Search Results (1,557)

Background: Acute compartment syndrome (ACS) is a limb-threatening surgical emergency most commonly associated with fractures or high-energy trauma. Non-fracture-related ACS in athletes is uncommon and may lead to delayed diagnosis. Repetitive blunt trauma during combat sports has rarely been described as a potential mechanism. Case Methods: The case concerns a 21-year-old elite-level kickboxing athlete who developed acute compartment syndrome of the left lower leg following repeated calf kicks sustained during sparring. The patient presented with rapidly progressive calf pain, swelling, compartment firmness, paresthesias and weight bearing difficulties. CT angiography demonstrated diffuse edema of the posterior compartments associated with a large intramuscular soleus hematoma without active arterial bleeding. Results: In view of the severity of the symptoms and the characteristic clinical presentation, an emergency fasciotomy was performed in operating room. Progressive closure was achieved using the vessel loop shoelace technique, allowing gradual tension-free closure. Wound healing progressed without infection, and physiotherapy was introduced with joint mobilization. The patient achieved full functional recovery after 6 months. Conclusions: This case illustrates an atypical etiology of ACS—repetitive targeted calf strikes—and underscores the importance of early recognition even in the absence of fracture or major trauma. Clinical vigilance remains paramount, and prompt surgical intervention is critical to prevent irreversible muscle and nerve damage. Awareness of such mechanisms is particularly relevant for clinicians managing athletes in combat sports. To our knowledge, this is the first documented case of ACS secondary to repeated calf kicks in kickboxing. Full article

Training distress is a multifactorial psychophysiological response resulting from the interaction of sustained high-intensity training, insufficient recovery, and additional psychosocial stressors. It manifests through mood disturbance, elevated perceived stress, fatigue, sleep disruption, and physical symptoms, and represents a precursor to maladaptive outcomes such as overtraining syndrome. The Multicomponent Training Distress Scale (MTDS) integrates these dimensions into a single monitoring framework; however, no validated Italian version has been available. The present study aimed to develop and provide a validation of the Italian Multicomponent Training Distress Scale (IMTDS). The IMTDS was administered to 536 Italian-speaking recreational and competitive sport participants (276 males, 260 females; age range = 16–35 years, M = 25.31, SD = 5.62). Exploratory Structural Equation Modeling supported the hypothesized six-factor structure (Depression, Vigor, Physical Symptoms, Sleep Disturbances, Stress, Fatigue), demonstrating acceptable model fit (CFI = 0.97, TLI = 0.92, RMSEA = 0.10). Internal consistency was satisfactory to high across subscales (ω = 0.82–0.88), and test–retest analyses indicated temporal stability. Intercorrelations among dimensions were consistent with theoretical expectations. These findings provide evidence that the IMTDS is a reliable instrument for monitoring training distress in Italian-speaking athletes. Full article

Sports-related injuries remain a major challenge in team sports, with important consequences for athlete health, performance, and team success. Recent advances in artificial intelligence (AI) and sensor-based monitoring technologies have enabled the integration of large volumes of training, competition, and physiological data to support injury prediction and risk modelling. However, the literature is characterised by substantial methodological diversity, limiting the ability to draw consistent conclusions. Hence, this scoping review aimed to map the existing evidence on the use of AI and sensor-based monitoring technologies for injury prediction and risk modelling in team sports, and to identify key methodological trends and research gaps. The scoping review was conducted in accordance with the PRISMA-ScR guidelines. Systematic searches were performed in PubMed and Scopus. Eligible studies included team-sport athletes and applied AI or machine learning approaches to predict injury occurrence, injury risk, or related outcomes using data derived from wearable or monitoring systems. Data were charted on study characteristics, sports and competition level, data sources, modelling techniques, validation strategies, and performance metrics. The database search yielded 123 records (PubMed: n = 37; Scopus: n = 86). After screening and eligibility assessment, 11 studies met the inclusion criteria. Most studies focused on football and rugby and relied primarily on wearable-derived data, particularly GPS and inertial sensor outputs. Common predictors included external workload variables, training exposure, previous injury history, and, in some studies, wellness or physiological markers. A wide range of models was reported, including logistic regression, decision trees, random forests, support vector machines, and neural networks. Validation strategies and reported performance varied markedly, and external validation was rarely undertaken. Across the included studies, injury risk was most consistently associated with external workload metrics, previous injury history, and internal or physiological indicators of recovery and readiness. However, current models remain limited by heterogeneous methodologies, single-team datasets, and the lack of external validation. Future research should emphasise multimodal data integration and multi-centre validation to develop reliable, interpretable, and practically applicable AI-based injury prediction systems. Full article

