METHODS: This study investigated the effects of two different training interventions based on individualized load velocity profiles (LVP) on maximal bench press strength (i.e., 1RM), maximum throwing velocity (TV), and skeletal muscle mass (SKMM). Twenty-two university handball players were randomly assigned to Group 1 (low-movement speed training) or Group 2 (high-movement speed training). Group 1 exercised with a bar speed of 0.75-0.96 m/s, which corresponds to a resistance of approximately 60% 1RM, whereas Group 2 trained at 1.03-1.20 m/s, corresponding to a resistance of approximately 40% 1RM. Both groups exercised three times a week for five weeks, with strength and throwing tests performed at baseline and post-intervention.
RESULTS: A two-way repeated measures ANOVA was applied, and the results showed the interaction between group and time was not statistically significant for SKMM (p = 0.537), 1RM (p = 0.883), or TV (p = 0.774). However, both groups significantly improved after the five weeks of training: SKMM (3.1% and 3.5%, p
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-five subjects performed isometric elbow extension until failure, and the rate of fatigue (ROF), time to fatigue (TTF) and normalized TTF (NTTF) were statistically analysed. Subsequently, the behaviour of root-mean-square (RMS), mean-power frequency (MPF) and median-power frequency (MDF) under pre-, onset- and post-fatigue conditions were compared.
RESULTS: The findings indicated that, among the heads, ROF was statistically significant at 30% and 45% MVC (P<0.05) but TTF and NTTF at all intensities was statistically insignificant (P>0.05). For every head, only TTF was statistically significant (P<0.05) at different intensities. MPF and MDF under pre-, onset- and post-fatigue conditions were statistically significant (P<0.05) among the heads at all intensities, whereas RMS showed no such behaviour.
CONCLUSION: The investigated parameters reveal that the three heads of TB act independently before fatigue onset and appear to work in union after fatigue. Synergist head pairs exhibit similar spectral and temporal behaviour in contrast to the non-synergist TB head pair. We find spectral parameters to be more specific predictors of fatigue.
METHODS: An initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals.
RESULTS: Although correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk.
CONCLUSIONS: The phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.
METHODS: Ten male collegiate rowers and physically active untrained subjects were recruited. Muscle synergies were extracted from 16 rowing-specific muscles using Principal Component Analysis with varimax rotation. Incremental rowing VO2 max Test was performed on slides ergometer (SE). Rowing performance and physiological variables were analyzed.
RESULTS: Rowers exerted greater power output, more energy expenditure and better rowing economy compared to untrained subjects. Rowers preferred to row slower with longer strokes compared to the untrained subjects. Three muscle synergies with high indices of similarity of waveform patterns were extracted in both groups. Significant association was found between muscle synergies and rowing economy.
CONCLUSIONS: The findings of this study showed that muscle synergies were robust during aerobic-dominant activity for collegiate rowers and untrained subjects. Rowers and coaches could utilize the findings by emphasizing on muscle coordination training, which may enhance the rowing economy.