paths without the information of destination point. Thus, the mass output caused by non- continuous acceleration-deceleration was eliminated. In the simulation, the necessary calculation, in the case of multiplication, was reduced by 11.54%.

• 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.

• Korean Journal of Applied Biomechanics
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• v.17 no.2
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• pp.41-50
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• 2007

The purpose of this study was to examine the effects of Task-oriented training on the balance, lapse time and MVC(Maximum Voluntary Contraction) of CVA(cerebral vascular accident) patients. The active balance equipment was used to measure of the static balance, lapse time and task-oriented training. The EMG technique was used to record muscle activitie of affected side of gluteus medius and vastus medialis. The raw EMG data were filtered with band pass filter (60Hz) to remove artifacts and then low pass filtered (20Hz) to find the linear envelope which resemble muscle tension curve. The experiment had been conducted at the department of physical therapy in J hospital in M city during 8weeks. The thirty patients experienced the stroke were participated: training group (15), control group (15). They were ambulatory with or without an assistive device. They were assessed on central perturbation(mm) in the static balance, lapse time(s) and MVC test(mV). The data were analyzed using repeated measured ANOVA. The results were as follows: After Task-oriented training, central perturbation and lapse time was significantly differences in both groups(p<.001), and MVC in gluteus medius were no significant differences in both groups, but vastus medialis was significant differences in both groups (p<.001).

• International Journal of Contents
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• v.10 no.3
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• pp.90-95
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• 2014

The purpose of this study was to analyze the changes in muscle fatigue by using electromyography (EMG) measurements of the median frequency of shoulder muscles of patients who underwent rotator cuff repair, and to provide basic data for efficient exercise methods during rehabilitation after the repair. In the study, 24 male and 8 female patients who underwent rotator cuff repair performed continuous passive shoulder joint motion for 3 weeks and the median frequency of their shoulder muscles before and after the repair were compared using measurements by EMG. The infraspinatus, supraspinatus, and serratus anterior muscles showed significant differences in the changes in the median frequency before and after the repair. Significant differences were also found in the median frequency of the three muscles both before and after the repair. Additionally, the middle deltoid muscle had a lower median frequency than the supraspinatus muscle before the repair and the infraspinatus muscle had a lower median frequency than the middle deltoid muscle after the repair. It is expected that these results will serve as important data in developing rehabilitation exercise programs for the infraspinatus, supraspinatus, and serratus anterior muscles by compensating the middle deltoid muscle with the lowest muscle fatigue after the rotator cuff repair erase.

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.241-246
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• 2009

Since inappropriate muscle forces mean that people cannot perform some activities related to roles of the muscle, muscle forces have been considered as an important parameter in clinic. Therefore, many methods have been introduced to estimate muscle forces indirectly. One of the methods is muscle tissue dynamics and it is widely used in commercial softwares including musculoskeletal model, such as SIMM. They, however, need motion data captured from 3-dimensional motion analysis system. In this study, we introduced an algorithm to estimate muscle forces in real-time by using joint angles. The heel-rise movements were performed for a normal with 3-dimensional motion analysis system, EMG measurement system, and electrogoniometers. Joint angles obtained from electrogoniometers and EMG signals were used to estimate muscle forces. Simulation was performed to find muscle forces using motion data which was imported into musculoskeletal software. As the results, muscle lengths and forces from the developed algorithm were similar to those from commercial software in pattern. Results of this study would be helpful to implement a tool to calculate reasonable muscle forces in real-time.

• Korean Journal of Applied Biomechanics
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• v.13 no.2
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• pp.115-122
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• 2003

The purposes of this study were to analyze the muscle activities and the characteristics of muscle recruting patterns of lower limb for crouching start technique using four elite splint. The EMG technique was used to record muscle activities of both right and left sides of retus femoris, vastus medialis, biceps femoris, and gastrocnemius. Eight surface electrodes were placed on the surface of the selected muscles and one ground electrode was also attached on the back of neck(C7). One video camera was also used to record the crouching start motion to define 6 events and 5 phases for further analysis. The raw EMG data were filtered with band pass filter(10-350) to remove artifacts and then low pass filtered(4Hz) to find the linear envelope which resemble muscle tension curve. This filter EMG data were normalized to MVIC for the purpose of comparison between right and left sides muscle. The results of this study were as follows. All four subjects showed that vastus medialis muscle activity was comparatively higher than those of retus femoris, biceps femoris, gastrocnemius. And left side of muscle activity was comparatively higher than right side of muscle activity. Therefore, when the subjects starting out crouching start position, we recognized that the muscle of lower limb showed interaction effect by each muscle.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.142-148
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• 2016

Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.