Search Results (433)

Background: Public fitness facilities are high-contact environments that facilitate microbial transfer via shared surfaces; however, temporal dynamics and device-specific contamination patterns remain insufficiently characterized. Methods: A repeated-measures observational study was conducted in a fitness facility over five consecutive weekdays (Monday to Friday). A total of 180 surface samples were collected from 12 gym devices, each sampled three times daily (morning, noon, and evening). Surface-associated cultivable bacteria were recovered using culture-based methods followed by MALDI-TOF MS identification. Ecological metrics, including species richness and Shannon diversity, were calculated, and taxa were classified by origin (skin-associated versus environmental). Device-specific contamination profiles were developed using a composite index incorporating pathogen presence, contamination frequency, and persistence. Temporal trends and predictors of contamination were analyzed using mixed-effects regression models. All statistical analyses were performed in R. Results: A total of 248 bacterial isolates were identified, representing 61 species across 32 families, with a predominance of skin-associated taxa (72.2%). Sampling time point was a strong independent predictor of contamination (adjusted OR for noon vs. morning: 7.19; p < 0.001). While overall microbial diversity remained stable across devices (Shannon index, p = 0.44), substantial heterogeneity was observed in pathogen prevalence, multispecies burden, and persistence. The functional trainer and leg extension showed the highest composite risk scores (42.3%), while the ab crunch machine and upper body ergometer demonstrated significantly increasing contamination trends over the sampling period (p < 0.05). Co-occurrence analysis showed nonrandom microbial associations, with the strongest positive links between Micrococcus luteus and Staphylococcus saprophyticus (Φ = 0.76) and Staphylococcus aureus (Φ = 0.61). Conclusions: Gym equipment surfaces harbor predominantly human-associated microbial communities exhibiting dynamic temporal contamination patterns, and on selected devices, increasing the baseline contamination across consecutive cleaning cycles. The findings indicate that contamination patterns on shared fitness equipment are dominated by taxa commonly associated with human skin and support targeted hygiene interventions focused on frequently contacted devices and periods of elevated contamination. Full article

Human pose detection is fundamental to quantitative sports training analysis in college general education courses, enabling an objective assessment of college students’ movement quality and the early identification of sports injury risks among non-professional athletes. At present, those detectors based on YOLO have encountered difficulties in capturing the continuous movement patterns of college athletes in routine training, maintaining the regression accuracy of different size posture targets, and maintaining the real-time calculation speed in the campus sports environment. Furthermore, most existing pose-estimation frameworks are optimized for general scenes and fail to address the unique challenges of college physical education settings, including non-standard student movements, diverse skill levels, and strict cost constraints for large-scale deployment. In order to solve these problems, we put forward PPLCNet-YOLOv11, which is a simplified human posture-estimation framework designed for college physical education. This model is optimized by three key improvements: (1) replacing the original backbone network with PPLCNet to enhance feature extraction, while strictly observing the strict FLOPs and parameter restrictions; (2) an enhanced Multi-Scale Attention Mechanism (MSAM) that combines adaptive scale perception, hierarchical channel attention, and pose-sensitive spatial attention to better represent elongated anatomical structures and multi-scale pose cues; and (3) an improved enhanced IoU loss function that incorporates scale-aware and aspect-ratio-aware penalty terms to refine the bounding box adjustment for atypical and sports-specific gestures. Experiments on both a dedicated college student sports pose dataset and two public benchmark datasets (COCO Keypoints 2017 and MPII Human Pose) demonstrate that PPLCNet-YOLOv11 achieves 77.8% mAP@0.5 and 37.09% mAP@0.95 based on the campus dataset, with 82.34% precision and 75.00% recall, while requiring only 2.62 M parameters and 6.38 GFLOPs. Extensive inference speed tests show that the model achieves 127 FPS on an NVIDIA RTX 4090 GPU, 38 FPS on an Intel i7-12700 CPU, and 16 FPS on a Jetson Nano edge device, meeting the real-time requirements of campus sports monitoring. Compared with mainstream lightweight YOLO variants and state-of-the-art specialized pose-estimation models, our proposed method improves mAP@0.5 by 4.93–12.6 percentage points based on the campus dataset. All experiments were repeated five times with different random seeds, and we report mean values with standard deviations and statistical significance tests to ensure result reliability. These results indicate that PPLCNet-YOLOv11 provides an accurate and resource-efficient solution for real-time pose evaluation in college physical training. Full article

