The bench press exercise (BP) plays an important role in recreational and professional training, in which muscle activity is an important multifactorial phenomenon. The objective of this paper is to systematically review electromyography (EMG) studies performed on the barbell BP exercise to answer the following research questions: Which muscles show the greatest activity during the flat BP? Which changes in muscle activity are related to specific conditions under which the BP movement is performed? PubMed, Scopus, Web of Science and Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library were searched through June 10, 2016. A combination of the following search terms was used: bench press, chest press, board press, test, measure, assessment, dynamometer, kinematics and biomechanics. Only original, full-text articles were considered. The search process resulted in 14 relevant studies that were included in the discussion. The triceps brachii (TB) and pectoralis major (PM) muscles were found to have similar activity during the BP, which was significantly higher than the activity of the anterior deltoid. During the BP movement, muscle activity changes with exercise intensity, velocity of movement, fatigue, mental focus, movement phase and stability conditions, such as bar vibration or unstable surfaces. Under these circumstances, TB is the most common object of activity change. PM and TB EMG activity is more dominant and shows greater EMG amplitude than anterior deltoid during the BP. There are six factors that can influence muscle activity during the BP; however, the most important factor is exercise intensity, which interacts with all other factors. The research on muscle activity in the BP has several unresolved areas, such as clearly and strongly defined guidelines to perform EMG measurements (e.g., how to elaborate with surface EMG limits) or guidelines for the use of exact muscle models.

This systematic review and meta-analysis investigates the application of artificial intelligence (AI) in sports performance analysis. Sixteen peer-reviewed studies spanning 13 distinct sports disciplines were included, employing a variety of AI techniques—from classical machine learning algorithms to advanced deep learning and computer vision models. Methods applied encompassed Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, reinforcement learning, and predictive modeling architectures. The pooled average classification accuracy was 87.78% (95% CI: 82.66–92.90), although substantial heterogeneity was observed across studies (I² = 93.75%). Computer vision and deep learning-based approaches were associated with higher performance metrics in several studies, particularly in movement-intensive sports such as tennis and basketball. Nevertheless, several challenges were identified, including lack of standardization in model evaluation, limited algorithmic transparency, and difficulties in generalizing findings from controlled laboratory environments to real-world competitive settings. The results underscore the promising role of AI in optimizing training protocols, supporting tactical decisions, and enhancing injury prevention strategies. Further research is warranted to address the ethical, methodological, and practical considerations surrounding the deployment of AI in sports contexts.

The primary objective of this study was to determine a relationship between aerobic capacity ([Formula: see text]O2max) and fatigue from high-intensity skating in elite male hockey players. The subjects were twenty-four male members of the senior national ice hockey team of Poland who played the position of forward or defence. Each subject completed an on-ice Repeated-Skate Sprint test (RSS) consisting of 6 timed 89-m sprints, with 30 s of rest between subsequent efforts, and an incremental test on a cycle ergometer in the laboratory, the aim of which was to establish their maximal oxygen uptake ([Formula: see text]O2max). The analysis of variance showed that each next repetition in the 6x89 m test was significantly longer than the previous one (F5,138=53.33, p<0.001). An analysis of the fatigue index (FI) calculated from the times recorded for subsequent repetitions showed that the value of the FI increased with subsequent repetitions, reaching its maximum between repetitions 5 and 6 (3.10±1.16%). The total FI was 13.77±1.74%. The coefficient of correlation between [Formula: see text]O2max and the total FI for 6 sprints on the distance of 89 m (r =-0.584) was significant (p=0.003). The variance in the index of players' fatigue in the 6x89 m test accounted for 34% of the variance in [Formula: see text]O2max. The 6x89 m test proposed in this study offers a high test-retest correlation coefficient (r=0.78). Even though the test is criticized for being too exhaustive and thereby for producing highly variable results it still seems that it was well selected for repeated sprint ability testing in hockey players.

Physical balance is an important factor in sport. Neurofeedback (EEG biofeedback) can be used to improve concentration and focus. The present study investigated and determined the impact of neurofeedback training on dynamic balance in judo. Eighteen judokas voluntarily participated in this study....

Gołaś, A, Maszczyk, A, Pietraszewski, P, Stastny, P, Tufano, JJ, and Zając, A. Effects of pre-exhaustion on the patterns of muscular activity in the flat bench press. J Strength Cond Res 31(7): 1919–1924, 2017—Pre-exhaustion (PE) has been applied in resistance training (RT) to manipulate the order of performing 2 resistance exercises, a single-joint exercise to momentary exhaustion, followed by a multi-joint movement that includes the same muscle group. This method ensures greater recruitment of muscles or muscle groups in the multi-joint exercise to further increase muscle strength and overcome strength plateaus. The purpose of the present study was to investigate muscle activity by electromyography during high-intensity (95% of 1 repetition maximum [RM]) bench press (BP), before and after PE of the pectoralis major (PM), anterior deltoid (AD), and triceps brachii (TB) muscles to determine the effects of PE of the prime movers. Eight healthy athletes, experienced in RT, participated in the study. There were 4 sessions in the experiment. Session 1 was aimed at determination of 1RM during a flat BP. Sessions 2, 3, and 4 consisted of performing a BP after PE of the muscles studied by the incline dumbbell fly, front deltoid raise, and lying triceps extension exercise. Peak concentric TB activation after TB PE (mean ± SD, 147.76 ± 18.6%) was significantly greater by analysis of variance (η ² = 0.82, F = 5.45, p = 0.004) compared with peak TB activation (114.77 ± 19.4%) before TB PE. The statistical analysis for PM and AD did not show any significant differences. Coaches should not expect the usefulness of PE protocol to elicit higher PM or AD activity or fatigue, but they can use it to increase TB activity before high-intensity BP exercise.

The Development and Prediction of Athletic Performance in Freestyle Swimming: This paper analyses the dynamics of changes between the performances of elite freestyle swimmers recorded at particular Olympic Games. It also uses a set of chronologically ordered results to predict probable times of swimmers at the 2012 Olympic Games in London. The analysis of past performances of freestyle swimmers and their prediction have revealed a number of interesting tendencies within separately examined results of men and women. Women's results improve more dynamically compared with men's. Moreover, the difference between women's and men's results is smaller, the longer the swimming distance. As both male and female athletes tend to compete more and more vigorously within their groups, the gap between the gold medallist and the last finisher in the final is constantly decreasing, which provides significant evidence that this sport discipline continues to develop.