Search Results (1,184)

Countermovement jump (CMJ) testing is widely used to monitor neuromuscular function, but trial-to-trial reliability depends on the population and testing ecology. Previous reliability prescriptions have often been derived from male cohorts, risking misapplication to female athletes, whose anthropometry, movement strategies, and testing environments differ. This study applied Generalizability Theory (G-Theory) to quantify the within-session reliability of CMJ metrics in NCAA Division I women’s volleyball, softball, soccer, and lacrosse, aiming to isolate the measurement precision independent of day-to-day biological variance. A fully crossed person × trial G-Theory analysis was performed, with the G-study phase estimating variance components and the D-study phase determining the number of trials required to reach actionable dependability (Φ ≥ 0.80). Force–time data from 103 athletes across 282 jumps were analyzed for 14 commonly monitored metrics. Results show that six concentric and takeoff indices, including force at zero velocity, phase-1 concentric impulse, total concentric impulse, jump height, takeoff velocity, and scaled power, achieved Φ ≥ 0.80 from a single trial across all sports. Second-tier variables, such as eccentric duration, phase-2 impulse, and the modified reactive strength index, stabilized within two to three trials, whereas braking impulse, countermovement depth, and deceleration RFD asymmetry required impractical sampling and were deemed fragile (i.e., requiring a greater number of trials to reach acceptable reliability). Compared with the male data, women exhibited larger between-subject variance and higher single-trial dependability for 11 of the 14 studied metrics. Findings support concise, sex-specific trial prescriptions that prioritize stable metrics and minimize unnecessary testing. Full article

Smart textiles are emerging as transformative modern textiles in which sensing, actuation, and communication are directly embedded into textiles, extending their role far beyond passive wearables. This review presents a comprehensive analysis of the convergence between smart textiles, the Internet of Things (IoT), and human-centric design, with sustainability as a guiding principle. We examine recent advances in conductive fibers, textile-based sensors, and communication protocols, while emphasizing user comfort, unobtrusiveness, and ecological responsibility. Key breakthroughs, such as silk fibroin ionic touch screens (SFITS), illustrate the potential of biodegradable and high-performance interfaces that reduce electronic waste and enable seamless human–computer interaction. The paper highlights cross-sector applications ranging from healthcare and sports to defense, fashion, and robotics, where IoT-enabled textiles deliver real-time monitoring, predictive analytics, and adaptive feedback. The review also focuses on sustainability challenges, including energy-intensive manufacturing and e-waste generation, and reviews ongoing strategies such as biodegradable polymers, modular architectures, and design-for-disassembly approaches. Furthermore, to identify future research priorities in AI-integrated “textile brains,” self-healing materials, bio-integrated systems, and standardized safety and ethical frameworks are also visited. Taken together, this review emphasizes the pivotal role of smart textiles as a cornerstone of next-generation wearable technology, with the potential to enhance human well-being while advancing global sustainability goals. Full article

This work presents a standardized 360-degree, clock-face ultrasonographic protocol for comprehensive static and dynamic assessment of the glenoid labrum. The protocol translates the arthroscopic clock-face orientation into ultrasound scanning windows, providing reproducible steps for each labral quadrant (12 to 12 o’clock) including patient positioning, transducer orientation, and dynamic maneuvers. By leveraging linear transducers with trapezoidal imaging and an optional convex transducer to bypass acoustic shadowing from the acromion and coracoid, all labral segments can be consistently visualized, while dynamic testing reveals subtle clefts, irregular margins, and medial displacement patterns. Clinically, this approach is particularly valuable for patients who cannot undergo MRI or MR arthrography (e.g., due to metallic implants, contrast allergy, claustrophobia or renal dysfunction) and in settings where MR/MRA is unavailable or impractical (sports medicine, urgent care, postoperative follow-up). The pictorial atlas and step-by-step checklists aim to support adoption in routine practice and to facilitate communication with surgeons through shared clock-face terminology. This protocol is not intended to replace MR arthrography for surgical planning; rather, when MRI/MRA cannot be performed or access is limited, it provides actionable, dynamic information that complements clinical decision-making. Full article

