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A285: Effects of Aerobic Exercise on Young Women with Binge Eating Disorder: A Randomized Controlled Trial
No full textBinge eating disorder (BED) is one of the most common eating disorders. It is more common in young women than in other groups and can lead to adverse physical and psychological problems. Previous studies have revealed that aerobic exercise is effective in reducing overeating, but it is not clear which exercise intensity works best. This study, therefore, compared the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on body composition and mental state of young women with BED. 30 BED young women (Mage = 20.07 years, SD = 0.20) who didn\u27t regularly participate in physical activity were selected from a Chinese university and randomly divided into 2 groups: the HIIT group (H, n=15) and the MICT group (M, n=15). Both interventions were performed twice a week for 8 weeks with the same exercise volume. During the experiment, heart rate and ratings of perceived exertion (RPE) of subjects were monitored, and the exercise volume increased gradually. Specific exercises were as follows: (1) H: treadmill exercise, 60-89% (heart rate reserve, HHR) for 4 min alternating 40-59% HHR for 3 min, and (2) M: treadmill exercise, 40-59% HHR. Binge eating scale (BES) scores, number of binges in the last week (NBLW), and the depression, anxiety, and stress scales-21 (DASS-21) scores were collected by validated questionnaires; Body mass index (BMI) and percentage of body fat (PBF) were measured by DXA before and after the experiment. Independent t-tests, Mann-Whitney U tests, two-way repeated measures ANOVA, and post-hoc tests were used in data analysis. (1) Before the intervention, there were no significant differences in age, weight, BES, NBLW, DASS-21, BMI, or PBF between the 2 groups. (2) After the experiment, all 5 clinical parameters mentioned above decreased significantly (p＜0.01) in both groups. (3) Compared to H, the BMI (1.14±0.56 vs 0.52±0.45, p＜0.05) and PBF (1.63±0.61 vs 0.96±0.58, p＜0.05) were reduced more significantly in M after the intervention. In accordance with previous findings, this study supported that aerobic exercise could treat, suggesting that both MICT and HIIT for 8 weeks could improve the body composition and mental state of BED young women, with MICT having a more significant impact on body composition. This study provided a scientific basis for making exercise prescriptions for BED patients. But more of different ages and genders, and clinical parameters should be included in future research
A257: Interdisciplinary Applications of Wearable Sensing Technology for Athletic Performance Enhancement and Injury Prevention
No full textAfter decades of development, sports biomechanics analysis technology has become a crucial tool for competitive sports training and public health management. Traditional laboratory equipment and surface electromyography (sEMG) signals have provided scientific bases for optimizing athletes\u27 movement patterns and studying the mechanisms of sports injuries. However, such equipment faces bottlenecks such as high costs, complex operations, and limited environments, leading grassroots sports teams and fitness institutions to rely predominantly on subjective observations or simple measurement tools. In recent years, breakthroughs in wearable sensor technology, through the integration of accelerometers, gyroscopes, and magnetometer modules, have significantly reduced equipment costs and support continuous monitoring in real-world scenarios such as sports fields and gyms. This paper aims to systematically review the innovative pathways of wearable technology in sports biomechanics analysis, construct a multidimensional evaluation framework for sports performance and injury prevention, and explore the challenges of technological transformation and the directions for standardization development. Method: 1) Analyzed global wearable sensor studies; 2) Tested multi-sensor devices on athletes in real-world settings; 3) Applied ML for biomechanical pattern decoding. 1) Triboelectric nanogenerators (TENGs) and flexible electrodes enable precise biomechanical capture in dynamic environments; 2) Kinetics-kinematics-physiology framework resolves single-parameter limitations; 3) ML-driven systems achieve adaptive load control and preclinical injury detection, shifting training from experiential to predictive paradigms. (1) Specialized Evaluation: Establish biomechanics databases and verification systems for specialized sports such as track and field and ball games to unify wearable sensor data with laboratory standards. (2) Cross-domain Collaboration: Collaborate with research institutions, manufacturers, and data platforms to formulate standards for device compatibility, open-source algorithms, and data privacy, promoting technological transformation. (3) Multidisciplinary Integration: Integrate sports physiology, flexible electronics, and AI technology to construct a closed-loop system of dynamic perception - intelligent analysis - autonomous regulation. For example, smart running shoes can dynamically adjust midsole cushioning performance based on real-time pressure distribution data, optimizing marathon runners\u27 running economy. (4) Precision Training: Utilize wearable systems to quantify technical details, load intensity, and fatigue thresholds, enhancing athletes\u27 technical efficiency. (5) Injury Early Warning: Develop predictive models based on biomechanical characteristics, shifting injury prevention from empirical intervention to intelligent prediction
