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Article

Neuromuscular Assessment of Maximal Shoulder Flexion/Extension Torque Development in Male Gymnasts

by
Dimitrios C. Milosis
1,*,
Costas Dallas
2,
Dimitrios A. Patikas
3,
George Dallas
2 and
Theophanis Siatras
1
1
Laboratory of Evaluation of Human Biological Performance, School of Physical Education and Sports Science, Department of Physical Education and Sport Sciences, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
2
School of Physical Education and Sport Science, Department of Physical Education and Sport Science, National and Kapodistrian University of Athens, 17237 Athens, Greece
3
School of Physical Education and Sports Science (Serres), Aristotle University of Thessaloniki, 62500 Serres, Greece
*
Author to whom correspondence should be addressed.
Biomechanics 2025, 5(3), 49; https://doi.org/10.3390/biomechanics5030049
Submission received: 10 June 2025 / Revised: 29 June 2025 / Accepted: 30 June 2025 / Published: 1 July 2025
(This article belongs to the Section Neuromechanics)

Abstract

Background/Objectives: The objective of this study was to compare muscular strength and neuromuscular activation characteristics between male gymnasts and physical education (PE) students during isometric shoulder extension and flexion tasks. Methods: Thirteen competitive male gymnasts (age: 19.59 ± 1.90 years; body mass: 66.54 ± 6.10 kg; height: 169.38 ± 6.28 cm; mean ± SD) and thirteen male physical education (PE) students (age: 20.96 ± 2.30 years; body mass: 74.00 ± 8.69 kg; height: 174.96 ± 4.93 cm) voluntarily participated in the study. Peak torque (PT), rate of torque development (RTD), RTD normalized to body mass (RTD/BM), and muscle activation assessed via surface electromyography (EMG), normalized to maximal EMG activity (EMG/EMGmax), were evaluated during bilateral isometric shoulder extension and flexion at a joint angle of 45°. Measurements were analyzed across the following time intervals: −50 to 0 ms (pre-tension), 0–30 ms, 0–50 ms, 0–100 ms, and 0–200 ms relative to contraction onset. Custom MATLAB R2024b scripts were used for data processing and visualization. One-way and two-way multivariate analyses of variance (MANOVAs) were conducted to test for group differences. Results: Gymnasts exhibit higher values of PT, PT/BM, RTD, and RTD/BM particularly within the early contraction phases (i.e., 0–50 ms and 0–100 ms) compared to PE students (p < 0.05 to <0.001; η2 = 0.04–0.66). Additionally, EMG activity normalized to maximal activation (EMG/EMGmax) was significantly greater in gymnasts during both early and mid-to-late contraction phases (0–100 ms and 0–200 ms), (p < 0.05 to <0.001; η2 = 0.04–0.48). Conclusions: These findings highlight gymnasts’ superior explosive neuromuscular capacity. Metrics like RTD, RTD/BM, and EMG offer valuable insights into rapid force production and neural activation, supporting performance monitoring, training optimization, and injury prevention across both athletic and general populations.

1. Introduction

Gymnastics is a prime example of a sport that relies heavily on rapid, explosive muscle contractions, like those involved in pulling, pushing, jumping, or sprinting [1]. High-level gymnastics performance requires strong and powerful shoulders and upper limbs. Therefore, training and evaluating gymnastics-specific power, strength, and coordination of the shoulder muscles particularly during bilateral extension or flexion in both isometric and isokinetic actions is important for assessing progress and potential in advanced gymnastics skills [2,3,4,5,6,7,8,9]. For this reason, gymnasts typically train regularly and systematically for 16 to 30 h per week, sometimes even up to 40 h, starting from an early age. Their training involves a consistently high load, a large volume of exercises, and numerous repetitions [10].
Strength training can lead to an increase in force, even in short-term studies. For example, researchers have found that gymnasts exhibit greater isometric shoulder flexion strength and shoulder girdle elevation in bilateral movements compared to age-matched controls [7], as well as a higher peak torque (PT) of the shoulder flexor and extensor muscles during isokinetic contractions in comparison to non-athletes [5].
In addition to maximal strength, the rate of torque development (RTD), which reflects the neuromuscular ability to rapidly increase torque production over time [11,12,13,14,15,16], is increasingly emphasized by researchers and practitioners due to its functional importance [12,16,17]. It is commonly monitored in sports using isometric muscle actions to evaluate performance and training progression [18]. The RTD is more relevant for rapid strength production than PT, which is a less sensitive measure in the sports that include movement durations of less than ~100–200 ms [19] and may also be useful to distinguish between athletes versus non-athletes. The RTD can be evaluated at various time points following the onset of contraction [12]. Typically, the early phases of the RTD are influenced by neural activation, representing the efficiency of the nervous system to recruit its motor neurons [16,20,21]. In contrast, the later phases are more strongly associated with factors such as the force during a maximal voluntary contraction (MVC), muscle thickness, the cross-sectional area, muscle architecture, and fatiguability [11,17,21,22].
Research concerning the RTD in gymnastics has garnered attention due to its implications for performance. The ability to generate torque rapidly is essential for gymnasts, as many skills require quick, explosive movements that last less than 200 ms [23,24]. The knee flexion (KF) and extension (KE) RTD were found to be significantly higher in young male gymnasts (who are typically trained for explosive muscular performance) than in young swimmers (who are mostly endurance-trained) or non-athletes [25]. Research has also shown that young female gymnasts display significantly higher PT and RTD values during MVC compared to their non-gymnast peers [7,23]. In this context, gymnasts were compared with untrained boys during maximal, explosive, isometric elbow flexions (EFs) [1,26] and knee flexions (KFs) and showed higher size-normalized EF PT and RTDpk. On the contrary, ref. [24], examining the differences between female collegiate basketball players and gymnasts, suggested that both relative PT and later RTD time phases (100–200 ms) tended to be deficient in gymnasts compared to basketball players. According to the researchers, these deficiencies could not be explained by the smaller size of the gymnasts.
To better understand the reasons behind the differences in force production and its derivatives between gymnasts and other athletes or untrained individuals, it is important to examine the activation of the muscles involved in generating force, thereby identifying the causes of these differences. The impact of muscle activation pattern adaptations resulting from strength training on torque production has also been investigated [12,13,14,15,16,27,28]. Based on these studies, it has been shown that elite athletes exhibit earlier and higher activation. More specifically in gymnasts, studies have indicated that they typically exhibit higher muscle activation levels during specific tasks compared to non-athletes [29,30,31]. This increased activation is linked to their training, which prioritizes the development of neuromuscular strategies that optimize performance in dynamic movements such as landings and acrobatic maneuvers [29,30,32]. Additionally, variations in torque production between gymnasts and non-athletes may result from intrinsic muscle adaptations driven by the functional demands of gymnastics [33]. In contrast, a study examining long-term neuromuscular adaptations to training in gymnastic landings found that gymnasts showed overall lower normalized root mean square (NRMS) values compared to the controls, possibly due to the use of a different normalization method [34]. However, no studies have investigated the effects of gymnastics training on gymnasts’ shoulder extension and flexion RTD or the rate of muscle activation.
Considering the above points, it seems that the RTD and muscle activation are different in gymnasts compared to non-gymnasts, and this might play a critical role in overall performance. Therefore, the purpose of this study was to assess the muscular strength and neuromuscular activation characteristics of male gymnasts and PE students during isometric shoulder extension and flexion tasks. It was hypothesized that gymnasts would demonstrate a higher RTD and a greater rate of muscle activation compared to PE students. The findings of this study are expected to provide valuable practical insights into rapid force production and neural activation in trained individuals, with potential applications in optimizing athletic performance, guiding rehabilitation strategies, and reducing injury risk.