This paper explores the replication of the DotA Plus prediction system using decision tree algorithms. The study implements and evaluates Extra Trees Classifier, Random Forest Classifier, and Hist Gradient Boosting Classifier, along with their combined average, for predicting the outcome of Defense of the Ancients (DotA) 2 matches. Data was collected using the OpenDotA API and the Steam API, and various features such as game duration, tower and barracks states, net-worth, assists, last hits, gold, level, gold per minute, and experience per minute were extracted for model training. Additionally, hero and item win rate features, derived from Dotabuff data, were incorporated to enhance the models’ predictive accuracy. The models were trained on datasets with varying match durations, including segments for matches under 10 min, between 10 and 20 min, and over 20 min. The experimental results show that the Extra Trees Classifier consistently outperformed other individual models and performed comparably to the averaged models, achieving a peak performance of 98.6% test accuracy on matches longer than 20 min when using match duration segmentation and hero/item embeddings. The study highlights the effectiveness of decision tree-based methods for real-time match outcome prediction in DotA 2 and offers insights into feature importance. The combined average of Extra Trees Classifier, Random Forest Classifier, and Hist Gradient Boosting Classifier models provides a robust and reliable prediction of DotA 2 match outcomes, thus showing potential as a real-time prediction system. Full article

To address the inherent limitations of easy oxidation and unstable electrical properties in two-dimensional MXene-based flexible sensors, this study developed a MXene/GO/rGO (reduced graphene oxide) textile-based flexible sensor using a lamination method and in situ steam reduction technology. The sensor was constructed on a high-elasticity knitted polyester fabric, with MXene as the primary conductive layer, graphene oxide (GO) as the adhesive layer, and reduced graphene oxide (rGO) as the protective encapsulation surface layer. The tensile strain-sensing and electrothermal properties of the resulting e-textile were systematically characterized. The MXene/GO/rGO textile demonstrated outstanding electrical and mechanical performance, achieving a conductivity of 39.7 S·m⁻¹, a gauge factors ranging from –3 to –1.6, and a controllable electrothermal heating range from 43 °C to 85 °C under currents of 0.02–0.05 A. Experimental results demonstrated that under applied currents of 0.02, 0.03, 0.04, and 0.05 A, the fabric reached temperatures of 43, 56, 73, and 85 °C, respectively, and remained constant over extended periods. In terms of strain sensing, the sensor exhibited a short response time (65 ms), high discriminability for different strain levels and stretching rates, and a consistent relative resistance change (ΔR/R0) under various stretching speeds (0.5, 1, 2, 4, and 6 mm/s). Compared with sensors based on a single conductive material, the MXene/GO/rGO polyester fabric sensor shows superior electrothermal and strain-sensing performance, indicating promising potential for applications in intelligent wearable textiles such as medical thermal therapy, sports monitoring, and health management. Full article

Myocardial work (MW), derived from non-invasive pressure–strain loop (PSL) analysis, has recently emerged as a promising echocardiographic index for assessing left ventricular performance. It integrates speckle-tracking echocardiography with estimated left ventricular pressure, providing a load-adjusted measure of myocardial performance. This technique addresses the limitations of traditional parameters such as global longitudinal strain (GLS) and ejection fraction (EF), particularly in populations exposed to dynamic loading conditions, such as athletes. Athletic training induces a spectrum of cardiac adaptations, collectively referred to as the “athlete’s heart,” which may mimic or mask pathological conditions. In this context, MW represents a valuable tool to differentiate physiological remodeling from early myocardial dysfunction or underlying cardiovascular disease (e.g., cardiomyopathies, myocarditis). The aim of this review is to explore the physiological rationale for using MW in athletes, evaluate its relationship with performance metrics (e.g., VO₂max, lactate threshold), and discuss its potential, yet still emerging and not fully validated, role in informing training adaptation and detecting subclinical cardiac conditions. Additionally, we examine MW applications across different sport disciplines (strength, mixed-sport, and endurance), highlighting its role in individualized assessment and risk stratification. By synthesizing current evidence and outlining future research directions, this work emphasizes the potential of MW to become a standard component of cardiovascular evaluation in sports cardiology. Full article