Background/Aim: Motor skill acquisition is the foundation of athletic performance, from the novice learning a new technique to the elite athlete executing complex movements automatically under pressure. Although classical models have defined the neural substrates of motor control—the cerebellum for error correction, the basal ganglia for action selection, and the primary motor cortex (M1) for execution—emerging evidence suggests that motor learning is the result of the dynamic interaction of multiple parallel processes rather than a linear hierarchy. This narrative review integrates classical neuroanatomical knowledge with contemporary findings on multisite plasticity, with a particular focus on sport-specific adaptations. Methods: We examined three core learning mechanisms operating in parallel: error-based learning (cerebellar-dependent, driven by sensory prediction errors), reinforcement learning (striatal-dependent, driven by reward prediction errors and dopamine), and use-dependent learning (cortical-dependent, driven by mere repetition). We also summarize the biochemical pathways supporting these learning processes, including glutamatergic LTP-like cortical plasticity, cerebellar mGluR1–PKC–LTD signaling, dopaminergic corticostriatal plasticity, BDNF–TrkB-dependent neurotrophic mechanisms, growth-factor signaling, and exercise-induced muscle–brain communication. Results: We then propose a spatiotemporal model in which the relative contribution of each network shifts dynamically across the three stages of skill acquisition, from the early cognitive/strategic phase to the late automatic phase characteristic of elite performance. At the molecular level, these stage-dependent adaptations are supported by synaptic strengthening and weakening mechanisms, reward-dependent dopamine signaling, neurotrophic and growth-factor-mediated remodeling, and peripheral metabolic/myokine signals that modulate brain plasticity during training and recovery. Special attention is given to contextual and sport-specific adaptations, using the paradigmatic example of elite swimmers who demonstrate enhanced short-interval intracortical inhibition (SICI) selectively in the aquatic environment, reflecting long-term sport-induced neuroplasticity. Conclusions: Understanding these dynamic network mechanisms has direct implications for coaching, training periodization, and the development of targeted neuromodulatory interventions to accelerate skill acquisition and optimize athletic performance. Full article

Organized youth sport has considerable potential to promote young people’s physical health, well-being, and personal and social development. However, these positive outcomes are not guaranteed. When sport environments are poorly structured, excessively performance-oriented, or inadequately supervised, participation may also lead to exclusion, excessive pressure, and other harmful experiences. Creating genuinely youth-centered sport environments is therefore essential, both to foster positive developmental outcomes and to prevent transgressive behavior. Despite growing attention to these issues, the field of youth sport lacks an overarching framework for the development of pedagogically sound, development-oriented, and socially safe sport environments. This study aimed to develop an overarching framework that integrates the developmental, motivational, and safeguarding dimensions of youth sport into one coherent model for creating optimal learning environments. Through an iterative process, a practice-based framework was developed, theoretically grounded, and initially operationalized. Early versions of the framework were subsequently examined for conceptual alignment through expert opinions, focus groups, and group discussions with existing European youth sport initiatives. This process resulted in the development of the Youth Sport Compass (YSC), a coherent conceptual and practical framework designed to support youth-centered and socially safe sport environments. Experts from different countries and disciplines considered the framework highly relevant, conceptually robust, and broadly applicable in practice. The YSC provides a strong conceptual and practical foundation for coaches, sport organizations, and policymakers seeking to create pedagogically sound, youth-centered, and socially safe sport environments. Although the YSC is firmly grounded in theory and practice, it has yet to be empirically validated. Further research is needed to assess its validity and practical effectiveness. Full article