2. Materials and Methods

2.1. Participants

Prior to data collection, an a priori power analysis was conducted for a between-groups design using (G*Power 3.1.9.7). Based on the assumption of a large effect size, it was determined that at least 24 participants were required to achieve a statistical power of 0.80 with an alpha level of 0.05. Thus, 13 competitive male gymnasts (age: 19.59 ± 1.90 years, body mass: 66.54 ± 6.10 Kg, and height: 169.38 ± 6.28 cm, M ± SD) and 13 male physical education (PE) students (20.96 ± 2.30, 74.00 ± 8.69, 174.96 ± 4.93 cm), participated in the study. All participants were free of shoulder joint disorders that could impair test performance and had no prior experience with isokinetic measurements. All gymnasts were senior-level athletes with over 10 years of intensive training, engaging in a minimum of 20 h of training per week. Notably, four of them trained twice daily for four days each week. Most competed in all gymnastics apparatuses, although they specialized in one to three. All participated in national competitions, and four also competed at the international level. The demographic characteristics of these participants are presented in Table 1. In accordance with the Declaration of Helsinki and in compliance with applicable legislation, all participants were thoroughly informed about the study’s purpose, procedures, benefits, and any potential risks or discomforts associated with the testing. Informed consent was obtained from all subjects involved in the study, as well as from the parents of the four underage gymnasts, prior to conducting the measurements.

2.2. Procedures

The measurements were conducted in the Laboratory of Biological Evaluation of Human Performance. All subjects adhered to a standardized protocol and were instructed to avoid strenuous exercise the day before testing. After recording height and body mass, participants completed a general warm-up consisting of (a) 6 min of arm cycling with progressively increasing intensity in forward and backward directions (evenly split), (b) 2 min of isometric shoulder extension and flexion using an elastic band (2 sets of 10 s), and (c) 3 min of shoulder muscle stretching [5,35].

2.2.1. Strength Assessment

After electrode placement, bilateral shoulder extension and flexion were evaluated isometrically. Shoulder muscle strength was assessed using an isokinetic dynamometer (Humac Norm 770), which was calibrated in accordance with the manufacturer’s guidelines (Humac Norm Manual; Computer Sports Medicine, Inc., Stoughton, MA, USA) [36]. Subjects were positioned supine on the dynamometer chair and secured with Velcro straps at the chest, pelvis, and thigh. Neutral position (0° flexion) was defined as the position in which the hands were aligned with the hips. The shoulder joint’s rotation axis was aligned with the device’s axis while the arms were flexed at 45°. Subjects pressed the elbow or shoulder adapter with fully extended elbows in an overhand grip (Figure 1) [5,9,35]. This action relates to key skills in gymnastics. Gravity correction was applied using the dynamometer’s software.
Before the maximal voluntary contraction (MVC) assessments, participants completed a standardized warm-up of three submaximal isometric contractions for extension and flexion with increasing intensity. Maximal isometric torque (PT) was then assessed in three ballistic voluntary contractions at a 45° angle. Participants exerted and maintained maximal effort for 6 s to ensure peak torque was recorded [37]. Rest intervals were 30 s between trials and 60 s between extension and flexion, which was sufficient for muscle recovery and reliable data collection [38]. Participants were instructed to kick out as quickly and forcefully as possible, with verbal encouragement provided throughout each trial. They were also instructed to gradually build up the torque over 2–4 s to approach maximum effort and generate as much torque as possible for an additional 2 s [39].
Rate of torque development. Neuromechanical function was assessed by measuring early and late phases of the RTD (0–30, 0–50, 0–100, and 0–200 ms), which correspond to the demands of daily activities and sport-specific tasks and are influenced by neural and muscular factors [11,17,24]. The peak RTD was determined as the maximum value after calculating the RTD with a 20 ms moving window, from the torque onset to the PT.
Onsets of voluntary and evoked ballistic torque signals were manually identified through visual inspection by the same investigator, using a two-point differential method. The onset was defined as the final trough preceding a deflection of the torque signal above the baseline mean—a technique that was demonstrated to be highly repeatable [21,40]. Manual identification is considered the gold standard method [21,40,41]. Although it is viewed as more subjective than mathematical algorithms (automated methods) commonly used in exercise science (e.g., ≥2 SD of the baseline), manual identification is more sensitive and accurate, allowing for the detection of onsets up to 60 ms earlier than automated methods. In addition to the absolute values, all PT and RTD variables were normalized to each participants’ body mass (BM).

2.2.2. Electromyography Recording

Electromyography (EMG) was measured for three shoulder extensor muscles (posterior deltoid, long head of the triceps brachii, and latissimus dorsi) and three flexor muscles (anterior deltoid, long head of the biceps brachii, and clavicular head of the pectoralis major) using two circular, pre-gelled, self-adhesive, Ag-AgCl surface electrodes. After shaving and cleaning the skin with ethanol, the electrodes were positioned over the muscle belly with an inter-electrode distance of 20 mm, following SENIAM guidelines [42]. EMG was measured on the right side of the body to minimize any interference from the cardiac muscle.
EMG signals were collected using the Biopac acquisition system (MP100A-CE, Biopac Systems, Inc., Goleta, CA, USA). The signal was amplified with a gain of 1000 (common mode rejection ratio > 100 dB), sampled at 1000 Hz, and band-pass filtered from 25 to 450 Hz. Signal processing was performed using AcqKnowledge 4.1 software (Biopac Systems, Inc., Goleta, CA, USA). For the quantification of muscle activation, the root mean square (RMS) of the filtered EMG signals was calculated using a 20 ms sample window [43]. For the estimation of the maximal muscle activation during the MVC (EMGmax), the average RMS was calculated 250 ms before and after the time when PT occurred during the MVC trial. All EMG signals were normalized to the EMGmax [44]. The composite EMG activity for the agonist extensor muscles was then calculated as [(LD + TB + PD)/3] and for the flexor muscles as [(PM + BB + AD)/3].
The RMS of EMG was assessed during torque development. The rate of RMS rise was used to assess the rate of muscle activation [25]. The average RMS was calculated for each muscle before (−50–0 ms) and after (0–30, 0–50, 0–100, and 0–200 ms) the EMG onset. The EMG onset was set at 70 ms before the torque onset, assuming a fixed electromechanical delay for all muscles [16,45]. Custom MATLAB scripts (The MathWorks, Inc., Natick, MA, USA) were used for data visualization and processing.