Climate change poses growing challenges to youth sports participation, but adolescent girls face disproportionate and compounding vulnerabilities. These arise from sex-specific physiological factors, sociocultural constraints, and institutional inequities that uniquely and disproportionately impact girls. These challenges are especially concerning considering the numerous health and well-being benefits of sports participation. However, there is a notable lack of research examining the specific impacts of climate change on adolescent girls’ sports participation, as well as evidence-informed strategies to mitigate these effects. The aim of this study is to (1) conduct a scoping review to better understand the impacts of climate change on adolescent girls’ sports participation and (2) examine the relationship between climate change and adolescent girls’ involvement in sports by integrating Ecologism and the Individual × Environment (I×E) frameworks. A search was conducted using four databases (PubMed, Scopus, SPORTDiscus and Web of Science), and a gray literature search was performed on Google. The search was limited to studies focusing on how climate change or weather variables impacted adolescent girls’ physical activity levels or sports participation. Studies must have been written in English, and all geographical regions were included. In total, 26 studies met the inclusion criteria. These findings were then analyzed by integrating Ecologism, which promotes sustainable infrastructure, and the Individual × Environment (I×E) framework, which highlights interventions tailored to individual and environmental interaction. Recommended strategies include climate-resilient facility design, equity-focused funding models, participatory research, and coordinated efforts from public health units and urban planning stakeholders. By integrating these frameworks, the paper proposes a comprehensive set of interventions that address both systemic ecological challenges and individual-level barriers, aiming to foster climate-resilient sports environments for adolescent girls. Full article

Reliable forecasting of network QoS indicators such as latency, jitter, and packet loss is essential for managing real-time and risk-sensitive applications. This study addresses the challenge of uncertainty quantification in QoS prediction by proposing a Bayesian Regression-enhanced Long Short-Term Memory (BR-LSTM) framework. The method integrates Bayesian mean variance estimates into sequential LSTM learning to enable accurate point forecasts and well-calibrated confidence intervals. Experiments are conducted using a Mininet-based emulation platform that simulates dynamic esports network environments. The proposed model is benchmarked against ten probabilistic and deterministic baselines, including ARIMA, Gaussian Process Regression, Bayesian Neural Networks, and Monte Carlo Dropout LSTM. Results demonstrate that BR-LSTM achieves competitive accuracy while providing uncertainty intervals that improve decision confidence for Service-Level Agreement (SLA) management. The calibrated upper bound $(\mu +k\sigma )$  can be compared directly against SLA thresholds to issue early warnings and prioritize rerouting, pacing, or bitrate adjustments when the bound approaches or exceeds policy limits, while calibration controls false alarms and prevents unnecessary interventions. The findings highlight the potential of uncertainty-aware forecasting for intelligent information systems in latency-critical networks. Full article

Stress, workload, and uncertainty characterize occupational tasks across sports, healthcare, military, and transportation domains. Emerging theory and empirical research suggest that coordinated whole-body movements may reflect these transient mental states. Wearable sensors and optical motion capture offer opportunities to quantify such movement dynamics and classify mental states that influence occupational performance and human–machine interaction. We tested this possibility in a small pilot study (N = 10) designed to test feasibility and identify preliminary movement features linked to mental states. Participants performed a perceptual decision-making task involving facial emotion recognition (i.e., deciding whether depicted faces were happy versus angry) with variable levels of stress (via a risk of electric shock), workload (via time pressure), and uncertainty (via visual degradation of task stimuli). The time series of movement trajectories was analyzed both holistically (full trajectory) and by phase: lowered (early), raising (middle), aiming (late), and face-to-face (sequential). For each epoch, up to 3844 linear and non-linear features were extracted across temporal, spectral, probability, divergence, and fractal domains. Features were entered into a repeated 10-fold cross-validation procedure using 80/20 train/test splits. Feature selection was conducted with the T-Rex Selector, and selected features were used to train a scikit-learn pipeline with a Robust Scaler and a Logistic Regression classifier. Models achieved mean ROC AUC scores as high as 0.76 for stress classification, with the highest sensitivity during the full movement trajectory and middle (raise) phases. Classification of workload and uncertainty states was less successful. These findings demonstrate the potential of movement-based sensing to infer stress states in applied settings and inform future human–machine interface development. Full article