A208: Application of Artificial Intelligence in Posture Correction
No full textIn the modern fast-paced life, poor postures are extremely common, leading to many health problems such as neck pain and back pain. Posture correction is of great significance for maintaining physical health, and the rise of artificial intelligence (AI) technology has opened a new path for posture correction. Posture correction means using specific means to restore and maintain the correct body posture. This study aims to systematically review the application of AI in the field of posture correction, clarify its advantages, limitations, and future development trends. A comprehensive search was carried out in domestic and foreign authoritative databases for research literature on the use of AI in posture correction. The research consisted of people of different ages and occupations with posture problems, and the research environment involved medical institutions, rehabilitation centers, and home settings. Research designs included experimental studies and case analyses. Intervention measures adopted various AI-based posture correction technologies, such as smart wearable device monitoring and computer vision analysis. Information such as the improvement of subjects\u27 postures and their feelings of use was extracted from the literature. Statistical methods were used to analyze quantitative data, and qualitative descriptions were analyzed by theme induction. AI has achieved remarkable results in posture correction. Smart wearable devices can monitor postures in real-time. Users can receive timely reminders of abnormal postures and then actively adjust their postures. Computer vision technology can accurately analyze postures and customize personalized rehabilitation training programs for patients to help them improve their postures. From user feedback, AI - AI-assisted tools have greatly improved the convenience of posture correction, making users more willing to cooperate in posture correction. Compared with traditional posture correction methods, the prominent advantages of AI are reflected in real-time monitoring and personalized customization. However, this study has certain limitations, lacking long-term follow-up data and comparative studies of different technologies. In the future, long-term effect tracking should be strengthened, and the effects of different AI technologies should be compared. This study provides a reference for clinical and public applications of AI in posture correction, helping to improve overall health
A076: Efficiency Evaluation of Yunnan Province National Fitness Public Service System: A Three-Stage DEA Model
No full textResearch grounded in establishing a service-oriented government is outlined in the 2024 Chinese Government Work Report. It integrates the core requirements of the 2025 Mass Sports Work, which emphasize promoting the equalization of public fitness services and enhancing the evaluation and monitoring of service efficiency. By conducting an in-depth analysis of regional case studies, research seeks to provide decision-making references for optimizing the development path of a service-oriented government to facilitate the construction of a more advanced public fitness service system nationwide. Method: Us three-stage DEA model to evaluate the efficiency of the public fitness service system in 129 counties of Yunnan Province in 2023:(1)Construct comprehensive evaluation index system, includ: input (facilities; human resources; financial input), output (proportion of the population engaged in physical exercise), and environmental variables (GDP; sports environment; industrial structure);(2)The DEA-BCC model adopted to measure the initial efficiency of each county as a decision-making unit (DMU);(3)The cross-sectional data SFA model used to decompose the input variable slack values and quantify the impact of environmental variables and random disturbances on efficiency;(4)A secondary efficiency assessment conducted using the adjusted input values after eliminating environmental factors to obtain more accurate efficiency results. (1) The comprehensive technical efficiency of the 129 counties in Yunnan Province ranged from 0.297 to 1. Among them, in the range of 0.9-1, 0.8-0.9, 0.6-0.8, 0-0.6 accounted for 19.80%, 15.52%, 44.96%, 19.72% respectively. (2) In SFA regression, the LR values of the seven indicators, including venue facilities and human input, were all higher than the critical value. (3) After three-stage adjustment, among the 129 counties, the efficiency of 78.29% of the counties improved, 11.63% declined, and 10.08% remained stable. (1) The level of comprehensive technical efficiency reflects the efficiency of the national fitness public service system. (2) SFA regression results show that the use of the stochastic frontier regression model is reasonable, and it is necessary to eliminate the influence of environmental variables in input relaxation to obtain more accurate efficiency values. (3) After three-stage adjustment, 78.29% of the counties\u27 efficiency improved, indicating that all the counties were at the same environmental level after eliminating the impact of environmental variables, and the poor environmental disadvantage of most counties was eliminated, resulting in an increase in the overall efficiency value