In tennis, where performance is governed by complex kinetic chain interactions, objective skill classification is vital for coaching and talent identification. This study presents a hierarchical deep learning framework leveraging synchronized bilateral Inertial Measurement Unit (IMU) data from 39 participants (11 elite, 28 amateur). The proposed system successfully distinguishes expertise levels across a total of 4594 strokes, including augmented samples. A hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) architecture was developed to autonomously extract spatiotemporal features from the raw kinematic signals of forehand, backhand, service, and volley strokes. The proposed model achieved an accuracy of 95.54%, significantly outperforming both traditional machine learning and state-of-the-art deep learning benchmarks. Qualitative t-distributed Stochastic Neighbor Embedding (t-SNE) analyses revealed that elite athletes form highly homogeneous clusters in the feature space. Furthermore, quantitative Asymmetry Index assessments confirmed that professionals exhibit superior bilateral coordination stability. These findings demonstrate that the proposed end-to-end system offers a robust, field-applicable solution for identifying technical excellence. It provides coaches with reliable digital biomarkers, thereby overcoming the limitations of subjective visual observation. Full article

Background: Life Kinetics training, a multimodal intervention integrating coordinated motor tasks with cognitive challenges, has been proposed as a method to enhance neurocognitive and sport-specific performance. This study examined the effects of an 18-session Life Kinetics program on concentration, working memory, and service performance in junior and intermediate badminton athletes. Methods: Forty athletes (20 junior, 20 intermediate) were included in the final analysis following random allocation to Life Kinetics or control groups. The intervention group performed Life Kinetics training in addition to regular badminton practice for six weeks, while the control group maintained standard training. Outcomes included concentration (Concentration Grid Test), working memory (Digit Span Test), and short- and long-service performance. Data were analyzed using mixed-design ANOVA to assess Group × Time (pre–post) effects, with statistical significance set at p < 0.05. Results: Significant Group × Time interaction effects were observed for concentration (F(1, 38) = 152.40, p < 0.001, ηp² = 0.80), working memory (F(1, 38) = 168.70, p < 0.001, ηp² = 0.82), short-service performance (F(1, 38) = 181.20, p < 0.001, ηp² = 0.83), and long-service performance (F(1, 38) = 210.50, p < 0.001, ηp² = 0.85). The Life Kinetics group demonstrated substantial improvements across all outcomes, whereas the control group showed minimal changes. Improvements were observed in both junior and intermediate athletes, with variations across outcomes. Exploratory EEG observations suggested a shift toward higher-frequency spectral activity following the intervention. Conclusions: Life Kinetics training was associated with significant improvements in cognitive function and service performance in badminton athletes. These findings support the integration of cognitive–motor training into athlete development programs. However, EEG findings should be interpreted cautiously due to methodological limitations, and future research using larger samples and advanced neuroimaging techniques is warranted. Full article

