26242 research outputs found
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A171: An Applied Study of Smart Sports to Enable Youth Soccer Training
No full textSmart sports technology can improve the technical and tactical level of youth soccer players through a new generation of information technology, combined with the laws of physical and mental development of young people, and through systematic and scientific training methods. This study verifies the effectiveness of smart sports technology in improving the level of youth soccer through application in youth soccer training. Method: recruit 40 adolescents (20 males and 20 females) involved in soccer training, aged 12-16 years (with informed consent of their guardians) for an 8-week period of 90-minute training, 3 times per week. 1. Use of technological monitoring undershirts (GPS trackers, heart rate monitors, and other equipment, weighing approximately 400 grams) to monitor exercise load during training in real time to avoid excessive fatigue. 2. Real-time tracking of players\u27 running position, standing position, etc., through intelligent monitoring and tracking equipment in the intelligent soccer field, generating real-time data through AI algorithms to help the coaching team formulate targeted training programs. 3. Use intelligent soccer to collect real-time data of players\u27 touching parts, passing, shooting, etc., to generate personalized training data and real-time feedback to the coaching team to improve the athletes\u27 deficiencies. Through the use of intelligent sports technology, the motivation of athletes can be improved; real-time feedback and personalized reports provided by AI algorithms can help the coaching team to improve the technical and tactical level of athletes, enhance training programs, and improve training results; real-time physiological data of athletes obtained through the use of monitoring devices can effectively ensure sports safety. The real-time feedback data obtained through the intervention of smart sports technology in training can improve the rationality of athletes\u27 running routes, touching parts of the ball, and the way of force generation when hitting the ball, and improve the training effect, which has certain practical significance. However, because this study relies heavily on the technical equipment of smart sports, it has a high cost and may not be able to be replicated on a larger scale, so the next step is to explore how to reduce cost and increase efficiency
A211: AI-driven Strategic Frameworks for Sport Event Propagation Under Media Affordance Theory
No full textThe advancement of intelligent technology has transformed interaction models across communication ecosystems, encompassing production, dissemination, and consumption. Exemplified by the Paris Olympics’ 180+ intelligent communication domains, “AI + Sports” has emerged as an industry paradigm. This study employs media affordance theory to analyze AI’s transformative role in sports communication and associated ethical challenges, offering insights for cultivating a robust digital sports ecosystem. Method: This study investigates the application pathways of artificial intelligence in 20 major sports events held between 2000 and 2024. Data on application frequency, audience feedback, and other relevant metrics w collected to analyze the impact patterns of AI in sports event communication. Empirical studies demonstrate that intelligent technologies in sport communication evolve through a “discrete infiltration-systematic reconstruction” process, achieving bidirectional structural transformation. From media affordance perspectives, AI-driven paradigm shifts create a triangular model featuring “informational density leap-user precision iteration-impact breadth reconfiguration.” In terms of productive affordance, AI technology significantly enhances communication efficiency, enabling precise coverage of audience needs. Regarding social affordance, algorithms foster emotional resonance between communicators and the audience. As for mobile affordance, AI-generated content (AIGC) transcends spatial and temporal constraints, effectively expanding the boundaries of sports event influence. However, the deepening of technological empowerment has also given rise to three critical ethical dilemmas in communication. First, under the algorithmic black-box effect, the absence of a fact-checking mechanism within the content production chain leads to a normative imbalance between “technological correctness” and “factual accuracy.” Second, emotional algorithmic manipulation introduced by technological mediation is eroding authentic audience-sport event connections. Lastly, the fluidity of user information boundaries has fostered a new form of digital exploitation within the framework of technological ethics. In the era of intelligent communication, the humanistic essence of sports events is facing profound challenges posed by digital deconstruction. Event organizers must establish a bidirectional “technology-life” reflection mechanism. First, they should actively explore the broader potential in the dissemination of large-scale events. Second, they must maintain a dialectical perspective throughout their application, carefully regulating risks to ensure the smooth operation of events. Content creators should adhere to a people-centered approach and promptly fill in the gaps where needed. Not only should the purpose of content production be rooted in human values, but the creative process must also leverage human agency to ensure both efficiency and quality in content delivery
