scholarly journals Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Sridhar P. Arjunan ◽  
Dinesh K. Kumar ◽  
Ganesh Naik
Keyword(s):  
Muscle Contraction ◽  
Muscle Fatigue ◽  
Root Mean Square ◽  
Linear Regression Analysis ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Median Frequency ◽  
Mean Square ◽  
Surface Electromyogram ◽  
The Relationship

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study:normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P<0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P<0.01). Both of these features were not affected by the intersubject variations (P>0.05).

scholarly journals Quadriceps short-term resistance exercise in subjects with resistant hypertension

2011 ◽  
Vol 24 (4) ◽  
pp. 629-636 ◽  
Author(s):  
Arthur de Sá Ferreira ◽  
Juliana Flávia de Oliveira ◽  
Ivan Cordovil ◽  
José Barbosa Filho
Keyword(s):  
Resistance Exercise ◽  
Root Mean Square ◽  
Resistant Hypertension ◽  
Pharmacological Treatment ◽  
Vastus Lateralis ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Median Frequency ◽  
Mean Square ◽  
Arterial Blood

INTRODUCTION: Resistant arterial hypertension may lead to muscle disuse and reduced functional capacity due to arterial and target-organs lesions. The main objective of this work is to evaluate the quadriceps strength and fatigue tolerance after a program of resistance exercise in subjects with resistant primary hypertension. METHODS: Six patients under pharmacological treatment were submitted to a four-week resistance exercise training program for the quadriceps (8-14 repetitions, 3 sets, 3 days per week). Strength was evaluated by isometric dynamometry, as the percentage change in maximum voluntary contraction over the four week program. Fatigue was analyzed by surface electromyography, as the change in both root mean square value and intercept of median frequency slope of vastus medialis and vastus lateralis. RESULTS: Significant increase in the maximum voluntary contraction was observed (p = 0.04). Fatigue tolerance was not improved as seen by root mean square as well as in the intercept of median frequency (p > 0.05). Additionally, no significant changes were observed in resting arterial blood pressure and heart rate throughout the training period. CONCLUSION: The prescribed protocol seemed to successfully increase localized muscle strength without negatively affecting the monitored cardiovascular variables in patients with resistant hypertension under pharmacological treatment.

A STUDY OF MODELS FOR HANDGRIP FORCE PREDICTION FROM SURFACE ELECTROMYOGRAPHY OF EXTENSOR MUSCLE

2009 ◽  
Vol 21 (02) ◽  
pp. 81-88 ◽  
Author(s):  
Wensheng Hou ◽  
Xiaolin Zheng ◽  
Yingtao Jiang ◽  
Jun Zheng ◽  
Chenglin Peng ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Surface Electromyography ◽  
Random Sequence ◽  
Maximum Voluntary Contraction ◽  
Force Production ◽  
Voluntary Contraction ◽  
Mean Square ◽  
Force Level ◽  
Force Output ◽  
Mean Square Errors

Force production involves the coordination of multiple muscles, and the produced force levels can be attributed to the electrophysiology activities of those related muscles. This study is designed to explore the activity modes of extensor carpi radialis longus (ECRL) using surface electromyography (sEMG) at the presence of different handgrip force levels. We attempt to compare the performance of both the linear and nonlinear models for estimating handgrip forces. To achieve this goal, a pseudo-random sequence of handgrip tasks with well controlled force ranges is defined for calibration. Eight subjects (all university students, five males, and three females) have been recruited to conduct both calibration and voluntary trials. In each trial, sEMG signals have been acquired and preprocessed with Root–Mean–Square (RMS) method. The preprocessed signals are then normalized with amplitude value of Maximum Voluntary Contraction (MVC)-related sEMG. With the sEMG data from calibration trials, three models, Linear, Power, and Logarithmic, are developed to correlate the handgrip force output with the sEMG activities of ECRL. These three models are subsequently employed to estimate the handgrip force production of voluntary trials. For different models, the Root–Mean–Square–Errors (RMSEs) of the estimated force output for all the voluntary trials are statistically compared in different force ranges. The results show that the three models have different performance in different force ranges. Linear model is suitable for moderate force level (30%–50% MVC), whereas a nonlinear model is more accurate in the weak force level (Power model, 10%–30% MVC) or the strong force level (Logarithmic model, 50%–80% MVC).