This study explored parental concerns regarding their sons’ experiences in a professional football academy, using a case study methodology over a twelve-year period. Drawing on over 60 interviews with parenting pairs, the research identified that concerns were shaped by internal (e.g., personal beliefs), semi-internal (e.g., peer influence, agent input), and external (e.g., social media, educational trends) information sources. These sources often led to misaligned expectations between parents and the academy. The findings highlighted the prevalence of misinformation. In response, a series of targeted interventions were implemented, including structured communication strategies, shared mental models (SMMs), and a refined parent–academy code of conduct. These changes facilitated more integrated parent–athlete–coach relationships and improved clarity around developmental processes. Although causality cannot be established, the frequency of parental complaints decreased over time. This study emphasizes the need for academies to proactively engage parents as key stakeholders through clear, consistent, and evidence-informed communication, ultimately supporting a more coherent developmental experience for athletes. These findings have broad implications for talent development environments aiming to balance athlete and parent welfare with high-performance goals. Full article

Background: Biological maturation is a major determinant of physical performance in youth football, although the previous evidence suggests that training context may influence maturation–performance associations. This study investigated the association between biological maturation and physical performance in youth football players from professional and non-professional settings. Methods: A total of 302 male football players (Under-10 to Under-14) from a professional academy (n = 122) and non-professional clubs (n = 180) participated. Biological maturation was estimated using maturity offset and age at peak height velocity (aPHV). Physical performance was assessed through standing broad jump, T-test agility, and sit-and-reach tests. General Linear Models and stratified correlation analyses were used to examine the interaction between maturation, age category, and training environment. Relative age distribution was also described. Results: Professional academy players demonstrated superior explosive power, agility, and flexibility across most age categories compared with non-professional players. Significant associations between biological maturation and physical performance were observed mainly in the non-professional environment, particularly for agility and explosive power, whereas few significant relationships emerged in the professional academy. Significant interactions between training environment, age category, and maturation status were found for all performance measures, with the strongest effect observed for agility. A relative age effect emerged only in the older professional categories. Conclusions: Associations between biological maturation and physical performance differed according to training environment in youth football players. Stronger maturation–performance relationships were generally observed in non-professional settings, whereas weaker associations emerged in the professional academy. However, due to the cross-sectional design and the likely interdependence between maturation, selection, and training exposure, causal interpretations cannot be inferred. Full article

The aim of this systematic review was to evaluate the validity and accuracy of wearable technologies used for monitoring physiological metrics in team-sport athletes. A systematic literature search was conducted in PubMed and Scopus databases, with additional studies identified through supplementary searching. Studies published between 2015 and 2025 were included if they assessed wearable devices in team-sport populations and compared their measurements with gold-standard methods. A total of eleven studies met the inclusion criteria. The findings indicate that heart rate monitoring demonstrates consistently high validity across different wearable devices, particularly in controlled laboratory conditions. In contrast, energy expenditure estimation shows substantial variability and systematic underestimation, especially during high-intensity and intermittent activities typical of team sports. VO₂max estimation presents mixed validity depending on device type and testing protocol, while respiratory frequency measurement demonstrates high agreement with gold-standard methods when assessed using specialized devices. Overall, wearable technologies provide valuable insights into athlete monitoring; however, their accuracy varies considerably depending on the physiological parameter and testing environment. These findings highlight the need for improved validation protocols and caution in the application of wearable-derived data in high-performance team-sport settings. Full article