Background and Clinical Significance: This case highlights the management of chronic extensor carpi ulnaris (ECU) tenosynovitis in a patient exposed to non-traditional wrist-loading activities. Exercise therapy rehabilitation is well established in shoulder and knee tendinopathies, although it remains less well described for wrist tendinopathies beyond De Quervain’s disease. Moreover, the patient’s active engagement in non-traditional, wrist-intensive sports such as handstands, slacklining, and yoga may have contributed to the development and persistence of chronic extensor carpi ulnaris (ECU) tenosynovitis. Unlike more common ECU injuries observed in tennis or golf players, this case demonstrates how ECU tenosynovitis can develop in less conventional sports. It adds to the scientific literature by showing that chronic ECU tenosynovitis can be effectively managed through non-surgical rehabilitation tailored to the specific needs of the patient, in particular by using exercise therapy. Case Presentation: The patient presented with chronic left wrist pain, especially during ulnar deviation and resisted ECU testing, following two traumatic events. Examination revealed limited range of motion caused by pain, particularly in flexion, extension, and both ulnar and radial deviations. Ultrasound imaging confirmed ECU tenosynovitis with mild inflammation of other wrist tendons and a small synovial cyst on radio-scapho-lunate level. ECU stability during forearm rotation was confirmed both clinically and by ultrasound.  The diagnosis of chronic ECU tenosynovitis was managed conservatively with a targeted rehabilitation program focused on isometric strengthening and progressive resistance exercises. Over one month, the patient demonstrated marked improvement in wrist strength, pain reduction, and functional capacity, allowing for a gradual return to sporting activities. Conclusions: The main takeaway from this case is that chronic ECU tenosynovitis can be successfully managed through individualized, conservative treatment based on exercise therapy. Early intervention, patient adherence, and rehabilitation tailored to the athlete’s specific demands are crucial for recovery, even in chronic cases, without the need for surgical intervention. Full article

Drag-reducing coating technology is a core approach to enhancing the performance of ice and snow sports equipment. By regulating the interfacial characteristics between the equipment surface and the ice or snow medium, it significantly reduces frictional resistance during motion, thereby optimizing athletes’ speed performance and control precision. This paper aims to review the current research status and challenges in this technological field. The review first elaborates on the fundamental principles of applying drag-reducing coatings to key equipment such as skis, sleds, and ice skates, covering current mainstream coating material systems, key preparation processes, and comprehensive performance evaluation methods. Furthermore, integrating multidisciplinary advances in surface engineering, fluid dynamics, and materials science, this review specifically examines how these disciplines can be harnessed to address the unique tribological challenges of snow/ice interfaces. It focuses on cutting-edge research directions such as micro-nano-structured coatings driven by biomimetic design concepts and smart coatings with environmental responsiveness. By synthesizing existing research achievements and potential technological bottlenecks, this paper aims to provide a systematic, theoretical basis and innovative ideas for the future development of a new generation of high-performance, intelligent ice and snow sports equipment. Full article

Background: Gender discrimination in sport remains a persistent global issue, reflected in women’s limited participation, leadership representation, media visibility, salary equity, and personal safety. These forms of discrimination also negatively affect athletes’ psychological well-being, mental health, and overall sports experience. Despite growing scholarly attention over the past three decades, a comprehensive quantitative synthesis of this research area has been lacking. Methodology: A bibliometric analysis of 397 peer-reviewed documents published between 1995 and 2026 was conducted using the Scopus database. Data were analysed through the Bibliometric R package 4.2.1 and Biblioshiny interface. Science-mapping techniques including keyword co-occurrence, thematic clustering, thematic evolution, and collaboration network analysis were combined with performance indicators such as annual publication output, leading sources, author productivity, and citation impact. Results: Scientific production increased markedly after the mid-2010s, involving 187 sources and 1106 authors, with rising collaboration and citation influence. Core research themes included gender inequality, leadership exclusion, media representation, harassment and abuse, and structural discrimination in sports systems. Importantly, many of these themes are directly linked to reduced athlete well-being, including increased stress, anxiety, and decreased participation. Recent thematic developments highlighted intersectionality, safeguarding, inclusion, governance, and athlete welfare. Conclusion: Research on discrimination against women in sport has evolved into a multidisciplinary, policy-relevant field. Addressing gender discrimination is essential not only to achieving equity but also to improving athletes’ subjective well-being and long-term participation in sport. However, significant gaps remain, particularly in Global South contexts and intervention-based studies, indicating the need for stronger evidence-driven strategies to advance gender equity, inclusion, and ethical governance in sport. Full article