A281: Research on the Exploration of Practical Knowledge of Physical Education Teachers in China
No full textThe implementation of the new round of curriculum reform with a focus on core literacy has not only triggered changes in physical education teaching but also had a new impact on the professional development of physical education teachers in China. The long-standing challenge for frontline physical education teachers at primary and secondary schools is how to respond to the relationship between the demands of curriculum reform and daily physical education teaching practices. Practical knowledge of physical education teachers is the educational and teaching cognition formed by physical education teachers through solving specific problems, continuously reflecting on and learning from their experiences in teaching practice, and it possesses strong actionability. Method: Based on the background of physical education curriculum reform in China, this study uses literature review and logical analysis to examine the development prerequisites and value of practical knowledge of physical education teachers and explore the development path of practical knowledge of physical education teachers. The study found that in the physical education curriculum reform in China, there are still limitations in promoting the professional development of physical education teachers, such as decontextualization, standardization, and technological rationalization. There are mismatches, contrasts, and imbalances between practical knowledge and the advocated theories, deterministic logic, and authoritative discourse in curriculum reform. The paths for physical education teachers in China to develop practical knowledge in physical education teaching include capturing practical knowledge in contexts, narrating practical knowledge of physical education teachers, reflecting on actions to generate practical knowledge, reconstructing practical knowledge through application, and inheriting practical knowledge through interaction. These paths provide new opportunities and space for their professional development. The study found that the development of practical knowledge is an important shift in the professional development of physical education teachers in China. Both physical education researchers and frontline physical education teachers should pay more attention to the practical knowledge of physical education teachers. Future research should further discuss how to coordinate and develop in synergy with teachers\u27 theoretical knowledge, guide the improvement of physical education teaching behaviors, and contribute to promoting the high-quality development of school physical education in China
A294: Research on the Optimization Path of Urban Sports Public Service from the Perspective of Collaborative Governance
No full textUnder the double background of the acceleration of the new urbanization process and the increasing heterogeneity of the distribution of public sports resources, the supply of urban sports services faces systemic governance challenges. This study is committed to building a multi-subject collaborative governance framework and solving the fairness dilemma and sustainable development problem of public sports resource allocation through institutional innovation. Different from the traditional single-subject research paradigm, this study innovatively integrates the interaction mechanism of the three subjects of government, market, and society, aiming to establish a comprehensive governance strategy with policy adaptation. This case study analysis and policy analysis. Select large cities (Beijing, Shanghai, Chengdu) for a stratified systematic investigation of the governance characteristics of different urban forms. A collaborative governance model, including four-dimensional entities (government agencies, community organizations, market entities, and citizen groups) constructed, and social network analysis (SNA) was used to quantify the effectiveness of policy transmission. In terms of data collection, a three-stage research design was implemented: first, semi-structured interviews were conducted with 54 policy makers and implementers, then a questionnaire survey covering 1126 citizens was conducted, and finally, multiple rounds of expert demonstration were completed by the Delphi method to ensure the validity. The empirical analysis shows that the multi-governance mechanism can improve the efficiency of policy implementation by 37.2% (p \u3c 0.01) and the equity index of resource allocation by 28.5%. The verification of the governance model shows that there is a significant positive correlation between the degree of agent cooperation and the efficiency of resource allocation (r=0.824), and its explanatory effectiveness is 42.6% higher than that of the traditional bureaucracy model. It is worth noting that the synergistic effect generated by the tripartite cooperation between government, enterprise, and society can break through institutional barriers and form a flexible governance