scholarly journals An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3108 ◽  
Author(s):  
Shing-Hong Liu ◽  
Chuan-Bi Lin ◽  
Ying Chen ◽  
Wenxi Chen ◽  
Tai-Shen Huang ◽  
...  
Keyword(s):  
Muscle Fatigue ◽  
Real Time ◽  
Root Mean Square ◽  
The Body ◽  
Median Frequency ◽  
Mean Square ◽  
Sport Injuries ◽  
Physiological Measurement ◽  
The Real ◽  
Emg Signal

In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants’ muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.

scholarly journals Relationship between Isometric Muscle Force and Fractal Dimension of Surface Electromyogram

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Matteo Beretta-Piccoli ◽  
Gennaro Boccia ◽  
Tessa Ponti ◽  
Ron Clijsen ◽  
Marco Barbero ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Muscle Contraction ◽  
Biceps Brachii ◽  
Isometric Force ◽  
Voluntary Contraction ◽  
Experimental Conditions ◽  
Surface Electromyogram ◽  
Mean Frequency ◽  
Muscle Contraction Intensity ◽  
The Relationship

The relationship between fractal dimension of the surface electromyogram (sEMG) and the intensity of muscle contraction is still controversial in simulated and experimental conditions. To support the use of fractal analysis to investigate myoelectric fatigue, it is crucial to establish the interdependence between fractal dimension and muscle contraction intensity. We analyzed the behavior of fractal dimension, conduction velocity, mean frequency, and average rectified value in twenty-eight volunteers at nine levels of isometric force. sEMG was obtained using bidimensional arrays in the biceps brachii muscle. The values of fractal dimension and mean frequency increased with force unless a plateau was reached at 30% maximal voluntary contraction. Overall, our findings suggest that, above a certain level of force, the use of fractal dimension to evaluate the myoelectric manifestations of fatigue may be considered, regardless of muscle contraction intensity.

Measurement and Analysis of Surface Electromyogram and Handgrip Force

2011 ◽  
Vol 225-226 ◽  
pp. 1318-1322
Author(s):  
Dong Mei Hao ◽  
Yan Zhang ◽  
Dong Ye Zhang ◽  
Zheng Wan ◽  
Yi Yang
Keyword(s):  
Voluntary Contraction ◽  
Median Frequency ◽  
Force Level ◽  
Mean Power ◽  
Mean Power Frequency ◽  
Surface Electromyogram ◽  
Static Contraction ◽  
Power Frequency ◽  
Relationship Of ◽  
The Relationship

To investigate the relationship of surface electromyogram (sEMG) and handgrip force, a measurement system was developed. Ten healthy subjects were required to perform a series of static contraction trials by maintaining the force level with maximal voluntary contraction (MVC), 75%MVC, 50%MVC and 25%MVC respectively. Then they sustained MVC as long as possible until fatigue. The handgrip force and sEMG on the forearm muscles were recorded. Root mean square (RMS), mean power frequency (MPF) and median frequency (MF) of the sEMG were calculated with LabVIEW. The results show that RMS increased with force level during voluntary contraction, while MPF and MF shift to lower frequency during fatigue condition. These findings suggested that the designed system can be used to study forearm function.

Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions

1990 ◽  
Vol 69 (5) ◽  
pp. 1810-1820 ◽  
Author(s):  
R. Merletti ◽  
M. Knaflitz ◽  
C. J. De Luca
Keyword(s):  
Muscle Fatigue ◽  
Root Mean Square ◽  
Conduction Velocity ◽  
Time Course ◽  
Tibialis Anterior Muscle ◽  
Median Frequency ◽  
Mean Square ◽  
Myoelectric Signal ◽  
Physiological Factor ◽  
Voluntary Contractions