Dataset for Re-assessing the Status of High Desert Bird Populations of the Morley Nelson Birds of Prey National Conservation Area After 30 Years of Change
No full textBird populations across North America are in decline. In sagebrush and other shrubsteppe habitats, habitat loss and other human pressures threaten bird communities. Our study assessed the status of a bird community at the Morley Nelson Snake River Birds of Prey National Conservation Area, a high desert site in southwestern Idaho, USA. Between 29 May and 14 June 2022, and 31 May and 19 June 2023, we conducted avian point count surveys at historical points that were surveyed two or more years from 1992–1995. We assessed changes in bird species detections, vegetation, and fire history between survey periods, as well as the relationship between vegetation, fire history, and species detections. We focused on the most numerous ten bird species in each time period, which included sagebrush obligate species, grassland specialist species, and species we considered open country generalists. Sagebrush cover decreased significantly at survey points between the historical and current survey periods, whereas annual herbaceous vegetation cover and fire occurrence increased significantly. Most species with at least 20 detections had different detection rates between time periods. Specifically, there were notable declines in detections of many species, particularly among sagebrush obligate species (Brewer’s Sparrow, Spizella breweri; Sagebrush Sparrow, Artemisiospiza nevadensis; and Sage Thrasher, Oreoscoptes montanus) as well as 2 common, generalist species — Horned Lark (Eremophila alpestris) and Western Meadowlark (Sturnella neglecta). Detections of several species increased from the historical to current survey period, particularly California Gulls (Larus californicus), Common Ravens (Corvus corax), and Long-billed Curlews (Numenius americanus). These 30-year trends highlight the perils of birds in sagebrush and shrubsteppe habitat and the relationship between bird population changes, loss of native vegetation, increase of invasive plant species, and more frequent fire
A304: Smart Sports in Tri-Space and Students’ Physical Health
No full textWith the rapid advancement of technology, smart sports, as an emerging paradigm, have begun to reshape campus sports by integrating physical, informational, and social spaces—a concept termed the tri-space framework. This integration offers new opportunities to address declining physical health among college students, exacerbated by traditional sports education’s limitations in resources, personalization, and engagement. Smart sports leverage technologies such as IoT, big data, and AI to optimize resource utilization, deliver data-driven fitness plans, and foster interactive social platforms. This study aims to explore how tri-space-integrated smart sports influence college students’ physical health, examining their mechanisms and potential to reform campus sports systems. A mixed-methods approach was adopted, combining quantitative and qualitative analyses. Data were collected from 1,200 students across six universities through structured questionnaires, wearable device metrics (e.g., heart rate, step counts), and pre-post physical fitness tests (e.g., BMI, endurance, flexibility). Smart sports interventions included AI-powered training apps, IoT-enabled gyms, and social fitness platforms. Statistical analyses (e.g., regression models, ANOVA) and thematic coding of interview responses were employed to assess changes in physical health indicators, participation rates, and psychosocial factors (e.g., motivation, social cohesion). The integration of tri-space smart sports demonstrated significant positive effects. Physically, students using IoT gyms and AI plans showed a 15.3% improvement in endurance (p \u3c 0.01) and a 9.7% reduction in sedentary behavior. Informational tools enhanced exercise adherence, with 68% of participants reporting personalized feedback as highly motivating. Socially, platform users exhibited 30% higher group activity engagement, correlating with improved mental resilience (r = 0.42, p \u3c 0.05). However, disparities emerged: students with limited tech access showed smaller gains, highlighting equity concerns. Qualitative feedback emphasized that gamified social interactions and real-time data tracking were critical drivers of sustained participation. Conclusions/Discussion: This study underscores the transformative potential of tri-space smart sports in enhancing college students’ physical health. By synergizing intelligent environments, data-driven insights, and social connectivity, such systems address traditional limitations while fostering holistic well-being. However, challenges like technological accessibility and privacy risks require institutional policies to ensure equitable benefits. Future research should explore longitudinal impacts and cross-cultural applicability. These findings advocate for broader adoption of smart sports frameworks in higher education, aligning with global trends toward digitized, student-centered health promotion
