METHODOLOGY/PRINCIPAL FINDINGS: Five electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. Two authors independently assessed selected articles using an MS-Word based form created for this review. Several domains (name of muscle, study type, sensor type, subject's types, muscle contraction, measured parameters, frequency range, hardware and software, signal processing and statistical analysis, results, applications, authors' conclusions and recommendations for future work) were extracted for further analysis. From a total of 2184 citations 119 were selected for full-text evaluation and 36 studies of MFs were identified. The systematic results find sufficient evidence that MMG may be used for assessing muscle fatigue, strength, and balance. This review also provides reason to believe that MMG may be used to examine muscle actions during movements and for monitoring muscle activities under various types of exercise paradigms.
CONCLUSIONS/SIGNIFICANCE: Overall judging from the increasing number of articles in recent years, this review reports sufficient evidence that MMG is increasingly being used in different aspects of MF. Thus, MMG may be applied as a useful tool to examine diverse conditions of muscle activity. However, the existing studies which examined MMG for MFs were confined to a small sample size of healthy population. Therefore, future work is needed to investigate MMG, in examining MFs between a sufficient number of healthy subjects and neuromuscular patients.
METHODS: Twenty male participants performed repetitive submaximal (60% MVIC) grip muscle contractions to induce muscle fatigue and the results were analyzed during the pre- and post-fatigue MVIC. MMG signals were recorded on the extensor digitorum (ED), extensor carpi radialis longus (ECRL), flexor digitorum superficialis (FDS) and flexor carpi radialis (FCR) muscles. The cross-correlation coefficient was used to quantify the cross-talk values in forearm muscle pairs (MP1, MP2, MP3, MP4, MP5 and MP6). In addition, the MMG RMS and MMG MPF were calculated to determine force production and muscle fatigue level, respectively.
RESULTS: The fatigue effect significantly increased the cross-talk values in forearm muscle pairs except for MP2 and MP6. While the MMG RMS and MMG MPF significantly decreased (p<0.05) based on the examination of the mean differences from pre- and post-fatigue MVIC.
CONCLUSION: The presented results can be used as a reference for further investigation of cross-talk on the fatigue assessment of extensor and flexor muscles' mechanic.
OBJECTIVE: The aim of this study was to compare the activity and relationship between surface EMG and static force from the BB muscle in terms of three sensor placement locations.
METHODS: Twenty-one right hand dominant male subjects (age 25.3 ± 1.2 years) participated in the study. Surface EMG signals were detected from the subject's right BB muscle. The muscle activation during force was determined as the root mean square (RMS) electromyographic signal normalized to the peak RMS EMG signal of isometric contraction for 10 s. The statistical analysis included linear regression to examine the relationship between EMG amplitude and force of contraction [40-100% of maximal voluntary contraction (MVC)], repeated measures ANOVA to assess differences among the sensor placement locations, and coefficient of variation (CoV) for muscle activity variation.
RESULTS: The results demonstrated that when the sensor was placed on the muscle belly, the linear slope coefficient was significantly greater for EMG versus force testing (r^{2} = 0.61, P > 0.05) than when placed on the lower part (r^{2}=0.31, P< 0.05) and upper part of the muscle belly (r^{2}=0.29, P > 0.05). In addition, the EMG signal activity on the muscle belly had less variability than the upper and lower parts (8.55% vs. 15.12% and 12.86%, respectively).
CONCLUSION: These findings indicate the importance of applying the surface EMG sensor at the appropriate locations that follow muscle fiber orientation of the BB muscle during static contraction. As a result, EMG signals of three different placements may help to understand the difference in the amplitude of the signals due to placement.