2.3. Statistical Analysis

Data normality was assessed by examining kurtosis and skewness values, as well as using the Shapiro–Wilk test. The assumptions of equality of variance–covariance matrices across groups and homogeneity were tested using Box’s test and Levene’s test, respectively. One-way multivariate analyses of variance (MANOVAs) were conducted to examine differences in (a) age, height, body mass (BM), (b) absolute peak torque (PT), PT normalized to BM (PT/BM), and (c) the maximum RMS of EMG (EMGmax) of agonist extensor and flexor muscles during isometric extension and flexion between gymnasts and PE students. Two-way MANOVAs were conducted to examine (a) the effects of group, time interval (0–30, 0–50, 0–100, 0–200), and their interaction on the rate of torque development (RTD), both in absolute terms and normalized to body mass (RTD/BM), during isometric extension and flexion. Both absolute and body mass-normalized values of PT and the RTD were reported, as in previous studies, to allow for performance comparison and neuromuscular efficiency analysis, and to increase the transparency, reproducibility, and interpretability of the findings [12,25,46,47]. (b) In addition, the effects of group, time interval (−50–0, 0–30, 0–50, 0–100, 0–200), and their interaction on the RMS of the EMG signal, normalized to the maximum EMG and expressed as a percentage (EMG/EMGmax × 100), were examined for the agonist muscles during isometric extension and flexion. A significance level of p < 0.05 was adopted. All statistical analyses were performed using SPSS 29.0 (IBM Corp., Armonk, NY, USA).

3. Results

With few exceptions, the examined variables met the criteria for an approximate normal distribution, as indicated by skewness values between −1.0 and +1.0, kurtosis values between −1.6 and +1.6, and non-significant Shapiro–Wilk tests (p > 0.05). Box’s M test and Levene’s test were significant in some cases, indicating violations of the assumptions of the equality of variance–covariance matrices and the equality of variances across groups, respectively. Nevertheless, MANOVAs and MANCOVAs were conducted, as these analyses are considered robust to such violations when sample sizes across groups are approximately equal [48]. In these cases, Pillai’s Trace was used as the test statistic due to its robustness to assumption violations.

3.1. Differences in Demographic Characteristics Between Groups

The one-way ΜANOVA yielded a main effect for group (Wilks’ λ = 0.443, F(3, 22) = 9.21, p < 0.001, η2 = 0.56). As shown in Table 1, the gymnasts had significantly lower BMs and heights, while there were no differences in age compared to the PE students.
Table 1. Means, standard deviations, and one-way MANOVA statistics for demographic characteristics.
Table 1. Means, standard deviations, and one-way MANOVA statistics for demographic characteristics.
VariablesGymnastsPE Students
MSDMSDFpη2
Age (years)19.591.9020.962.302.720.1120.10
Height (cm)169.386.28174.964.9325.380.0010.13
Body mass (kg)66.546.1074.008.696.420.0180.51
M: mean; SD: standard deviation; p: level of statistical significance; η2: effect size.

3.2. Differences in PT and Peak RTD Between Groups

Absolute PT and normalized PT (PT/BM) during isometric extension and flexion. The one-way ΜANOVA revealed a main effect by group, where Pillai’s Trace = 0.710, F(4, 21) = 12.87, p < 0.001, η2 = 0.71. Follow-up univariate ANOVAs indicated that the gymnasts had significantly higher absolute PT and PT/BM values compared to the PE students during isometric extension and flexion (Table 2).
Absolute peak RTD and normalized peak RTD (peak RTD/BM) during isometric extension and flexion. The one-way ΜANOVA revealed that the main effect of group on peak RTD and peak RTD/BM was not significant (Wilks’ λ = 0.397, F(4, 21) = 3.46, p < 0.05, η2 = 0.26). Follow-up univariate ANOVAs indicated that gymnasts had higher peak RTD and peak RTD/BM values compared to PE students during extension and flexion (Table 2).

3.3. Differences in RTD Across Time Intervals

Absolute RTD and normalized RTD (RTD/BM) during isometric extension across time intervals. The two-way MANOVA revealed a significant multivariate effect of group, with Pillai’s Trace = 0.343, F(2, 95) = 24.77, p < 0.001, η2 = 0.34, and a non-significant multivariate effect of the time interval, with Pillai’s Trace = 0.61, F(6, 192) = 1.01, p = 0.417, η2 = 0.03. There was no interaction between groups and time intervals, with Pillai’s Trace = 0.008, F(2, 192) = 0.13, p = 0.993, η2 = 0.00. Follow-up univariate ANOVAs indicated that gymnasts had higher RTD (F(1, 96) = 21.60, p < 0.001, η2 = 0.18) and RTD/BM (F(1, 96) = 34.49, p < 0.001, η2 = 0.26) values over time compared to PE students. On the other hand, there were no differences in RTD and RTD/BM values between time intervals for both groups combined. Regarding the interaction between time intervals and groups, follow-up univariate ANOVAs indicated that gymnasts had significantly higher (a) RTD values for the time intervals of 0–50 (F(1, 96) = 6.97, p < 0.01, η2 = 0.07), 0–100 (F(1, 96) = 6.84, p < 0.01, η2 = 0.07), and 0–200 (F(1, 96) = 4.22, p < 0.05, η2 = 0.04), and (b) RTD/BM values for the time intervals of 0–30 (F(1, 96) = 6.00, p < 0.05, η2 = 0.06), 0–50 (F(1, 96) = 10.71, p < 0.01, η2 = 0.10), and 0–100 (F(1, 96) = 10.56, p < 0.01, η2 = 0.10, and F(1, 96) = 6.77, p < 0.01, η2 = 0.07) compared to PE students (Figure 2). Finally, for the interaction between groups and time intervals, follow-up univariate ANOVAs indicated that there were no differences in RTD and RTD/BM values between time intervals for each group.
Absolute RTD and normalized RTD (RTD/BM) during isometric flexion across time intervals. The two-way MANOVA revealed a significant multivariate effect of group (Pillai’s Trace = 0.269, F(2, 95) = 17.51, p < 0.001, η2 = 0.27) and a non-significant multivariate effect of time interval (Pillai’s Trace = 0.103, F(6, 192) = 1.73, p = 0.115, η2 = 0.05). There was no interaction between group and time interval (Pillai’s Trace = 0.011, F(2, 192) = 0.173, p = 0.984, η2 = 0.01). Follow-up univariate ANOVAs indicated that gymnasts had higher RTD (F(1, 96) = 16.50, p < 0.001, η2 = 0.27 and RTD/BM, F(1, 96) = 22.81, p < 0.001, η2 = 0.17) values over time compared to PE students. On the other hand, there were no differences in RTD and RTD/BM values between time intervals for both groups combined. Regarding the interaction between time interval and group, follow-up univariate ANOVAs indicated that gymnasts had significantly higher (a) RTD values for the time intervals of 0–50 (F(1, 96) = 5.44, p < 0.05, η2 = 0.05) and 0–100 (F(1, 96) = 5.67, p < 0.05, η2 = 0.06), and (b) RTD/BM values for the time intervals of 0–30 (F(1, 96) = 3.94, p < 0.05, η2 = 0.04), 0–50 (F(1, 96) = 7.45, p < 0.01, η2 = 0.07), 0–100 (F(1, 96) = 7.90, p < 0.01, η2 = 0.08), and 0–200 (F(1, 96) = 4.11, p < 0.05, η2 = 0.04) compared to PE students (Figure 3). Finally, for the interaction between groups and time intervals, follow-up univariate ANOVAs indicated that there were no differences in RTD and RTD/BM values between time intervals for each group.