Sex-related differences in lower-limb biomechanics and neuromuscular strategies during rope jumping remain underexplored, particularly in combat-sport athletes. This study investigated leg stiffness and muscle activation in ten female (22.8 ± 0.8 years) and ten male (22.9 ± 1.4 years) Muay Thai athletes. Participants performed rope skipping under three conditions: dominant leg, non-dominant leg, and double leg at 2.2 Hz. Ground reaction forces were recorded at 1000 Hz, center of mass displacement at 200 Hz, and electromyographic activity of the vastus lateralis, biceps femoris, tibialis anterior, and medial gastrocnemius at 3000 Hz. Vertical stiffness (K_vert) was calculated as the ratio of peak vertical force to displacement. Results showed no significant sex differences in peak ground reaction force (e.g., dominant leg: females 2.83 ± 0.42 vs. males 3.22 ± 0.57 kN; double leg: females 4.04 ± 0.83 vs. males 4.35 ± 0.73 kN; p > 0.05), vertical stiffness (females 17.02 ± 3.66 vs. males 16.21 ± 4.09 kN/m; p > 0.05), contact time (females 0.280 ± 0.03 vs. males 0.275 ± 0.05 s; p > 0.05), or flight time (females 0.205 ± 0.03 vs. males 0.245 ± 0.05 s; p > 0.05). In contrast, females exhibited significantly higher co-activation ratios during unilateral skipping, including BF/VL (0.76 ± 0.18 vs. 0.63 ± 0.10; p < 0.05) and TA/MG (0.38 ± 0.11 vs. 0.29 ± 0.07; p < 0.05), suggesting a neuromuscular strategy to enhance joint stability. These findings highlight rope jumping as a practical drill that can promote neuromuscular control and stability in Muay Thai training. Full article

Background/Objectives: The benefits of physical activity (PA) do not depend on the PA level alone but also on sedentary behavior (SB). The interaction between PA and SB (i.e., PA–SB interplay) is important to determine one’s health status. This study explored the effect of PA–SB interplay on balance and gait in healthy young adults. Methods: Healthy young adults (n = 133, 18–35 yrs) were placed in four PA–SB interplay groups (according to their sitting duration and physical activity duration) using the American College of Sports Medicine PA guidelines (i.e., sedentary active [>6 h/day, >150 min/week], sedentary inactive [>6 h/day, <150 min/week], physically active [<6 h/day, >150 min/week], and physically inactive [<6 h/day, <150 min/week]). In this cross-sectional study, participants’ balance and gait were assessed with inertial measurement units placed on seven bodily sites. In this exploratory study, significance level was set at p < 0.1. Results: Sway acceleration RMS during the eyes closed on stable surface balance test showed a statistically significant difference among the PA–SB interplay groups (p = 0.055) which was found between sedentary active and physically inactive (p = 0.066). Anticipatory postural adjustment (APA) duration during gait showed a statistically significant difference (p = 0.010) which was found between sedentary inactive and physically active (p = 0.019) and between sedentary active and physically active (p = 0.026). Conclusions: PA–SB interplay influences static (sway acceleration RMS) and dynamic (APA duration) balance of healthy young adults. Findings suggest that somatosensory processing during balance and gait initiation are significantly impacted by PA–SB interplay. Full article

Swimming is one of the most popular forms of recreational sport worldwide, recommended for people of all ages as a healthy activity. While numerous studies have focused on the impact of indoor air quality on the health of pool users, relatively few have addressed how specific airborne parameters in indoor swimming facilities affect the durability of construction materials. This article analyzes the current state of knowledge on the influence of the pool indoor environment on structural reliability, with trichloramine (NCl₃) emphasized as a degradation factor. Indoor pool environments are classified as chemically aggressive, due to elevated air temperature (~30 °C), high humidity (often exceeding 60%), and the presence of volatile chlorine compounds released from disinfected water. Our case study demonstrates that during swimming competitions, the average concentration of airborne NCl₃ reached a value of 900 µg/m³, with peaks up to 1200 µg/m³, i.e., about ten times higher than on typical usage days. The median trichloramine concertation during the competition was 1071 µg/m³. Such exposure conditions accelerate corrosion processes in stainless steels and other building materials, reducing service life and requiring targeted monitoring and preventive maintenance. Based on the findings, recommendations are provided regarding material selection, highlighting the importance of surface texture, ventilation strategies, and protective measures tailored to periods of intensive facility use. Full article