A106: School-Based Physical Activity Interventions on Cardiorespiratory Fitness and Body Composition in Children and Adolescents: A-Meta-Analysis-Using-the-RE-AIM-Framework
No full textThis systematic review and meta-analysis aimed to (1) assess the effects of school-based physical activity (PA) interventions on cardiorespiratory fitness (CRF) and body composition in children and adolescents, and (2) evaluate the reporting of internal validity (i.e. Reach and Effectiveness) and external validity (i.e. Adoption, Implementation, and Maintenance) within included studies using the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework. A comprehensive search was conducted across five databases (PubMed, Embase, Web of Science, EBSCO, and Cochrane Library) for studies published from January 1, 2000, to July 10, 2024. Eligible studies included randomized and non-randomized controlled trials involving healthy children and adolescents aged 5 to 17 years. Only studies that reported CRF or body composition with PA or exercise as the sole intervention were included. The RE-AIM framework was applied to assess study quality. 43 studies with a total of 27,626 participants were included in the meta-analysis. School-based PA interventions had a significant positive effect on CRF (SMD = 0.28, 95% CI = 0.19 to 0.38, P \u3c 0.001; I² = 75%). Subgroup analysis revealed a significant positive effect on CRF in studies involving mixed-gender groups (SMD = 0.30, 95% CI = 0.20 to 0.40; I² = 76%), while no significant effects were found in studies involving only boys or girls. Furthermore, no significant effect of school-based PA interventions on percentage of body fat (%BF) was observed (SMD = -0.05, 95% CI = -0.10 to 0.00, P = 0.054; I² = 28%). The total proportion of the RE-AIM framework reported was 48.1%. Among the five dimensions, Effectiveness is the most frequently reported (72.7%), followed by Reach (53.1%), Adoption (52.3%), Implementation (42.4%), and Maintenance (4.7%). School-based PA interventions significantly improve CRF in children and adolescents, particularly among mixed-gender populations, though the effect on reducing %BF is not significant. Moreover, reporting of internal validity was more frequent than external validity in the included studies of the RE-AIM framework
A174: Visualization Analysis of Artificial Intelligence Applications in Sports: A Decade of Trends and Insights
No full textArtificial intelligence (AI) has revolutionized sports science, advancing performance analysis, injury prevention, and strategy optimization. However, its long-term impact remains underexplored. This study conducts a bibliometric and predictive analysis of -driven sports research over the past decade, identifying key contributors, emerging trends, and future directions through visualization techniques. Method: A systematic review was conducted on related sports research from 2014 to 2024 using the Web of Science Core Collection. Bibliometric tools Citespace and Vosviewer were employed to analyze publication trends, author networks, institutional collaborations, and keyword co-occurrences. Polynomial regression analysis was applied to forecast future research growth based on historical publication and citation trends. A total of 5,811 publications with 96,753 citations were identified. China, the United States, and the United Kingdom were the most productive countries, with China leading in volume but exhibiting lower citation impact. The Chinese Academy of Sciences, Stanford University, and the University of Oxford were the top research institutions. Keyword analysis revealed that machine learning, deep learning, and computer vision were the most studied topics, while emerging themes such as stress analysis, information processing, and pose estimation indicated shifts towards driven real-time monitoring and predictive analytics. Polynomial regression models predicted continued research growth, with publication trends following y = 354x² + 1350x + 528 (r² = 0.94) and citation growth modeled as y = 9680x² + 24900x + 7850 (r² = 0.99), suggesting sustained acceleration in AI applications within sports science. The integration of sports science has grown rapidly, with machine learning and computer vision playing a pivotal role in optimizing athletic performance, real-time feedback, and injury prevention. Predictive analytics and driven modeling can transform sports training by personalizing programs based on biomechanical and physiological data, enhancing both performance and injury resilience. However, disparities in AI adoption across regions and institutions highlight the need for greater international collaboration, particularly in developing regions where access to driven sports technologies is limited. Future research should refine -driven models for individualized training, integrate wearable sensor data for precision, and address ethical concerns. Additionally, policymakers and sports organizations should invest in AI-based training and health monitoring systems to bridge the gap between technology-rich and technology-limited regions. As it evolves, its role in sports science will expand, driving advancements in performance analysis, health monitoring, and strategic decision-making
A301: Application of Sports Rehabilitation Technology in College Students with Cervical Spondylosis