3.4. Differences in Maximum EMG (EMGmax) Across Time Intervals

The one-way ΜANOVA revealed that the main effect of group on EMGmax was not significant (Wilks’ λ = 0.700, F(2, 23) = 4.20, p < 0.05, η2 = 0.30). Follow-up univariate ANOVAs indicated that gymnasts had a higher EMGmax compared to PE students during extension (F(1, 24) = 8.15, p < 0.01, η2 = 0.30) and flexion (F(1, 24) = 8.26, p < 0.01, η2 = 0.26).

3.5. Differences in Normalized EMG (EMG/EMGmax) Across Time Intervals

The two-way MANOVA revealed a significant multivariate effect of (a) group (Pillai’s Trace = 0.242, F(2, 119) = 19.02, p < 0.001, η2 = 0.24) and (b) a significant multivariate effect of time interval (Pillai’s Trace = 0.966, F(8, 240) = 28.05, p < 0.001, η2 = 0.48). There was no interaction between group and time interval, with Pillai’s Trace = 0.114, F(8, 240) = 1.82, p = 0.074, η2 = 0.06. Follow-up univariate ANOVAs revealed significant differences between gymnasts and PE students in EMG/EMGmax values during extension (F(1, 120) = 23.97, p < 0.001, η2 = 0.17) and flexion (F(1, 120) = 28.76, p < 0.001, η2 = 0.29) over time. On the other hand, the participants in both groups combined had significant differences in EMG/EMGmax values during extension and flexion between all intervals, except for the time interval of −50–0 compared to 0–30. Regarding the interaction between time interval and group, follow-up univariate ANOVAs indicated that gymnasts had significantly higher EMG/EMGmax values during (a) extension for the time intervals of 0–100 (F(1, 120) = 7.76, p < 0.01, η2 = 0.07) and 0–200 (F(1, 120) = 20.31, p < 0.001, η2 = 0.15), and (b) flexion for the time intervals of 0–50 (F(1, 120) = 5.62, p < 0.05, η2 = 0.05), 0–100 (F(1, 120) = 7.63, p < 0.01, η2 = 0.06), and 0–200 (F(1, 120) = 25.68, p < 0.001, η2 = 0.18) compared to PE students. Finally, for the interaction between groups and time intervals, follow-up univariate ANOVAs indicated that (a) gymnasts had significant differences in EMG/EMGmax values during extension and flexion between all intervals, except for the time interval of −50–0 compared to 0–30 and 0–50, and (b) PE students had significant differences in EMG/EMGmax values during extension and flexion between all intervals, except for the time interval of −50–0 compared to 0–30 (Figure 4).