The time course of muscle fiber conduction velocity and surface myoelectric signal spectral (mean and median frequency of the power spectrum) and amplitude (average rectified and root-mean-square value) parameters was studied in 20 experiments on the tibialis anterior muscle of 10 healthy human subjects during sustained isometric voluntary or electrically elicited contractions. Voluntary contractions at 20% maximal voluntary contraction (MVC) and at 80% MVC with duration of 20 s were performed at the beginning of each experiment. Tetanic electrical stimulation was then applied to the main muscle motor point for 20 s with surface electrodes at five stimulation frequencies (20, 25, 30, 35, and 40 Hz). All subjects showed myoelectric manifestations of muscle fatigue consisting of negative trends of spectral variables and conduction velocity and positive trends of amplitude variables. The main findings of this work are 1) myoelectric signal variables obtained from electrically elicited contractions show fluctuations smaller than those observed in voluntary contractions, 2) spectral variables are more sensitive to fatigue than conduction velocity and the average rectified value is more sensitive to fatigue than the root-mean-square value, 3) conduction velocity is not the only physiological factor affecting spectral variables, and 4) contractions elicited at supramaximal stimulation and frequencies greater than 30 Hz demonstrate myoelectric manifestations of muscle fatigue greater than those observed at 80% MVC sustained for the same time.

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

Intramuscular and surface electromyogram changes during muscle fatigue

1986 ◽  
Vol 60 (4) ◽  
pp. 1179-1185 ◽  
Author(s):  
T. Moritani ◽  
M. Muro ◽  
A. Nagata
Keyword(s):  
Muscle Fatigue ◽  
Biceps Brachii ◽  
Surface Emg ◽  
Firing Frequency ◽  
Voluntary Contraction ◽  
Mean Power ◽  
Mean Power Frequency ◽  
Surface Electromyogram ◽  
Spike Amplitude ◽  
Frequency Power

Twelve male subjects were tested to determine the effects of motor unit (MU) recruitment and firing frequency on the surface electromyogram (EMG) frequency power spectra during sustained maximal voluntary contraction (MVC) and 50% MVC of the biceps brachii muscle. Both the intramuscular MU spikes and surface EMG were recorded simultaneously and analyzed by means of a computer-aided intramuscular spike amplitude-frequency histogram and frequency power spectral analysis, respectively. Results indicated that both mean power frequency (MPF) and amplitude (rmsEMG) of the surface EMG fell significantly (P less than 0.001) together with a progressive reduction in MU spike amplitude and firing frequency during sustained MVC. During 50% MVC there was a significant decline in MPF (P less than 0.001), but this decline was accompanied by a significant increase in rmsEMG (P less than 0.001) and a progressive MU recruitment as evidenced by an increased number of MUs with relatively large spike amplitude. Our data suggest that the surface EMG amplitude could better represent the underlying MU activity during muscle fatigue and the frequency powers spectral shift may or may not reflect changes in MU recruitment and rate-coding patterns.

scholarly journals Relationship Between Millennials and Brand Loyalty: Mediating Brand Loyalty Factors

2017 ◽  
Vol 5 (3) ◽  
pp. 223
Author(s):  
Dhameeth, S. Gehan ◽  
Ochi, Yamamoto
Keyword(s):  
Root Mean Square ◽  
Brand Loyalty ◽  
Structural Equation ◽  
Brand Management ◽  
Management Strategies ◽  
Second Phase ◽  
Mean Square ◽  
Root Mean Square Residual ◽  
Mediating Factors ◽  
The Relationship

<p><em>The purpose of this study is to identify factors (brand elements) that mediate between Millennials and brand loyalty, and to test a theoretical model that includes these mediating factors in describing the relationship between millennials and brand loyalty. The study focused on the key factors that we identified and hypothesized to mediate the relationship between millennials and brand loyalty. The quantitative study surveyed two hundred and fifty-three (n=253) respondents randomly drawn. Structural Equation Modelling (SEM) was used to test a model of the relationship between the mediating factors, millennials and brand loyalty. All model fit parameters were well within acceptable bounds. The Comparative Fit Index (CFI) was 0.999, Root Mean Square Error of Approximation (RMSEA) was 0.018, and Standardized Root Mean Square Residual (SRMR) was 0.022. However, we believe that the model is over-fitting the data, and this is not surprising given that there are 22 variables and 253 data points. These results show promise, but require further investigation in a second phase of the inquiry. This study limited itself to surveying millennials, brand loyalty, and the seven mediating factors we identified and hypothesized to play a role in mediating between them. Based on this study, brand management strategies are proposed.</em><em></em></p>

Sign in / Sign up

Export Citation Format

Share Document