Shoulder muscles recruitment during a power backward giant swing on high bar: a wavelet-EMG-analysis

Validity of Gymnastics-Specific Assessment of Neuromuscular Function of Shoulder Flexor and Extensor Muscles to Predict Performance in Gymnastics Skills

ABSTRACT

Milosis, DC. Validity of gymnastics-specific assessment of neuromuscular function of shoulder flexor and extensor muscles to predict performance in gymnastics skills. J Strength Cond Res 37(3): 652-660, 2023-This study examined the relationships between gymnastics-specific laboratory measurements of neuromuscular function of the shoulder flexor and extensor muscles and performance in specific gymnastics skills. Fifteen highly competitive male gymnasts and 18 male students (age 20.41 ± 2.51 years, body mass 69.7 ± 7.07 kg; mean ± SD ) participated voluntarily. The electromyogram (EMG) was used to assess muscle activation of 3 flexor and 3 extensor shoulder muscles during isometric (45, 90, and 135°) and isokinetic (concentric and eccentric 60, 180, and 300°/s) flexion-extension of the shoulder. Peak torque (PT), neuromuscular efficiency (NME: torque to EMG ratio), and antagonist coactivation index (CI) were evaluated. Furthermore, performance in specific gymnastics skills was evaluated. The results supported the ecological validity of the measurements. Specifically, significant correlations emerged between the shoulders' neuromuscular function parameters and the performance in the gymnastics skills (PT: r = 0.798, p < 0.001, NME: r = 0.576, p < 0.001, CI: r = -0.351, p < 0.05). In addition, according to the results of the regression analysis, neuromuscular function of the shoulder flexor and extensor muscles predicted gymnastics performance. Specifically, the model that was produced significantly predicted the dependent variable (performance in specific gymnastics skills) in all steps and explained a total variance of 64.4% ( p < 0.001). Based on beta coefficients, PT had the higher contribution to the prediction of performance. The insight gained on these relationships could help coaches to plan the training of their gymnasts and to monitor the longitudinal changes in neuromuscular function of shoulder muscles induced by training more effectively.

Muscle Co-Contraction Detection in the Time-Frequency Domain

Background: Muscle co-contraction plays a significant role in motion control. Available detection methods typically only provide information in the time domain. The current investigation proposed a novel approach for muscle co-contraction detection in the time–frequency domain, based on continuous wavelet transform (CWT). Methods: In the current study, the CWT-based cross-energy localization of two surface electromyographic (sEMG) signals in the time–frequency domain, i.e., the CWT coscalogram, was adopted for the first time to characterize muscular co-contraction activity. A CWT-based denoising procedure was applied for removing noise from the sEMG signals. Algorithm performances were checked on synthetic and real sEMG signals, stratified for signal-to-noise ratio (SNR), and then validated against an approach based on the acknowledged double-threshold statistical algorithm (DT). Results: The CWT approach provided an accurate prediction of co-contraction timing in simulated and real datasets, minimally affected by SNR variability. The novel contribution consisted of providing the frequency values of each muscle co-contraction detected in the time domain, allowing us to reveal a wide variability in the frequency content between subjects and within stride. Conclusions: The CWT approach represents a relevant improvement over state-of-the-art approaches that provide only a numerical co-contraction index or, at best, dynamic information in the time domain. The robustness of the methodology and the physiological reliability of the experimental results support the suitability of this approach for clinical applications.

Estimation of Time-Frequency Muscle Synergy in Wrist Movements

Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0–125 Hz during the MC stage is more than that in the frequency band of 125–250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625–156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125–156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system.

Construct validity of gymnastics-specific assessment on the neuromuscular function of shoulder flexor and extensor muscles

The present study examined the construct validity of gymnastics-specific measurements of the shoulder flexor and extensor neuromuscular function. Fifteen male gymnasts and 18 male physical education (PE) students participated voluntarily. The electromyogram (EMG) of 3 flexor and 3 extensor shoulder muscles was assessed during isometric (45, 90, and 135º) and isokinetic (concentric and eccentric 60, 180, and 300º/s) shoulder flexion/extension. Peak torque (PT) and neuromuscular function in terms of neuromuscular efficiency (NME, i.e. torque to EMG ratio) and antagonist/agonist coactivation index were evaluated. The construct validity of the measurements was supported by the ability to discriminate between gymnasts and physical education (PE) students, taking into consideration the shoulders' neuromuscular function parameters (37%-57% of the variability explained). After accounting for the limitations of the study, these findings may assist gymnastics coaches and researchers to develop and evaluate more effective training methods for athletes related to shoulder joint physiological characteristics and level of expertise.

Upper Limb Neuromuscular Activities and Synergies Comparison between Elite and Nonelite Athletics in Badminton Overhead Forehand Smash

This study is aimed at comparing muscle activations and synergies in badminton forehand overhead smash (BFOS) between elite and nonelite players to clarify how the central nervous system (CNS) controls neuromuscular synergy and activation to generate complex overhead movements. EMG of five upper limb muscles was recorded through surface electromyography (EMG) electrodes from twenty players. Athletics is divided into two groups: elite and nonelite. Eventually, nonnegative matrix factorization (NNMF) was utilized to the calculated electromyography signals for muscle synergy comparison. Similarities between elite and nonelite groups were calculated by scalar product method. Results presented that three muscles synergies could sufficiently delineate the found electromyography signals for elite and nonelite players. Individual muscle patterns were moderately to highly similar between elite and nonelite groups (between-group similarity range: 0.52 to 0.90). In addition, high similarities between groups were found for the shape of synergy activation coefficients (range: 0.85 to 0.89). These results indicate that the synergistic organization of muscle coordination during badminton forehand overhead smash is not profoundly affected by expertise.