4. Discussion

The present investigation represents the first study to examine shoulder agonist muscles’ RTD, RTD/BM, and EMG/EMGmax during bilateral extension and flexion in gymnasts and PE students. The findings indicate that isometric shoulder extension and flexion in male gymnasts are characterized by more rapid torque generation, a higher RTD, and elevated electromyographic activity compared to PE students. In terms of shoulder strength parameters, gymnasts exhibited significantly higher absolute and body mass-normalized PT values during extension and flexion. Furthermore, the gymnast group demonstrated significantly greater peak RTD and peak RTD/BM values compared to the PE student group. Notably, the magnitude of between-group differences was more pronounced when RTD values were normalized to body mass, particularly within the early contraction phases (i.e., 0–50 ms and 0–100 ms intervals), indicating a greater explosive neuromuscular capacity in gymnasts during rapid force production.
Research has shown that male gymnasts exhibit greater force production during bilateral isometric shoulder extension and flexion compared to students [5]. Similarly, young female gymnasts demonstrate superior isometric shoulder flexion strength compared to non-athlete controls [7]. Several studies have demonstrated differences in the RTD, with gymnasts excelling over other athletes and untrained individuals. Young male gymnasts, whose training predominantly targets explosive muscular performance, exhibit significantly higher KF and KE RTD values compared to young swimmers, who primarily emphasize endurance, and non-athletes [25]. In this context, gymnasts outperformed untrained boys in maximal, explosive, isometric EFs and KFs, demonstrating higher size-normalized EF PT and peak RTD values, with force levels comparable to those of adults [1]. Likewise, after 10 months of training, gymnasts exhibited a significantly greater increase in normalized peak RTD values only during EF compared to the control group [26]. Čeklić & Šarabon (2021) [49] also reported that young female gymnasts display significantly greater KF and KE PT and RTD values during MVC compared to their non-gymnast peers. Likewise, young female gymnasts showed superior force production and a faster rate of force generation than untrained controls [7].
Research indicates that targeted training involving fast and explosive muscle contractions, such as those seen in gymnastics, not only enhances maximal strength but, more critically, improves the RTD. Research has shown that training with the intention to perform explosive efforts, even during isometric (zero-velocity) contractions, can enhance the RTD and promote high-velocity strength adaptations [1]. This training effect in gymnasts is further supported by the work of Halin et al. (2002) [30], who observed a higher mean power frequency and a more pronounced decline during isometric EFs in gymnasts compared to untrained boys. These results confirm an improved ability to generate rapid torque, reflecting a greater capacity to recruit fast-twitch type II motor units, along with increased motor unit firing rates and earlier recruitment of high-threshold motor units in response to explosive training [30,50,51]. The early phase of the RTD (<100 ms) appears to be primarily influenced by neural drive and the intrinsic contractile properties of the involved muscles, whereas the late phase (>100 ms) is strongly associated with maximal muscle strength, muscle architecture, and contractile properties, proving to be important to assess neuromuscular performance [1,11,12,17,21].
However, research findings on the RTD across different time periods are inconsistent. For instance, Kochanowicz et al. (2019) [26] reported that, after adjusting baseline values, gymnasts exhibited significantly greater increases in RTD 0–100 and RTD 0–200 during EE compared to their untrained peers. In the case of EF, significantly higher adjusted changes in gymnasts were observed only for the 0–200 ms RTD interval [26]. In contrast, Thompson et al. (2017) [24] investigated differences between female collegiate basketball players and gymnasts, finding that gymnasts tended to have lower relative PT and reduced RTD values in the later time phases (100–200 ms) compared to basketball players. The researchers noted that these deficits could not be attributed to the gymnasts’ smaller body size. In this context, some research suggests that although it seems logical to assume that combining strength and rapid-contraction training would improve both strength and the RTD, this combination may have a more significant effect on PT than on the RTD [13]. In this regard, studies indicate that although traditional resistance training increases maximal strength, it does not always lead to improvements in the RTD [17]. These findings may partially account for the results observed in the present study, which revealed no significant differences in RTD values between gymnasts and PE students across any of the analyzed time intervals.
With respect to muscle activation, the present study found that gymnasts had higher EMGmax and EMG/EMGmax values during time intervals compared to PE students. Notably, the magnitude of between-group differences was more pronounced during the early and mid-to-late contraction phases—specifically within the 0–100 ms and 0–200 ms time intervals—indicating a superior explosive neuromuscular capacity in gymnasts during rapid force production. Several studies have indicated that strength training leads to increased muscle activation, as assessed through surface EMG [12,13,14,28], with the initial phase of contraction showing heightened responsiveness to training focused on a high rate of muscle activation (ROA) [12,28]. Researchers have reported that, compared to other athletes, gymnasts exhibit different patterns of muscle activity during the execution of fundamental gymnastics skills [52]. Mitchell et al. (2011) [25] reported a higher rate of EMG increase during KE in gymnasts, suggesting a faster muscle activation rate compared to untrained boys. Christoforidou et al. (2017) [29] reported that gymnasts demonstrated higher normalized EMG signals for the lateral gastrocnemius (LG) and VL muscles during landing in comparison with untrained girls. In contrast, a similar study reported that gymnasts exhibited overall lower normalized root mean square (NRMS) values compared to control participants [34]. The authors attributed this discrepancy to the use of a different normalization method, which limits the ability to directly compare outcomes with those of previous studies. An additional finding of the present study was a progressive increase in EMG activity across time intervals beyond the 0–50 ms mark. This pattern was evident during both shoulder extension and flexion and was consistently observed in both gymnasts and PE students. Similar temporal increases in muscle activation have been reported in previous studies [34,53].
Go-contraction (or coactivation) of antagonistic muscles is a factor that may influence the development of rapid muscle strength, especially in activities that require explosive power. In adults, it has been shown that strength training reduces antagonist coactivation and thus results in greater net joint torque [54,55]. A relevant study investigating the neuromuscular function of the shoulder extensor and flexor muscles in gymnasts found that long-term intensive gymnastics training leads to reduced antagonist muscle coactivation. This reduction is essential for generating powerful torque while preserving shoulder joint integrity. As a result, gymnasts achieve higher neuromuscular efficiency (NME), which is crucial for performing complex movements that demand rapid torque production [9]. Similarly, the results of the study by Kochanowicz et al. (2019) [26] showed that the coactivation of the EE was lower in adult gymnasts compared to untrained individuals after 10 months of explosive sport training. According to Kochanowicz et al. (2019), [26] neuromuscular adaptations may reflect either improved coordination between antagonistic muscle groups, leading to greater rate of torque development (RTD), or the enhanced maximal activation of the agonist muscles (increased motor unit recruitment and firing rate) associated with gains in maximal strength, or a combination of both.
In the context of gymnasts, where typical muscle contractions last around 50–150 ms, researchers have explained the observed increase in muscle activity during shoulder extension and flexion as sport-specific neuromuscular adaptations. These adaptations are essential for performing complex movements and maintaining stability throughout gymnastic routines. These involve the enhancement of motor unit recruitment, increased neural drive, and refined intramuscular coordination. The high demands of gymnastics, especially during dynamic upper-body movements like handstands, swings, and tumbling, lead gymnasts to develop enhanced efficiency and control in activating both agonist and antagonist muscles surrounding the shoulder joint. This increased muscle activity is a result of the neuromuscular system’s adaptation to repeated high-intensity training that aims to improve joint stability and movement precision. However, research examining EMG values across different time phases in gymnasts remains limited. The findings of the present study suggest that analyzing the RTD and EMG within short, consecutive time intervals may offer deeper insights into the factors influencing the RTD in sports like gymnastics, where performance relies heavily on rapid force production.
A limitation of the present study was that the PE students were sports-oriented and engaged in gymnastics and other athletic activities as part of their school curriculum, with some possibly participating regularly in sports and explosive resistance training beyond the school program. Their involvement in sports and resistance training may have influenced their shoulder extension and flexion muscle strength and power. Another methodological limitation of this study was its cross-sectional design. Regarding the procedure of the measurements, a potential limitation of the evaluation was the inclusion of only two repetitions and a single measurement angle. Furthermore, the normalization of the measurements was carried out using the body mass of the participants. Although the gymnasts had a lower body mass compared to the PE students, it could be hypothesized that they had a higher cross-sectional area (CSA) of the examined muscles. Normalizing the measurements using CSA may yield different results. Due to these limitations, the results cannot be generalized to populations with different characteristics (e.g., younger individuals or females).
Future research is recommended to investigate the neuromuscular characteristics of the shoulder extensors and flexors across populations with homogeneous traits, as well as between groups with more distinct differences (e.g., elite gymnasts versus individuals who do not engage in regular exercise more than once a week), or among gymnasts specializing in different apparatuses. Studies should also consider methodological issues such as testing at additional joint angles (e.g., 90° and 135°), including more repetitions, or evaluating the effects of specific interventions. Finally, future research could also explore additional mechanisms that may influence the RTD, including the muscle cross-sectional area and fiber type composition.

5. Conclusions

The present findings underscore the value of laboratory-based isometric testing as an effective tool for assessing neuromuscular adaptations associated with long-term, sport-specific training. In particular, measurements such as RTD, RTD/BM, and EMG activity provide critical insights into the rapid force-generating capacity and neural activation strategies of trained individuals. This type of testing also offers a complementary method for monitoring explosive muscular performance across different training phases. Understanding the nature and implications of these neuromuscular adaptations is essential for optimizing performance-oriented training and rehabilitation strategies, as well as reducing injury risk across athletic and general populations.

Author Contributions

Conceptualization, D.C.M. and T.S.; Methodology, D.C.M. and T.S.; Software, D.A.P.; Validation, D.C.M.; Formal analysis, D.C.M. and D.A.P.; Investigation, D.C.M.; Data curation, C.D.; Writing—review & editing, D.C.M., D.A.P., G.D. and T.S.; Visualization, C.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and in compliance with applicable legislation.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data analyzed in this paper are available from the corresponding author on reasonable request.