structure with spatial adaptability. This research breaks through the binary opposition framework of government-market in traditional public management theory and proposes a four-dimensional interactive governance paradigm. The main innovations are as follows: (1) Building a policy evaluation system including SNA indicators such as network centrality and structural hole index; (2) revealing the transformation mechanism of the inter-subject power game to cooperation and symbolism. Despite the limited geographical coverage of the sample (only in first-tier cities) and cross-sectional data constraints, the study conclusions provide key empirical support for the implementation of the National Fitness Program (2021-2025). Subsequent studies suggest extending to the urban agglomeration scale and introducing system dynamics models for long-term policy simulation
A207: AI Era and Sports Equity: A Sociological Perspective
No full textThis study explores the impact of artificial intelligence (AI) on sports equity and inclusion, focusing on its use in training, officiating, and talent selection. AI includes technologies like AI-driven training tools and systems, such as VAR. While AI can enhance access to sports resources, it may also worsen existing inequalities. The goal is to examine how AI influences fairness in sports and promotes inclusion, particularly in university sports, while considering its effects on athlete development, decision-making, and fan engagement across social groups. A qualitative approach was used to examine AI in university sports. Participants include sports students, faculty, coaches, and administrators. Data were collected through semi-structured interviews, focus groups, and surveys to understand perceptions of AI in training, officiating, and health monitoring. Data analysis follows a thematic approach, using sports sociology theories such as social structure and digital divide theory to identify key themes on AI’s impact on sports equity. AI affects sports equity in both positive and negative ways. AI-driven training and health monitoring improve accessibility, especially for student-athletes with fewer resources. However, AI in officiating and talent selection raises fairness concerns, with AI favoring well-funded programs. AI is also reshaping careers in sports, creating demand for AI skills but reducing traditional roles. Digital technologies like VR/AR change training and fan engagement but are limited by the digital divide. AI’s impact on decision-making raises ethical concerns, with AI recruitment favoring certain styles and overlooking diverse talents. Some athletes note that AI prioritizes male performance metrics over female athletes, highlighting the need for ethical AI in sports. This study confirms that AI enhances sports accessibility but reinforces technological divides. While AI-driven training and health monitoring promote inclusivity, socio-economic disparities persist in adoption. Unlike prior research on elite sports, this study highlights AI’s role in education and grassroots participation. Limitations include a university-based sample and a lack of quantitative validation. Future research should expand samples and integrate mixed methods to assess AI’s long-term impact on careers, ethics, and regulation. Addressing the digital divide and promoting ethical AI use can foster a more inclusive sports environment. Enhancing AI literacy among stakeholders can maximize benefits and mitigate risks, ensuring advancements align with social responsibility
A055: Aerobic Exercise Improves Sarcopenia and Gut-Muscle Axis in ABX-Treated SAMP8 Mice
No full textSarcopenia, characterized by reduced skeletal muscle mass and function, is a common geriatric condition that impairs mobility and quality of life. Its causes include neuroendocrine dysregulation, chronic inflammation, malnutrition, and gut microbiota imbalance. The gut microbiota influences muscle metabolism and function via the gut-muscle axis, and aerobic exercise has been shown to improve both gut microbiota composition and muscle function. This study explores whether aerobic exercise can alleviate sarcopenia induced by gut microbiota dysbiosis through the gut-muscle axis, offering a basis for exercise interventions. The study employed the senescence-accelerated mouse strain P8 (SAMP8) model. Gut microbiota dysbiosis was induced via a one-week intraperitoneal injection of a broad-spectrum antibiotic cocktail (ABX). Eight-week-old male SAMP8 mice were divided into four groups: control (CON), ABX-treated (ABX), exercise-trained (EXE), and ABX-treated with exercise (ABX+EXE). The EXE and ABX+EXE groups underwent an 8-week aerobic exercise program with progressively increasing intensity. Post-intervention assessments included skeletal muscle mass (quadriceps and gastrocnemius weights), muscle strength (hanging and grip strength tests), muscle fiber type (HE staining and immunohistochemistry), oxidative stress markers (malondialdehyde and superoxide dismutase), gut microbiota composition (16S rRNA sequencing), intestinal barrier function (serum diamine oxidase and D-lactate levels), and neuromuscular junction protein expression (Western blot). Data were analyzed using SPSS 26.0, expressed as mean ± SD, and compared using one-way ANOVA. ABX treatment significantly reduced gut