Background: Advances in monitoring systems featuring wearable sensors, computer vision, and artificial intelligence (AI) have been increasingly used in sports science and rehabilitation practices as a means of movement pattern analysis, injury prevention, and training optimization. These technologies are becoming essential components of athlete-performance analysis and rehabilitation-monitoring systems designed to support biomechanical assessment, athlete development, and movement-quality evaluation. Athlete-performance analysis and rehabilitation monitoring increasingly rely on intelligent multimodal sensing systems capable of continuously evaluating movement quality, biomechanical patterns, training execution, and recovery progress. Human activity recognition (HAR) serves as a key enabling technology for these applications by providing automated assessment of human movement using wearable and vision-based sensing modalities. Therefore, the purpose of this study was to develop and evaluate an attention-based multimodal framework that integrates wearable inertial sensing and RGB video analysis for robust athlete-performance assessment and rehabilitation monitoring through accurate recognition of human movement patterns. Methods: Athlete-performance analysis and rehabilitation monitoring combining inertial sensor data and RGB-based visual information was introduced. Inertial signals were segmented with adaptive windowing, whereas silhouette refinement was performed to analyze motion structures from visual inputs in support of athlete-performance analysis and rehabilitation monitoring. Temporal, spatial, and motion features such as trajectory, orientation, and skeleton-based space-time representations were calculated from multimodal inputs. The proposed framework was designed to capture complex movement dynamics associated with rehabilitation exercises and sports-related motion patterns across heterogeneous sensing environments. Extracted features were then combined and optimized with a multimodal feature fusion approach, while the Ranger optimization algorithm was utilized during the process. An attention-based deep learning classifier was implemented to classify movement activities. Results: The results showed that the proposed framework reached accuracy scores of 88.40% and 87.96% on the VIDIMU dataset and the UTD-MHAD dataset respectively. Recognition performance across both inertial and vision-based modalities provided greater robustness than single-modality solutions. The integration of wearable sensing and computer vision modalities further improved the ability of the framework to analyze complex movement behaviors under varying execution conditions and environmental variations. Conclusion: The proposed multimodal framework provides a foundation for intelligent athlete-performance and rehabilitation-monitoring systems by integrating wearable sensing, computer vision, and attention-based artificial intelligence for robust movement analysis. The findings highlight its potential to support biomechanical assessment, movement-quality evaluation, training-performance monitoring, rehabilitation tracking, and injury-risk management in modern sports and healthcare environments. Full article

Resistance training (RT) is commonly used to enhance neuromuscular performance and sprint swimming outcomes. However, the optimal relative load for elite junior swimmers remains unclear. In particular, little is known about whether very low relative loads can elicit meaningful adaptations while minimizing neuromuscular fatigue in athletes exposed to high concurrent training demands. Therefore, the aim of this study was to compare the effects of two land-based RT programs differing only in relative load intensity (40–50% vs. 55–65% 1RM), performed with maximal intended concentric velocity, on strength, jumping ability, and 50 m freestyle swimming performance in elite junior swimmers. Eighteen elite junior swimmers (15.6 ± 0.9 years) from a national high-performance program were randomly assigned to a low-load (40–50% 1RM; n = 9) or moderate-load (55–65% 1RM; n = 9) group. Both groups completed an 8-week RT program (2 sessions·week⁻¹) with identical exercise selection, volume, execution velocity, and in-water training load. Neuromuscular performance (countermovement jump, squat, bench press, and pull-up strength) and swimming performance (50 m freestyle from the starting block and in-water start) were assessed pre- and post-intervention. Both RT protocols improved squat and bench press strength and 50 m freestyle performance, whereas significant improvements in countermovement jump, pull-up strength, and maximal pull-up repetitions were observed only in the low-load group. Significant group × time interactions were found for countermovement jump, maximal number of pull-up repetitions, and 50 m freestyle performance from the starting block, indicating more favorable changes over time in the low-load group. In conclusion, both low- and moderate-load high-velocity RT improved neuromuscular and 50 m freestyle performance outcomes in elite junior swimmers. However, the low-load RT (40–50% 1RM) appeared to provide additional benefits in specific outcomes (i.e., jumping, pull-ups, and 50 m performance from the starting block). These findings suggest that relatively low loads may be a practical alternative to moderate-load RT in high-volume swimming training environments. Full article

