• Korean Journal of Applied Biomechanics
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• v.31 no.4
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• pp.270-275
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• 2021

Objective: The purpose of this study was to evaluate 16 muscles activity according to three exercise intensity when performing Deadlift and Upright row. Method: To accomplish the purpose of the study, subjects (n=10) were performed Electromyography (EMG) measurement for 16 different muscles. The experimental movements were Deadlift and Upright row, measured five times for each intensity (40%, 60%, 80%) of 1RM. This study normalized the EMG values through RVC for comparative analysis. Results: The results were summarized as follows: As a result of Deadlift, there was significant difference in the mean EMG value according to the exercise intensity in all muscles except RA, PM and BB (p<.05). As a result of Upright row, There was significant difference in the mean EMG value according to the exercise intensity in all muscles except BF, TA, GN, RA and UT (p<.05). Conclusion: This study allowed us to know the activities of major muscles according to the exercise intensity for 16 different muscles when performing Deadlift and Upright row.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.2
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• pp.2308-2313
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• 2021

Background: Although the scapular posterior tilt movement could facilitate the lower trapezius (LT) muscle activity, no study identified the effects of the scapular posterior tilt movement on the selective activation of the LT muscle during prone shoulder extension. Objectives: To examine the influences of additional scapular posterior tilt on electromyography (EMG) of the upper trapezius (UT) and the LT muscles during prone shoulder extension. Design: Cross-sectional study. Methods: There were 15 asymptomatic male participants in this study who performed prone shoulder extension with and without scapular posterior tilt movements. For the scapular posterior tilt movements, participants performed visual biofeedback training for scapular movement using motion sensor. During the exercises, the EMG activity of the UT and LT was recorded using surface EMG system. Results: The EMG activity of the LT significantly increased during prone shoulder extension with scapular posterior tilt compared to that of general prone shoulder extension, whereas that of the UT was not significantly different between the two exercises. Moreover, scapular posterior tilt application significantly decreased UT/LT muscle activity ratio. Conclusion: Scapular posterior tilt movement may be emphasized during exercise when facilitating LT muscle activation.

• Clinical Pain
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• v.19 no.2
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• pp.90-96
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• 2020

Objective: To investigate the diagnostic accuracy of two physical examinations (straight leg raise [SLR] and Bragard test) and electromyography (EMG) in patients with lumbosacral monoradiculopathy in acute and chronic state on confirmation of different diagnostic criteria (MRI vs MRI and diagnostic selective nerve root block [DSNRB]). Method: We identified 297 participants retrospectively from the departmental database. MRI evidence of L5 or S1 nerve root compression and a positive result in diagnostic SNRB served as reference standards. They were divided into two groups by the symptom duration: lasting more than 12 weeks in the chronic group and less than 12 weeks in the acute group. The diagnostic value of clinical tests and EMG were compared. Results: The clinical tests (SLR and Bragard test) done in acute stage on detection by MRI and DSNRB had the highest sensitivity (68%) compared to the chronic stage (63%), but sensitivity was low (57%) on confirmation of MRI alone. However, there was no significant difference on sensitivity and specificity of EMG regardless of reference standards and symptom duration. Electromyography was a significant predictor of neuropathic abnormalities on both acute (OR, 6.3; 95% CI, 2.4 to 16.7; p<0.01) and chronic (OR, 6.8; 95% CI, 2.9 to 16.3; p<0.01). Conclusion: In general, individual physical tests are easy to do and a combination of those tests could be a sensitive indicator of L5 or S1 radiculopathy. Furthermore, the use of provocation tests could provide useful information, especially in proceeding therapeutic selective nerve root block.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1129-1137
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• 2012

The aim of this study was to find useful parameters of the between myotonometer and surface electromyography(sEMG) on the medialis gastrocnemius of stroke patients and investigate between these parameters and modified Ashworth scale(MAS) relationship. 5 years clinical experience physical therapist using the Modified Ashworth Scale(MAS) was selected 15 patients with ankle spasticity and divided randomly MAS2, MAS3, MAS4 groups. Myotonometer and sEMG was measured during relaxed and maximum voluntary contractions of the gastrocnemius muscle. The results of this study, the higher MAS score was the lowered the relaxation and contraction state tissue compliance and muscle activity and in the correlation analysis the higher MAS score during voluntary contraction in the cylinder receiving low-intensity correlation could see that increased than relaxation. Therefore, the myotonometer is a useful clinical and research tool with spasticity muscle and can provide objective quantitative data about the efficacy of physical therapy interventions.

• Physical Therapy Korea
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• v.24 no.1
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• pp.9-18
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• 2017

Background: Short foot exercise (SFex) is often prescribed and performed in the sport and rehabilitation fields to strengthen intrinsic foot muscles. However, SFex is difficult to perform because of lack of feedback methods. Objects: The aim of this study was to compare the effects of SFex with and without electromyography (EMG) biofeedback on the medial longitudinal arch (MLA) of healthy individuals who maintained a static standing position. Methods: All participants (14 males and 12 females) were randomly divided into two groups (biofeedback and non-biofeedback groups). The EMG activity of the abductor hallucis (AbdH) and tibialis anterior (TA) and the MLA angle on the dominant leg side were measured with the participant in the standing position in the pre- and post-intervention conditions. The intervention session consisted of 15 minutes of SFex with (biofeedback group) or without (non-biofeedback group) EMG biofeedback. The groups were compared using two-way repeated measures analysis of variance. Results: The post-intervention activities of the AbdH muscle (p<.05) and the AbdH/TA ratio (p<.05) were significantly greater in the biofeedback group than in the non-biofeedback group. The activity of the TA (p<.05) and the MLA angle (p<.05) in the biofeedback group were significantly lower in the post-intervention condition than in the pre-intervention condition. Conclusion: The present findings demonstrate that the combination of SFex and EMG biofeedback can effectively facilitate the muscle activity of the AbdH and strengthen the medial longitudinal arch.

• Journal of Korean Physical Therapy Science
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• v.10 no.1
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• pp.83-89
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• 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 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.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.37-50
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• 2022

Objective : This study aimed to investigate the use of electromyography (EMG) to evaluate upper limb movement or function in stroke patients. Methods : We reviewed papers published in journals between January 2018 and December 2021 using PubMed, EMBASE, Scopus, RISS, and KISS. The main keywords of databases were ('stroke' OR 'hemiplegia') AND ('EMG' OR 'electromyography' OR 'electromyogram' OR 'muscle activity') AND ('Upper limb' OR 'Hand'). Results : Fifteen studies were selected, most of which evaluated muscle activity. Interventions performing tasks related to activities of daily living (ADLs), using assistive technology, and interventions that provide repetitive training were most frequently applied. Conclusions : When evaluating upper limb functions using electromyography, it is meaningful to present an evaluation that can be used according to the purpose of the study and to provide a basis for setting up interventions that can utilize electromyography during evaluation.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.211-220
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• 2023

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.