Background: Visio-spatial skills (VSS) are essential perceptual-cognitive skills that enable athletes to process visual information, interpret spatial relationships, and execute appropriate motor responses in dynamic sporting environments. In combat sports, athletes must rapidly anticipate and react to an opponent’s actions, making well-developed VSS crucial for optimal performance. Although boxing, karate, and taekwondo share similar competitive characteristics, each discipline presents distinct technical and perceptual demands that may influence the development of specific VSS profiles. This study aimed to investigate whether significant differences exist in VSS profiles among boxing, karate, and taekwondo athletes. Methods: A comparative cross-sectional design was used involving 150 amateur combat sport athletes, 50 boxers, 50 karate athletes, and 50 taekwondo athletes. Participants were assessed using a VSS test battery measuring six variables: accommodation facility (AF), saccadic eye movement (SEM), speed of recognition (SR), (HEC), peripheral awareness (PA), and visual memory (VM). Data was analyzed using one-way ANOVA with η², ω², and Cohen’s f effect sizes, and principal component analysis (PCA). Results: One-way ANOVA revealed statistically significant differences in five of six VSS (all p < 0.001). PA produced the largest sport-specific differentiation (η² = 0.457, Cohen’s f = 0.918), followed by HEC (η² = 0.273, f = 0.612), SR (η² = 0.224, f = 0.537), and SEM (η² = 0.180, f = 0.468). AF yielded a significant moderate effect (η² = 0.108, f = 0.347). VM was the sole non-significant variable (F (2.147) = 0.74, p = 0.479, ω² = 0.000), suggesting domain-general encoding processes insensitive to discipline-specific training at this developmental level. Boxing athletes achieved the highest scores in SEM, SR, and PA, while karate athletes led in AF and HEC. PCA revealed a single dominant component (PC1 = 93.91% of variance), confirming that VSS function as a highly integrated perceptual-motor construct rather than independent sub-skills. Conclusions: Visio-spatial skills in combat sports are governed by a dominant integrated factor, with discipline-specific variations reflecting unique performance requirements. Visio-spatial skills in combat sport athletes are highly interdependent and largely governed by a single perceptual-motor construct, with discipline-specific profiles observed across boxing, karate, and taekwondo. The findings support the integration of sport-specific, ecologically valid visual training programs targeting key perceptual-cognitive skills, alongside routine assessment to inform athlete development and performance optimization. Full article

Bodybuilding aims to achieve a muscular physique through intensive resistance training and strict dietary control. Athletes in this sport could be at risk of disordered eating behaviors; however, limited evidence exists regarding its association with ON. Social media use and Weight-Related Self-Monitoring (WRSM) applications may contribute to ON symptoms by reinforcing rigid dietary behaviors. These aspects remain underexplored in the current literature, particularly within the sporting context. This narrative review aimed to synthesize current evidence on the potential association between bodybuilding and ON, and to examine the influence of social media and weight-related self-monitoring (WRSM) applications on its development. Literature searches included the terms “bodybuilding AND orthorexia nervosa”, “bodybuilding AND eating disorders”, “bodybuilding AND social media”, “bodybuilding AND aesthetic pressure”, “orthorexia nervosa”, “orthorexia nervosa AND social media”, “fitness influencers” and “orthorexia nervosa in sport”. Available evidence suggests that bodybuilders may present risk factors for orthorexic tendencies, including dietary rigidity, body image centrality, perfectionism, and compulsive exercise. Social media may contribute by promoting unrealistic aesthetic standards, potentially reinforcing disordered eating patterns. Although direct data in bodybuilding are limited, findings indicate a plausible vulnerability profile. Monitoring and preventive strategies may be warranted to reduce the risk of onset or exacerbation of comorbid eating disorders. Full article