Acknowledgments

Some of the language and phrasing improvements in this manuscript were supported by ChatGPT-4o-mini architecture, under the supervision and final revision of the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Dotan, R.; Mitchell, C.J.; Cohen, R.; Gabriel, D.; Klentrou, P.; Falk, B. Explosive Sport Training and Torque Kinetics in Children. Appl. Physiol. Nutr. Metab. 2013, 38, 740–745. [Google Scholar] [CrossRef] [PubMed]
  2. Gorosito, M.A. Relative Strength Requirement for Swallow Element Proper Execution: A Predictive Test. Sci. Gymnast. J. 2013, 5, 59–67. [Google Scholar] [CrossRef]
  3. Gupta, V. Gymnastic Performance and Motor Fitness and Its Components. Int. J. Adv. Res. Manag. Soc. Sci. 2014, 3, 169–178. [Google Scholar]
  4. Hübner, K.; Schärer, C. Relationship between Swallow, Support Scale and Iron Cross on Rings and Their Specific Preconditioning Strengthening Exercises. Sci. Gymnast. J. 2015, 7, 59–68. [Google Scholar] [CrossRef]
  5. Milosis, D.C.; Siatras, T.A.; Christoulas, K.I.; Patikas, D.A. Construct Validity of Gymnastics-Specific Assessment on the Neuromuscular Function of Shoulder Flexor and Extensor Muscles. Sport. Biomech. 2023, 22, 966–981. [Google Scholar] [CrossRef] [PubMed]
  6. Milosis, C.D.; Siatras, A.T.; Christoulas, I.K.; Proios, K.M.; Proios, K.M.; Papaioannou, G.A. Accuracy of University Students’ Skill-Specific Self-Efficacy and Self-Efficacy-Performance in Gymnastics Relationship. Int. J. Sport. Psychol. 2018, 49, 429–447. [Google Scholar]
  7. Prescott, J. Identification and Development of Talent in Young Female Gymnasts. Ph.D. Dissertation, Loughborough University, Loughborough, UK, 1999. [Google Scholar] [CrossRef]
  8. Siatras, T.A.; Douka, I.D.; Milosis, D.C. Feasibility and Reproducibility of Muscular Strength Measures in Gymnastics-Specific Body Positions Using Hand-Held Dynamometry. Isokinet. Exerc. Sci. 2010, 18, 223–234. [Google Scholar] [CrossRef]
  9. Milosis, D.C. Validity of Gymnastics-Specific Assessment of Neuromuscular Function of Shoulder Flexor and Extensor Muscles to Predict Performance in Gymnastics Skills. J. Strength. Cond. Res. 2023, 37, 652–660. [Google Scholar] [CrossRef]
  10. Caine, D.; Knutzen, K.; Howe, W.; Keeler, L.; Sheppard, L.; Henrichs, D.; Fast, J. A Three-Year Epidemiological Study of Injuries Affecting Young Female Gymnasts. Phys. Ther. Sport 2003, 1466, 10–23. [Google Scholar] [CrossRef]
  11. Andersen, L.L.; Aagaard, P. Influence of Maximal Muscle Strength and Intrinsic Muscle Contractile Properties on Contractile Rate of Force Development. Eur. J. Appl. Physiol. 2006, 96, 46–52. [Google Scholar] [CrossRef]
  12. Aagaard, P.; Simonsen, E.B.; Andersen, J.L.; Magnusson, P.; Dyhre-Poulsen, P. Increased Rate of Force Development and Neural Drive of Human Skeletal Muscle Following Resistance Training. J. Appl. Physiol. 2002, 93, 1318–1326. [Google Scholar] [CrossRef] [PubMed]
  13. Del Vecchio, A.; Enoka, R.M.; Farina, D. Specificity of Early Motor Unit Adaptations with Resistive Exercise Training. J. Physiol. 2024, 602, 2679–2688. [Google Scholar] [CrossRef]
  14. Gruber, M.; Gruber, S.B.H.; Taube, W.; Schubert, M. Differential effects of ballistic versus sensorimotor training on rate of for. J. Strength Cond. Res. 2007, 21, 274–282. [Google Scholar] [CrossRef] [PubMed]
  15. Holtermann, A.; Roeleveld, K.; Engstrøm, M.; Sand, T. Enhanced H-Reflex with Resistance Training Is Related to Increased Rate of Force Development. Eur. J. Appl. Physiol. 2007, 101, 301–312. [Google Scholar] [CrossRef] [PubMed]
  16. Maffiuletti, N.A.; Aagaard, P.; Blazevich, A.J.; Folland, J.; Tillin, N.; Duchateau, J. Rate of Force Development: Physiological and Methodological Considerations. Eur. J. Appl. Physiol. 2016, 116, 1091–1116. [Google Scholar] [CrossRef]
  17. Andersen, L.L.; Andersen, J.L.; Zebis, M.K.; Aagaard, P. Early and Late Rate of Force Development: Differential Adaptive Responses to Resistance Training? Scand. J. Med. Sci. Sport. 2010, 20, 162–169. [Google Scholar] [CrossRef]
  18. Stone Michael, H.; Oʼbryant Harold, S.; Mccoy Lora, S.; Coglianese Robert, S.; Lehmkuhl Mark, S.; Schilling Brian, S. Power and Maximum Strength Relationships During Performance of Dynamic and Static Weighted Jumps. J. Strength. Cond. Res. 2003, 17, 140–147. [Google Scholar]
  19. Hernández-Davó, J.; Sabido, R. Rate of Force Development: Reliability, Improvements and Influence on Performance. A Review. Eur. J. Hum. Mov. 2014, 33, 46–69. [Google Scholar]
  20. Vecchio, A.D.; Negro, F.; Holobar, A.; Casolo, A.; Folland, J.P.; Felici, F.; Farina, D.; Taylor, J.; Carson, R. You Are as Fast as Your Motor Neurons: Speed of Recruitment and Maximal Discharge of Motor Neurons Determine the Maximal Rate of Force Development in Humans. J. Physiol. 2019, 9, 2445–2456. [Google Scholar] [CrossRef]
  21. Folland, J.P.; Buckthorpe, M.W.; Hannah, R. Human Capacity for Explosive Force Production: Neural and Contractile Determinants. Scand. J. Med. Sci. Sports 2014, 24, 894–906. [Google Scholar] [CrossRef]
  22. Cossich, V.; Maffiuletti, N.A. Early vs. Late Rate of Torque Development: Relation with Maximal Strength and Influencing Factors. J. Electromyogr. Kinesiol. 2020, 55, 102486. [Google Scholar] [CrossRef] [PubMed]
  23. Čeklić, U.; Šarabon, N. Strength and Jumping Asymmetries in Gymnast and Their Non-Gymnast Peers. Sci. Gymnast. J. 2021, 13, 411–424. [Google Scholar] [CrossRef]
  24. Thompson, B.J.; Cazier, C.S.; Bressel, E.; Dolny, D.G. A Lower Extremity Strength-Based Profile of NCAA Division I Women’s Basketball and Gymnastics Athletes: Implications for Knee Joint Injury Risk Assessment. J. Sports Sci. 2018, 36, 1749–1756. [Google Scholar] [CrossRef]