Spectral properties of multiple myoelectric signals: New insights into the neural origin of muscle synergies

It is still unclear if muscle synergies reflect neural strategies or mirror the underlying mechanical constraints. Therefore, this study aimed to verify the consistency of muscle groupings between the synergies based on the linear envelope (LE) of muscle activities and those incorporating the time-frequency (TF) features of the electromyographic (EMG) signals. Twelve healthy participants performed six 20-m walking trials at a comfort and fast self-selected speed, while the activity of eleven lower limb muscles was recorded by means of surface EMG. Wavelet-transformed EMG was used to obtain the TF pattern and muscle synergies were extracted by non-negative matrix factorization. When five muscle synergies were extracted, both methods defined similar muscle groupings whatever the walking speed. When accounting the reconstruction level of the initial dataset, a new TF synergy emerged. This new synergy dissociated the activity of the rectus femoris from those of the vastii muscles (synergy #1) and from the one of the tensor fascia latae (synergy #5). Overall, extracting TF muscle synergies supports the neural origin of muscle synergies and provides an opportunity to distinguish between prescriptive and descriptive muscle synergies.

The punctum fixum-punctum mobile model: a neuromuscular principle for efficient movement generation?

According to the “punctum fixum–punctum mobile model” that was introduced in prior studies, for generation of the most effective intentional acceleration of a body part the intersegmental neuromuscular onset succession has to spread successively from the rotation axis (punctum fixum) toward the body part that shall be accelerated (punctum mobile). The aim of the present study was to investigate whether this principle is, indeed, fundamental for any kind of efficient rotational accelerations in general, independent of the kind of movements, type of rotational axis, the current body position, or movement direction. Neuromuscular onset succession was captured by surface electromyography of relevant muscles of the anterior and posterior muscle chain in 16 high-level gymnasts during intentional accelerating movement phases while performing 18 different gymnastics elements (in various body positions to forward and backward, performed on high bar, parallel bars, rings and trampoline), as well as during non-sport specific pivot movements around the longitudinal axis. The succession patterns to generate the acceleration phases during these movements were described and statistically evaluated based on the onset time difference between the muscles of the corresponding muscle chain. In all the analyzed movement phases, the results clearly support the hypothesized succession pattern from punctum fixum to punctum mobile. This principle was further underlined by the finding that the succession patterns do change their direction running through the body when the rotational axis (punctum fixum) has been changed (e.g., high bar or rings [hands] vs. floor or trampoline [feet]). The findings improve our understanding of intersegmental neuromuscular coordination patterns to generate intentional movements most efficiently. This could help to develop more specific methods to facilitate such patterns in particular contexts, thus allowing for shorter motor learning procedures of context-specific key movement sequences in different disciplines of sports, as well as during non-sport specific movements.

Patterns of anterior and posterior muscle chain interactions during high performance long-hang elements in gymnastics

In a prior study with high level gymnasts we could demonstrate that the neuromuscular activation pattern during the "whip-like" leg acceleration phases (LAP) in accelerating movement sequences on high bar, primarily runs in a consecutive succession from the bar (punctum fixum) to the legs (punctum mobile). The current study presents how the neuromuscular activation is represented during movement sequences that immediately follow the LAP by the antagonist muscle chain to generate an effective transfer of momentum for performing specific elements, based on the energy generated by the preceding LAP. Thirteen high level gymnasts were assessed by surface electromyography during high performance elements on high bar and parallel bars. The results show that the neuromuscular succession runs primarily from punctum mobile towards punctum fixum for generating the transfer of momentum. Additionally, further principles of neuromuscular interactions between the anterior and posterior muscle chain during such movement sequences are presented. The findings complement the understanding of neuromuscular activation patterns during rotational movements around fixed axes and will help to form the basis of more direct and better teaching methods regarding earlier optimization and facilitation of the motor learning process concerning fundamental movement requirements.

Between-subject variability of muscle synergies during a complex motor skill

The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This cyclic movement is interesting because it requires learning, as untrained subjects are unable to perform this task. Nine gymnasts were tested. Both kinematics and electromyographic (EMG) patterns of 12 upper-limb and trunk muscles were recorded. Muscle synergies were extracted by non-negative matrix factorization (NMF), providing two components: muscle synergy vectors and synergy activation coefficients. First, the coefficient of correlation (r) and circular cross-correlation (r(max)) were calculated to assess similarities in the mechanical patterns, EMG patterns, and muscle synergies between gymnasts. We performed a further analysis to verify that the muscle synergies (in terms of muscle synergy vectors or synergy activation coefficients) extracted for one gymnast accounted for the EMG patterns of the other gymnasts. Three muscle synergies explained 89.9 ± 2.0% of the variance accounted for (VAF). The coefficients of correlation of the muscle synergy vectors among the participants were 0.83 ± 0.08, 0.86 ± 0.09, and 0.66 ± 0.28 for synergy #1, #2, and #3, respectively. By keeping the muscle synergy vectors constant, we obtained an averaged VAF across all pairwise comparisons of 79 ± 4%. For the synergy activation coefficients, r(max)-values were 0.96 ± 0.03, 0.92 ± 0.03, and 0.95 ± 0.03, for synergy #1, #2, and #3, respectively. By keeping the synergy activation coefficients constant, we obtained an averaged VAF across all pairwise comparisons of 72 ± 5%. Although variability was found (especially for synergy #3), the gymnasts exhibited gross similar neuromuscular strategies when performing backward giant swings. This confirms that the muscle synergies are consistent across participants, even during a skilled motor task that requires learning.