Anterior cruciate ligament (ACL) injuries remain a leading cause of morbidity in athletic populations, with 70–80% occurring through non-contact mechanisms driven by biomechanical risk factors including knee valgus (>10°), low knee flexion (<30°), tibial internal rotation (>20°), and loading asymmetry (>15°), yet implementation of evidence-based neuromuscular training (which reduces injury risk by 50–70%) remains limited due to barriers in identifying at-risk individuals through accessible field-based screening. This narrative review synthesizes motion analysis technologies spanning laboratory-based optical systems (marker-based), wearable inertial measurement units (IMUs), computer vision and marker-less pose estimation, force plate and pressure-sensitive insole systems, and integrated drone-based field assessment platforms to address this critical gap. We present a three-tier clinical screening framework that progresses from basic anthropometric and single-plane video analysis to multi-modal biomechanical assessment using real-time kinematic feedback. As an illustrative example of emerging field-deployable technology, an integrated drone-based motion capture and smart insole system combining 4K video capture, AI-driven 3D motion reconstruction, and plantar pressure mapping is described to demonstrate how laboratory-quality biomechanical assessment can be achieved in ecologically valid field settings. This evidence-based review addresses current gaps between laboratory research and practical field deployment, with emphasis on cost-effectiveness, accessibility, and clinical utility for ACL injury prevention in diverse sporting environments. Full article

While much of the current research on early specialization focuses on physical outcomes, training models, and policy implications, little is known about how athletes themselves make sense of their developmental experiences. This study aims to examine how ice hockey players perceive and experience early specialization within competitive youth sport contexts, with the goal of generating a nuanced, inductively grounded understanding of athlete development from the athlete perspective. A qualitative study design was used where eight current and former ice hockey players with experience of early specialization participated. Data were collected using semi-structured interviews and analyzed using qualitative conventional content analysis. Three overarching themes emerged, highlighting experiences of loneliness, pressure, and elevated expectations within elite sport environments, alongside the vital importance of support networks and team community: ‘Thrown into adulthood with premature expectations’, ‘Balancing Support and Pressure in Athlete Development’, and ‘The Struggle Between Dream and Reality’. Players described feeling pressured, isolated, and prematurely professionalized, often at the expense of personal development. The findings highlight the psychological and structural challenges of early specialization in elite ice hockey. While support systems played a crucial role, they also contributed to performance anxiety and external expectations. These insights underscore the need for youth sport systems that prioritize long-term athlete well-being over short-term success. Full article

Interpreting doping prevalence estimates generated through indirect estimation models (IEMs) remains challenging for sport policy and governance due to the wide variation in reported rates and methodological complexity. In this study, we combined a critical appraisal of the methodological and epistemic developments of IEM applications to doping prevalence with a bibliometric analysis of publication trends, citation patterns, and collaboration networks, using a convergent parallel mixed-methods design. Across 52 records published between 2002 and 2026, this study maps the scientific landscape of IEM-based doping prevalence research. Findings show that IEM-based prevalence research is methodologically sophisticated yet institutionally dispersed and largely Eurocentric, reflecting a field still consolidating its standards and disciplinary identity. Over time, the focus has shifted from reporting prevalence rates to methodological critique and re-analysis of existing datasets. Reported prevalence estimates, ranging from 0 to 57.1%, are highly sensitive to modelling assumptions about athlete behaviour in complex survey environments. While this trend strengthens rigour, it also complicates evidence synthesis for policy actors and risks undermining trust in IEM-based estimates if poorly communicated. Anti-doping organisations and researchers should treat IEM-derived prevalence as bounded indicators rather than definitive rates and integrate prevalence evidence with contextual data for transparent policy and public communication. Full article