  25. Mitchell, C.; Cohen, R.; Dotan, R.; Gabriel, D.; Klentrou, P.; Falk, B. Rate of Muscle Activation in Powerand Endurance-Trained Boys. Int. J. Sports Physiol. Perform. 2011, 6, 94–105. [Google Scholar] [CrossRef] [PubMed]
  26. Kochanowicz, A.; Niespodziński, B.; Mieszkowski, J.; Sawczyn, S.; Cieszczyk, P.; Kochanowicz, K. Neuromuscular and Torque Kinetic Changes after 10 Months of Explosive Sport Training in Prepubertal Gymnasts. Pediatr. Exerc. Sci. 2019, 31, 77–84. [Google Scholar] [CrossRef]
  27. Aagaard, P. Training-Induced Changes in Neural Function. Exerc. Sport Sci. Rev. 2003, 31, 61–67. [Google Scholar] [CrossRef]
  28. Gruber, M.; Gollhofer, A. Impact of Sensorimotor Training on the Rate of Force Development and Neural Activation. Eur. J. Appl. Physiol. 2004, 92, 98–105. [Google Scholar] [CrossRef]
  29. Christoforidou, A.; Patikas, D.A.; Bassa, E.; Paraschos, I.; Lazaridis, S.; Christoforidis, C.; Kotzamanidis, C. Landing from Different Heights: Biomechanical and Neuromuscular Strategies in Trained Gymnasts and Untrained Prepubescent Girls. J. Electromyogr. Kinesiol. 2017, 32, 1–8. [CrossRef]
  30. Halin, R.; Germain, P.; Buttelli, O.; Kapitaniak, B. Differences in Strength and Surface Electromyogram Characteristics between Pre-Pubertal Gymnasts and Untrained Boys during Brief and Maintained Maximal Isometric Voluntary Contractions. Eur. J. Appl. Physiol. 2002, 87, 409–415. [Google Scholar] [CrossRef]
  31. da Silva, R.S.; Cerqueira, M.S.; Maciel, D.G.; da Silva, S.T.; de Figueiredo, M.C.C.; Cardoso, D.C.R.; Neto, S.B.N.; Bezerra, C.F.; Pereira, R.; de Brito Vieira, W.H.; et al. Rate of Torque Development of Paretic Lower Limb Is an Excellent Predictor of Walking Speed in Chronic Stroke Individuals. Clin. Biomech. 2022, 91, 105527. [Google Scholar] [CrossRef]
  32. Wu, C.; Hao, W.; He, W.; Xiao, X.; Li, X.; Sun, W. Biomechanical and Neuromuscular Strategies on Backward Somersault Landing in Artistic Gymnastics: A Case Study. Math. Biosci. Eng. 2019, 16, 5862–5876. [Google Scholar] [CrossRef]
  33. Goulart, N.B.A.; Dias, C.P.; Lemos, F.d.A.; Geremia, J.M.; Oliva, J.C.; Vaz, M.A. Gymnasts and Non-Athletes Muscle Activation and Torque Production at the Ankle Joint. Rev. Bras. Cineantropom. Desempenho Hum. 2014, 16, 555–562. [Google Scholar] [CrossRef]
  34. Niespodziński, B.; Grad, R.; Kochanowicz, A.; Mieszkowski, J.; Marina, M.; Zasada, M.; Kochanowicz, K. The Neuromuscular Characteristics of Gymnasts’ Jumps and Landings at Particular Stages of Sports Training. J. Hum. Kinet. 2021, 78, 15–28. [Google Scholar] [CrossRef] [PubMed]
  35. Milosis, D.C.; Siatras, T.A.; Christoulas, K.I.; Patikas, D.A. Relative and Absolute Reliability of Isometric and Isokinetic Shoulder Maximal Moment and Flexion/Extension Ratios in Gymnasts. Sci. Gymnast. J. 2018, 10, 227–244. [Google Scholar] [CrossRef]
  36. CSMI. Humac®/NormTM Testing & Rehabilitation System User’s Guide Model 770; Computer Sports Medicine, Inc.: Stoughton, MA, USA, 2006. [Google Scholar]
  37. Moudgil, R.; Karpovich, P.V. Duration of a Maximal Isometric Muscular Contraction. Res. Q. 1969, 40, 536–539. [Google Scholar] [CrossRef] [PubMed]
  38. Perrin, D.H. Isokinetic Exercise and Assessment; Human Kinetics: Champaign, IL, USA, 1993. [Google Scholar]
  39. Moskowitz, S.; Russ, D.W.; Clark, L.A.; Wages, N.P.; Grooms, D.R.; Woods, A.J.; Suhr, J.; Simon, J.E.; O’Shea, A.; Criss, C.R.; et al. Is Impaired Dopaminergic Function Associated with Mobility Capacity in Older Adults? GeroScience 2021, 43, 1383–1404. [Google Scholar] [CrossRef]
  40. Tillin, N.A.; Jimenez-Reyes, P.; Pain, M.T.G.; Folland, J.P. Neuromuscular Performance of Explosive Power Athletes versus Untrained Individuals. Med. Sci. Sports Exerc. 2010, 42, 781–790. [Google Scholar] [CrossRef]
  41. Dotan, R.; Jenkins, G.; O’Brien, T.D.; Hansen, S.; Falk, B. Torque-Onset Determination: Unintended Consequences of the Threshold Method. J. Electromyogr. Kinesiol. 2016, 31, 7–13. [Google Scholar] [CrossRef]
  42. Hermens, H.J.; Freriks, B.; Disselhorst-Klug, C.; Rau, G. Development of Recommendations for SEMG Sensors and Sensor Placement Procedures. J. Electromyogr. Kinesiol. 2000, 10, 361–374. [Google Scholar] [CrossRef]
  43. De Luca, C.J. The use of surface electromyography in Biomechanics. J. Appl. Biomech. 1997, 13, 135–163. [Google Scholar] [CrossRef]
  44. Besomi, M.; Hodges, P.W.; Clancy, E.A.; Van Dieën, J.; Hug, F.; Lowery, M.; Merletti, R.; Søgaard, K.; Wrigley, T.; Besier, T.; et al. Consensus for Experimental Design in Electromyography (CEDE) Project: Amplitude Normalization Matrix. J. Electromyogr. Kinesiol. 2020, 53, 102438. [Google Scholar] [CrossRef]
  45. Aagaard, P.; Simonsen, E.B.; Andersen, J.L.; Magnusson, P.; Dyhre-Poulsen, P. Neural Adaptation to Resistance Training: Changes in Evoked V-Wave and H-Reflex Responses. J. Appl. Physiol. 2002, 92, 2309–2318. [Google Scholar] [CrossRef] [PubMed]
  46. Dotan, R.; Mitchell, C.; Cohen, R.; Gabriel, D.; Klentrou, P.; Falk, B. Child-Adult Differences in the Kinetics of Torque Development. J. Sports Sci. 2013, 31, 945–953. [Google Scholar] [CrossRef]
  47. Kochanowicz, A.; Niespodziñski, B.; Mieszkowski, J.; Kochanowicz, K.; Sawczyn, S. The Effect of Gymnastic Training on Muscle Strength and Co-Activation during Isometric Elbow and Glenohumeral Flexion/Extension. J. Sports Med. Phys. Fit. 2018, 58, 966–973. [Google Scholar] [CrossRef] [PubMed]