(1) Background: This study aims to investigate the differences in body composition, muscle strength, and power between young karate athletes from different competitive disciplines. (2) Methods: The study sample consisted of 131 participants (69 boys and 62 girls) aged 10–14 years divided into three groups: kata (n = 48), kumite (n = 40), and athletes competing in both disciplines (n = 43). The set of variables included 1 anthropometric variable, 6 variables for assessing body composition (InBody 270), 8 variables for assessing handgrip strength (handgrip strength test, Fmax, RFD, absolute and relative, both hands), and 3 variables for assessing lower limb muscle power (force plate, CMJ height and power). Of the statistic analysis, MANOVA and ANOVA, along with MANCOVA and ANCOVA were performed. (3) Results: The adjusted results revealed significant general differences between groups (from p = 0.005 to p = 0.009). Regarding body composition, kumite athletes are taller, have greater body mass, body water, proteins, minerals, and muscle mass content than kata athletes and athletes specialized in both disciplines (from p = 0.002 to p = 0.045). The young karate athletes specialized in kumite competition exhibit higher levels of absolute handgrip muscle strength, rate of force development, and absolute lower limb muscle power than kata athletes and athletes specialized in both disciplines (from p = 0.002 to p = 0.041). There were no significant differences in any measured parameters between kata athletes and young karate athletes specialised in both disciplines. (4) Conclusions: The results are associated with higher values of body composition, muscle strength, and power in kumite athletes compared to kata athletes and athletes competing in both disciplines. Full article

Although routine biomechanical monitoring in rowing increasingly relies on sensor-based and instrumented measurement systems that can capture multidimensional performance indicators with considerable precision, systematic approaches are still needed to integrate these sensor-derived data into a unified monitoring dataset and translate them into decision support for practice. This study aimed to construct a unified rowing training monitoring dataset from real-world sensor-derived biomechanical measurements, develop predictive models for athletes’ performance gaps relative to target 2 km performance, and, for target attainment classification, identify key training monitoring indicators and evaluate their practical value in training practice. A total of 249 biomechanical testing records collected during the 2024–2025 season from the Chinese National Rowing Team were included. After standardized processing, 449 athlete-level records were generated for the primary analysis. Following exclusion of observations with missing primary regression labels, 172 modeling records were retained, corresponding to 87 test reports and 119 athletes. The primary regression outcome was the percentage time difference relative to target 2 km performance. XGBoost Regressor, Elastic Net, and LASSO were used for regression modeling, whereas Logistic Regression and XGBoost Classifier were used for the secondary classification task of target attainment. Internal validation was performed using grouped cross-validation at the athlete level, and model interpretation was supported by permutation importance, sparse linear coefficients, and robustness analyses. The results showed that all formal models outperformed their respective baseline models. In the primary regression task, XGBoost Regressor achieved the best performance in terms of MAE, whereas Elastic Net performed best in RMSE and R². The key training-monitoring indicators mainly included mean boat velocity, minimum boat velocity, stroke rate, distance per stroke, and efficiency-related variables. After removal of grouping variables related to boat class, sex, and weight category, the performance of XGBoost Regressor remained largely stable, suggesting that the primary predictive signal was mainly derived from measured technical and biomechanical features. In the secondary classification task, XGBoost Classifier achieved an ROC AUC of 0.992. This study provides a team-specific applied framework for extending sensor-derived rowing monitoring outputs from multi-indicator measurement toward interpretable performance evaluation and decision support within an elite-team setting, while broader external validation remains necessary. Full article