No full textBased on the theoretical framework of exercise prescription, this study systematically evaluates the intervention efficacy of exercise rehabilitation techniques at different frequencies on cervical dysfunction in university students with cervical spondylosis, aiming to provide evidence-based support for constructing campus cervical health management programs. A triple-blind randomized controlled trial was conducted, enrolling 14 university students diagnosed with cervical spondylosis according to ICD-11 criteria. Participants were stratified and randomized into a high-frequency intervention group (ERF), a low-frequency intervention group (ERT), and a matched blank control group with equivalent baseline characteristics. An 8-week structured exercise intervention protocol was implemented, including: (1) Atlanta-occipital joint retraction training; (2) eccentric contraction training of the scalene muscles; (3) isometric contraction training of the deep cervical flexors; and (4) scapular kinetic chain activation training. A multimodal assessment system was employed: the Neck Disability Index (NDI) quantified functional impairment, a three-dimensional motion capture system (Vicon MX) measured C1-C7 segmental range of motion (ROM), and surface electromyography (sEMG) monitored the integrated electromyographic values (iEMG) of the sternocleidomastoid and upper trapezius muscles. Repeated-measures ANOVA and post hoc tests were used for intra- and inter-group difference analys Post-intervention, the experimental groups demonstrated significant improvements compared to the control group in NDI scores (ERT: Δ=12.3±1.7, ERF: Δ=13.1±1.9 vs. control Δ=2.1±0.8, P \u3c 0.001), flexion ROM (ERT: +18.6°±3.2°, ERF: +19.1°±2.9° vs. control +2.3°±1.1°, P \u3c 0.001), and normalized iEMG values (ERT: -42.3%±6.1%, ERF: -45.7%±5.8% vs. control -3.2%±1.6%, P \u3c 0.001). No statistically significant difference in intervention effect size was observed between ERF and ERT. This study demonstrates that the progressive exercise protocol significantly improves cervical biomechanical characteristics, potentially mediated by intervertebral load redistribution and enhanced activation efficiency of deep cervical flexors. The findings confirm that a thrice-weekly intervention frequency achieves the minimal clinically important difference (MCID=10%), providing dose-response evidence for implementing tiered cervical health management strategies in university settings
A140: Kinetic Comparison of Weightlifting Pulling Derivatives with Different Starting Positions
No full textWeightlifting movements have been shown to provide a superior training stimulus for force and power development. Among these, Weightlifting pulling derivatives (WPDs) without the catch phase may generate superior kinetic stimulation compared to the full weightlifting movements. Previous studies have confirmed that the starting position significantly affects the peak vertical ground reaction forces (Fz), peak rate of force development (RFD), and peak power of the weightlifting derivatives with the catch phase. However, the influence of starting position on WPDs is still unclear. Therefore, this study aims to compare the kinetic performance differences of WPDs with different starting positions to optimize training programs. Eighteen men (age: 21.44±1.76 years; height: 1.78±0.06 m; mass: 75.56±6.61 kg; power clean 1RM: 104.03±11.41 kg) were recruited. This study employed a within-subject design, whereby peak Fz, peak RFD, and peak power were determined during the clean pull (CP), clean pull from the knee (CPK), and midthigh clean pull (MCP). Participants were tested in a balanced sequence using a standardized load (60% of power clean 1RM). All lifts were performed with the subjects standing on a force plate (Kunwei, KWF6040-10K), sampling at 1,000 Hz. A repeated-measures ANOVA was conducted to compare the three variants, a significance level of 0.05. Bonferroni-corrected post-hoc tests identified significant mean differences. Result: Significant differences were among the WPDs with different starting positions for peak Fz (p \u3c 0.001), peak instantaneous RFD (p \u3c 0.001), and peak power (p \u3c 0.001). Subsequent post-hoc tests indicated that: The MCP had significantly higher peak Fz than CPK (p \u3c 0.001), which in turn had higher values than the CP (p \u3c 0.001). The MCP had significantly higher peak RFD than the CP (p \u3c 0.001), which in turn had higher values than the CPK (p \u3c 0.001). The CPK significantly higher peak power than the MCP (p = 0.010), which was higher than the CP (p = 0.004). This study demonstrates that when the objective is to maximize force development, the midthigh-starting position for WPD is optimal. When the goal shifts to maximizing power development, unlike the clean variations, where the mid-thigh-starting position is the optimal choice, the knee-starting position for WPD is superior. This difference may be attributed to the initial velocity provided by the transition phase and the increased bar speed achievable with WPD. Since WPDs with different starting positions commonly use different loads in practice, future research should consider this aspect
A196: Prediction of Cardiovascular Function Improvement Based on Wearable Device Motion Monitoring and OTNmanba-BiLSTM Model