  48. Tabachnick, B.G.; Fidell, L.S. Using Multivariate Statistics, 6th ed.; Pearson: Boston, MA, USA, 2012. [Google Scholar] [CrossRef]
  49. Čeklić, U.; Šarabon, N. Comparison between Gymnasts and Non-Gymnasts in Isometric Strength of the Lower Limbs. Eur. J. Transl. Myol. 2021, 31, 9663. [Google Scholar] [CrossRef] [PubMed]
  50. Duchateau, J.; Baudry, S. Training Adaptation of the Neuromuscular System. In Neuromuscular Aspects of Sport Performance; Komi, P.V., Ed.; Wiley-Blackwell: Hoboken, NJ, USA, 2010; Volume 17, pp. 216–253. [Google Scholar] [CrossRef]
  51. Gabriel, D.A.; Kamen, G.; Frost, G. Neural Adaptations to Resistive Exercise: Mechanisms and Recommendations for Training Practices. Sport. Med. 2006, 36, 133–149. [Google Scholar] [CrossRef]
  52. Kochanowicz, A.; Niespodzinski, B.; Mieszkowski, J.; Marina, M.; Kochanowicz, K.; Zasada, M. Changes in the Muscle Activity of Gymnasts during a Handstand on Various Apparatus. J. Strength. Cond. Res. 2019, 33, 1609–1618. [Google Scholar] [CrossRef]
  53. Tillin, N.A.; Folland, J.P. Maximal and Explosive Strength Training Elicit Distinct Neuromuscular Adaptations, Specific to the Training Stimulus. Eur. J. Appl. Physiol. 2014, 114, 365–374. [Google Scholar] [CrossRef]
  54. Amiridis, I.G. Co-Activation and Tension-Regulating Phenomena during Isokinetic Knee Extension in Sedentary and Highly Skilled Humans. Eur. J. Appl. Physiol. Occup. Physiol. 1996, 73, 149–156. [Google Scholar] [CrossRef]
  55. Tillin, N.A.; Pain, M.T.G.; Folland, J.P. Short-Term Unilateral Resistance Training Affects the Agonist-Antagonist but Not the Force-Agonist Activation Relationship. Muscle Nerve 2011, 43, 375–384. [Google Scholar] [CrossRef]
Figure 1. Adjusted elbow or shoulder adapter assembly.
Figure 1. Adjusted elbow or shoulder adapter assembly.
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Figure 2. Differences in isometric rates of torque development (RTD), absolute and normalized (RTD/BM), between gymnasts and physical education (PE) students across different time intervals during extension. * p < 0.05, ** p < 0.01.
Figure 2. Differences in isometric rates of torque development (RTD), absolute and normalized (RTD/BM), between gymnasts and physical education (PE) students across different time intervals during extension. * p < 0.05, ** p < 0.01.
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Figure 3. Differences in isometric rates of torque development (RTD), absolute and normalized (RTD/BM), between gymnasts and physical education (PE) students across different time intervals during flexion. * p < 0.05, ** p < 0.01.
Figure 3. Differences in isometric rates of torque development (RTD), absolute and normalized (RTD/BM), between gymnasts and physical education (PE) students across different time intervals during flexion. * p < 0.05, ** p < 0.01.
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Figure 4. Differences in normalized EMG (EMG/EMGmax) between groups across different time intervals during extension and flexion. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 4. Differences in normalized EMG (EMG/EMGmax) between groups across different time intervals during extension and flexion. * p < 0.05, ** p < 0.01, *** p < 0.001.
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Table 2. Means, standard deviations, and one-way MANOVA statistics for absolute and normalized-with-body-mass PT and peak RTD during isometric extension and flexion.
Table 2. Means, standard deviations, and one-way MANOVA statistics for absolute and normalized-with-body-mass PT and peak RTD during isometric extension and flexion.
VariablesGymnastsPE Students
MSDMSDFpη2
Ext_PT (Nm)272.6031.62211.8946.9214.960.0010.38
Flex_PT (Nm)202.3738.74166.7238.225.580.0270.19
Ext_PT/BM (Nm/kg)4.110.432.840.5047.140.0010.66
Flex_PT/BM (Nm/kg)3.050.592.240.4415.520.0010.39
Ext_RTD (Nm/s)2683.56562.612129.51758.574.470.0450.16
Flex_RTD (Nm/s)2627.10961.211938.10707.204.330.0480.15
Ext_RTD/BM (Nm/s/kg)40.8410.4728.639.359.830.0040.29
Flex_RTD/BM (Nm/s/kg)39.9515.2525.978.358.400.0080.26
Ext_EMGmax (mV)769.17165.39564.68198.418.150.0090.25
Flex_EMGmax (mV)795.01186.13582.42190.518.280.0080.26
M: mean; SD: standard deviation; PT: absolute peak torque; PT/BM: peak torque normalized to body mass; RTD: absolute rate of torque development; RTD/BM: rate of torque development normalized to body mass; EMGmax: the maximum RMS of EMG of the agonist muscles; Ext: extension; Flex: flexion.
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Milosis, D.C.; Dallas, C.; Patikas, D.A.; Dallas, G.; Siatras, T. Neuromuscular Assessment of Maximal Shoulder Flexion/Extension Torque Development in Male Gymnasts. Biomechanics 2025, 5, 49. https://doi.org/10.3390/biomechanics5030049

AMA Style

Milosis DC, Dallas C, Patikas DA, Dallas G, Siatras T. Neuromuscular Assessment of Maximal Shoulder Flexion/Extension Torque Development in Male Gymnasts. Biomechanics. 2025; 5(3):49. https://doi.org/10.3390/biomechanics5030049

Chicago/Turabian Style

Milosis, Dimitrios C., Costas Dallas, Dimitrios A. Patikas, George Dallas, and Theophanis Siatras. 2025. "Neuromuscular Assessment of Maximal Shoulder Flexion/Extension Torque Development in Male Gymnasts" Biomechanics 5, no. 3: 49. https://doi.org/10.3390/biomechanics5030049

APA Style

Milosis, D. C., Dallas, C., Patikas, D. A., Dallas, G., & Siatras, T. (2025). Neuromuscular Assessment of Maximal Shoulder Flexion/Extension Torque Development in Male Gymnasts. Biomechanics, 5(3), 49. https://doi.org/10.3390/biomechanics5030049

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