Accurate detection of initial contact (IC) during side-cutting is essential for evaluating m. semitendinosus (ST) pre-activity, a protective mechanism against ACL injury in team sport athletes. This study developed two insole pressure sensor (IPS) algorithms—a body weight-based and a criteria-based algorithm—for IC detection and evaluated their agreement with force-plate-derived IC based on vertical ground reaction forces (vGRF). Twenty-six adult female athletes performed sport-specific side-cutting while IPS, vGRF, and ST electromyography were recorded. IPS-derived IC events were compared with vGRF-derived IC, and ST pre-activity within 50 ms prior to IC was compared between methods. Agreement and limits of agreement (LoA) were evaluated using Bland–Altman analysis. The body weight-based IPS algorithm showed a systematic delay in IC detection of 9.2 ms (LoA: 4.1 to 14.3 ms) and a −3.5 percentage point bias in ST pre-activity (LoA: −8.9 to 1.9% of MVC). In contrast, the criteria-based IPS algorithm, demonstrated minimal bias in IC detection (−0.1 ms; LoA: −3.5 to 3.4 ms) and ST pre-activity (−0.1% MVC; LoA: −1.9 to 1.7% of MVC). These findings suggest the criteria-based IPS algorithm enables accurate IC detection, supporting its potential for practical monitoring of ST pre-activity during sports-specific side-cutting outside laboratory environments. Full article

Background: Nutrient-enriched sports foods can support efficient nutrient intake in specific circumstances in athletic nutrition management, such as during competition, when training away from the usual environment, or during periods of weight management. Despite their widespread availability, sports foods are not always used appropriately, necessitating tools to support informed product selection. Objective: This study aimed to characterize sports foods consumed by Japanese athletes and to develop a Japanese sports food exchange list to facilitate product selection based on target nutrient requirements. Methods: Seven sports food categories commonly used in Japanese sports settings were examined: sports drinks, energy jellies, energy bars, energy gels, protein drinks, protein bars, and protein powders. Following the methodology of Spain’s sports food exchange list, development proceeded in two stages. First, suppliers were selected based on INFORMED CHOICE certification or listing on the Japan Anti-Doping Agency’s product information website, with input from experienced sports dietitians. Subsequently, 523 products were classified into subcategories based on nutrient content per unit using established statistical criteria, including the mean, standard deviation, coefficient of variation, and z-values. Results: After excluding products with z-values outside ±2 or compositions deemed unsuitable for carbohydrate or protein supplementation, 498 products from 36 suppliers were classified into 24 subcategories. Japanese sports foods exhibited broad distributions in nutrient composition, variability derived from ingredient differences, and a high proportion of plant-based protein powders. Conclusions: This study developed a Japanese sports food exchange list comprising 498 products across 24 subcategories, enabling evidence-based product selection aligned with the nutrient intake goals of Japanese athletes. Full article

With society’s ever-growing concern for animal welfare, the equestrian industry has focused on passing and enforcing new rules to protect the main athlete, the horse. In jumping, courses go by quickly, with judges using the occurrence of conflict behaviours to assess any welfare breach. This study aimed to evaluate the overall frequency of such behaviours in Brazilian Sport Horses during elite show jumping competitions in Brazil. Conflict behaviour displays were analyzed in 120 different horse–rider pairs in jumping competitions in Brazil. All videos were observed at a slowed-down speed, with the frequency of behaviours being recorded. The observed behaviours included head shaking, tail swishing, neck hyperflexion, excessive pulling on the reins, kicking, bucking, rearing, and disobedience. All horses (100%) presented at least one type of conflict behaviour, with head shaking (100%, n = 120, IQR 3–7, range 1–18) being the most common one (p < 0.001) and tail swishing (45.83%, n = 55, IQR 1–10, range 1–29) being the second most common (p < 0.001). Most horses showed only one (41.67%, n = 50) or two (43.33%, n = 52) different types of behaviours, with few episodes of each throughout the course. Those findings were in line with studies in other disciplines, as the competition environment offers a series of challenging and stressful situations. The low levels of conflict observed in most horses indicate that the current horse welfare rules are working and must continue to be reinforced to consistently protect the horses. Full article