No full textCardiovascular diseases are among the leading chronic health conditions worldwide, with prolonged physical inactivity or improper exercise increasing the risk of their occurrence. Existing studies suggest that well-structured exercise interventions can significantly enhance cardiac function and improve the adaptability of the cardiovascular system. However, accurately predicting the long-term impact of different exercise durations and intensities on heart health remains challenging due to individual physiological differences, exercise habits, and lifestyle factors. This study employs a data-driven approach to develop a predictive model based on wearable device motion monitoring data, aiming to elucidate the dynamic relationship between exercise and cardiovascular health and support personalized exercise interventions. Volunteers wore wearable devices to continuously record multiple physiological parameters (e.g., heart rate, movement speed, and step frequency) during exercise, generating a time-series dataset. A bidirectional long short-term memory network (BiLSTM) was utilized for time-series prediction, integrated with manba and OrthoNets attention mechanisms, leading to the development of the OTNmanba-BiLSTM prediction algorithm. This hybrid model enhances forecasting accuracy and stability by capturing temporal dependencies and critical features in physiological data, enabling the quantification of exercise-induced effects on cardiovascular function. Experimental results demonstrate that the OTNmanba-BiLSTM model effectively captures the impact of exercise on cardiovascular function, providing high-precision predictions across different exercise durations and intensities. Compared to conventional deep learning methods, the proposed model exhibits superior long-term prediction accuracy and generalization capability. The findings validate the quantitative association between exercise interventions and cardiovascular health improvements, offering actionable insights for personalized exercise regimens. This study validates the effectiveness of data-driven modeling in understanding the exercise-cardiovascular health relationship and establishes the OTNmanba-BiLSTM algorithm as a robust tool for predicting long-term cardiac health outcomes. The framework provides a foundation for scalable applications in exercise rehabilitation and cardiovascular health management. Future research should prioritize optimizing model architectures, integrating individualized factors (e.g., genetics, clinical data), and expanding applications in chronic disease exercise prescription, thereby advancing the integration of precision medicine and sports science
A067: Improving Children\u27s Community-Based Sports Coaching Service Quality: An SOR Model Analysis
No full textIn recent years, children’s community-based sports coaching has experienced rapid growth due to its convenience, safety, and tailored approach. However, parents’ trust in the quality of coaching services significantly impacts development. This study, grounded in the stimulus-organism-response (SOR) model, examines how service quality (stimulus) influences parental trust (organism) and their intention to utilize such services (response) from the perspective of parental trust. It analyzes existing service issues and proposes measures to enhance service quality, offering practical guidance for institutions and coaches. Method: This study combined the use of questionnaires and semi-structured interviews. First, questionnaires were distributed to 300 parents to collect their evaluations of service quality, including professionalism, process standardization, communication effectiveness, and service outcomes. Structural Equation Modeling (SEM) was used to analyze the data, examining the impact of service quality (stimulus) on parental trust and satisfaction (organism), and how these internal states influence behavioral intentions (response). Second, semi-structured interviews were conducted with 20 staff members from various institutions to gain deeper insights into the operational models and existing issues of community-based sports coaching services. The questionnaire and interview results revealed several issues in current community-based sports coaching services: Lack of transparency in coach qualifications; non-standardized service processes; insufficient communication between coaches and trainees; and Absence of evaluation mechanisms for training effectiveness. The Structural Equation Model (SEM) analysis demonstrated that service quality significantly influenced parental internal intention. Specifically, the quality of coaching services had a positive effect on parents\u27 trust. Parental trust significantly enhances parents\u27 intention to continue using the services (β = 0.52, p \u3c 0.01) and their intention to recommend them (β = 0.48, p \u3c 0.01). The findings indicate that improving the service quality of community sports coaches can significantly boost parental trust and satisfaction, thereby increasing their willingness to continue using the services. Therefore, sports training institutions should establish a coach certification system, enhance the standardization of courses, strengthen communication between coaches and children, and introduce third-party evaluation mechanisms. These measures hold significant practical importance for improving parental trust and satisfaction