Perceptual–cognitive abilities are essential components of performance in volleyball, where players must quickly interpret visual information and respond effectively to rapidly changing game situations. The present study aimed to examine perceptual–cognitive abilities and reaction performance in competitive female volleyball players and to explore how these abilities may contribute to athlete development and training design. Thirty-nine young female volleyball athletes participated in the study and underwent an evaluation of perceptual–cognitive abilities considered critical for volleyball performance. These abilities were assessed through specially designed computer-based tasks delivered via dedicated experimental software, enabling the measurement of reaction time and response accuracy during perceptual–motor processing. Group comparisons did not reveal significant differences between playing positions or competitive levels in the measured perceptual–cognitive abilities. Multivariate and clustering analyses suggested the presence of potential performance patterns characterized by different combinations of reaction speed, response accuracy, and perceptual–cognitive processing. However, these patterns should be interpreted with caution, as the clustering solution showed limited separation (silhouette score = 0.02), indicating an exploratory and non-definitive structure. Overall, the findings highlight the multidimensional nature of perceptual–cognitive performance in volleyball and suggest that athletes may rely on different perceptual–motor strategies when responding to game-related stimuli. From an applied perspective, integrating perceptual–cognitive challenges into training environments may support athlete development and improve decision-making efficiency in dynamic game situations. Full article

Background: Children and adults with disabilities are widely acknowledged to have poorer health and emotional wellbeing than their non-disabled peers, which is further compounded by less access to health services and health-promoting activities. A relatively untried solution is to mobilize community initiatives such as sports to promote better health. Method: Special Olympics (SO) is an international sports organization present in over 200 countries and jurisdictions, engaging with just under four million athletes with intellectual disabilities annually. Research on the perceptions of sports coaches around incorporating health promotion within their sports training has been scarce. Likewise, little attention has been paid to identifying athletes’ understanding of what health means to them and actions that would make them healthier. A qualitative, descriptive study was conducted with eight national SO programs involving 62 coaches and 47 athletes. Group interviews were conducted via Zoom and a thematic content analysis was made of their responses. Results: In all countries, coaches and athletes agreed that the most common needs were healthy eating, healthy weight and exercise. Good mental wellbeing and sleeping well were also named. Ideas were sought from both sets of participants regarding how coaches could assist their athletes to attain better health and the barriers they might face in doing so. Conclusions: Three main conclusions emerged. Athletes and coaches were aware of health deficits and knew of ways to reduce them. Both appreciated the contribution that coaches could make through motivating athletes and providing training activities but were dependent on suitable resources being available to them. Engagement with families and available health and social care services was essential. Health-oriented, sporting activities offer promise in improving the health and wellbeing of persons with developmental disabilities, particularly in less affluent countries with fewer health professionals and poorly developed primary care services. Full article

Advancing athlete health requires a shift from reactive sports medicine toward proactive, personalized, and longitudinal care. This article presents a conceptual framework for an Interdisciplinary AI Center for Longevity and Well-Being designed to integrate Artificial Intelligence of Things (AIoT), wearable sensing, and multimodal analytics into a unified athlete health ecosystem. The manuscript contextualizes the proposed framework with relevant literature across key technical domains and presents a reference edge–fog–cloud architecture together with a proof-of-concept dashboard pipeline to illustrate technical feasibility. Within this framework, heterogeneous data streams from wearable physiological sensors, biomechanical devices, non-invasive biomarker monitors, and environmental trackers are organized to support multimodal analysis and individualized performance intelligence. The paper outlines five target application domains: real-time health monitoring, injury risk assessment, performance optimization, holistic well-being evaluation, and longevity-oriented health management. Privacy-preserving and interpretable AI components, including federated learning, differential privacy, and explainability-oriented design considerations, are presented as key architectural priorities, while several elements are explicitly identified as future development directions. Rather than claiming full real-world validation, this work provides an interdisciplinary blueprint and prototype-informed foundation for future research and implementation at the intersection of computer science, biomedical engineering, and sports science. Full article