Sport psychology research has shown that athletes might experience self-presentation concerns. However, fairly limited work has examined these specific concerns among athletes experiencing an injury, particularly among adolescent populations. Therefore, the purpose of this qualitative study was to explore the nature, precursors, and implications of injured adolescent athletes’ self-presentation concerns. Semi-structured interviews were conducted with female (n = 12) and male (n = 2) competitive adolescent athletes (Mage = 15.1 years) who experienced a variety of serious injuries (e.g., ACL rupture, labrum tear) as a result of competing in various sports. Braun and Clark’s thematic analysis (2006) was used to develop themes pertaining to the nature, precursors, and implications of injury. Findings highlight a range of specific types of self-presentation concerns (e.g., concerns over “faking” an injury, lacking capability, disappointing others), the impact of the closeness of relationships with significant others, key implications (e.g., future sport apprehensions, negative emotions, motivational enhancements), and coping strategies. Results identify factors for targeted interventions aimed at managing self-presentation concerns among injured adolescents. Full article

Fatigue is a multidimensional phenomenon with profound implications for performance, health, and wellbeing. Its complexity means that no single discipline can adequately explain its causes or management, highlighting the need for integrative approaches. This article introduces the F.L.A.M.E.S. framework, a psychological model that integrates self-report, physiological, emotional, and contextual perspectives on fatigue. The framework combines validated assessment tools with evidence-based management strategies including goal setting, motivational self-talk, attentional control, and emotion regulation and embeds these within proactive, reactive, and preventative approaches. Applications are illustrated through case studies in sport, healthcare, and education, showing how the model can be co-constructed with practitioners to ensure ecological validity and uptake. By linking mechanisms to management and scaling solutions across domains, the F.L.A.M.E.S. framework provides a roadmap for enhancing performance, resilience, and sustainable wellbeing. Full article

Background: Electroencephalography (EEG) is a non-invasive technique that records millisecond-scale cortical electrical activity using scalp electrodes. In EEG-based neurofeedback (NFB), these signals are processed to provide real-time feedback that supports self-regulation of targeted brain rhythms; evidence suggests improvements in cognitive and neurophysiological performance in athletes and non-athletes. However, methodological inconsistencies—such as limited blinding, poor sham control, and outdated approaches to EEG spectral analysis—restrict reproducibility and hinder cumulative progress in the field. Methods: This scoping review aimed to identify and analyze the methodological characteristics, outcome measures, and reproducibility gaps in EEG-based NFB studies involving athletes and non-athletes. Following PRISMA-ScR guidelines, we systematically searched academic databases (PubMed, Embase, Scopus, Web of Science, PsycINFO, and Cochrane Library), as well as gray literature sources (ProQuest Dissertations, LILACS, Tripdatabase, and Google Scholar). Of 48 included studies, 44 were published in international peer-reviewed journals and 4 in regional journals. Data were extracted on study design, participant population, NFB protocols, targeted EEG rhythms, cognitive and neurophysiological outcomes, and methodological rigor. Results: The review revealed substantial heterogeneity in targeted rhythms, protocols, and reporting standards. None of the studies employed modern spectral parameterization methods (e.g., FOOOF), while only 29% used active sham protocols and 6% employed inert sham conditions. Reporting blinding procedures and follow-up assessments was limited or absent in most studies. Discussion: This review highlights critical methodological shortcomings that may bias interpretations of NFB effects in sport and cognitive domains. To strengthen future research, studies should rigorously implement sham and blinding procedures, ensure transparent reporting of EEG metrics, and adopt open-science practices, including modern approaches to spectral parameterization. Full article