microbiota diversity (P \u3c 0.01), disrupted intestinal barrier function (elevated serum diamine oxidase and D-lactate, P\u3c0.05), and exacerbated sarcopenia (decreased muscle mass and strength, P \u3c 0.01). Aerobic exercise significantly improved muscle mass (P \u3c 0.01) and strength (P \u3c 0.01) in ABX-treated mice, increased fast-twitch muscle fiber proportion (P \u3c 0.05), and reduced oxidative stress (P \u3c 0.05). Exercise also modulated gut microbiota (increased diversity, P \u3c 0.01), enhanced intestinal barrier function (decreased diamine oxidase and D-lactate, P \u3c 0.05), and promoted neuromuscular junction protein expression (P \u3c 0.05). This study elucidates the mechanisms by which aerobic exercise ameliorates sarcopenia via the gut-muscle axis, underscoring the role of gut microbiota. However, the small sample size and single animal model limit the findings\u27 generalizability. Future research should expand the sample size and incorporate diverse models or clinical studies to validate this mechanism. This study supports aerobic exercise as a non-pharmacological intervention for sarcopenia, potentially improving quality of life in the elderly
A239: Optimization Study of Elite Volleyball Players\u27 Spiking Speed Based on AI Muscle Patch Intelligence Analysis
No full textSpiking speed is an important indicator of volleyball players\u27 offensive ability, and the weakness of arm muscle strength may affect the performance of spiking. Traditional EMG equipment is difficult to meet the training needs of elite athletes due to the lag in data analysis. In this study, we used an “AI muscle patch” to collect EMG signals of volleyball players\u27 arms during analyzed the weak links of individual muscles through an AI model, identified the weak chains of muscles that affect the speed of spiking, and formulated a personalized training program to strengthen the muscles to improve the spiking speed. The study aims to verify the application value and promotion potential of AI real-time analysis technology in high-level volleyball training. Method: In this study, 18 elite male volleyball athletes (8 Master athletes and 10 Division I athletes) were selected, and a pre- and post-test experimental design was used. First, measured the spike speed in the natural state (baseline) and wore AI muscle patches to collect the arm EMG signals during the spike. A personalized training program was developed based on the results of the AI macromodel analysis, with a training cycle of 6 weeks, 4 times per week, and the spiking speed (km/h) was measured again after the intervention. The data were analyzed using a paired t-test, and the significance level was set at p \u3c 0.05. AI analysis revealed that the weak muscles of the athletes\u27 arms were mainly concentrated in the distal triceps brachii, radial wrist extensors, and superficial finger flexors. After 6 weeks of individualized training intervention targeting these areas, the spike speed was significantly increased from 72.3±3.1 km/h to 78.5±3.6 km/h (p=0.018). The results showed that the AI muscle patch combined with AI model analysis could accurately identify the weak links of muscle strength and effectively improve the ball-spiking speed through personalized training. This study verifies the effectiveness of the AI muscle patch, which can accurately identify the weak links of muscles of elite volleyball players and significantly improve the spiking speed through targeted training, which is more accurate and efficient than the traditional method of AI-assisted training. The study provides a new means for volleyball-specific training and a reference for the application of AI technology in sports training, which can be expanded to technical training such as blocking and serving, as well as other sports in the future
A263: Exploring CADD-Based Binding Modes of Androstenedione and Its Metabolites with Potential in vivo Targets
No full textThe abuse of androstenedione, an endogenous steroid hormone, among athletes to enhance performance is a significant concern in sports. Current anti-doping detection methods are limited by short detection windows and high false-positive rates, largely due to the transient nature of primary metabolites. To address these challenges, this study employs computer-aided drug design (CADD) to identify stable, long-acting metabolites of androstenedione that can extend the detection window and improve anti-doping efficacy. The integration of CADD with sports physiology principles allows for a more comprehensive understanding of how exercise-induced metabolic fluctuations can influence the detection of these metabolites. Method: Molecular docking simulations using AutoDock (v1.5.6) were performed to analyze interactions between androstenedione, its nine metabolites, and two key enzymes involved in steroid metabolism: 17β-hydroxysteroid dehydrogenase (PDB ID: 1qyx) and cytochrome P450 17α (PDB ID: 3n9y). Ligand structures were retrieved from PubChem, optimized using Chem3D, and converted to mol2/pdbqt formats. Receptor proteins were preprocessed by removing water molecules and adding hydrogen atoms. Semi-flexible docking with 50 cycles per ligand-receptor pair was conducted, and outcomes were evaluated based on binding energy, root mean square deviation (RMSD), and hydrogen bond counts. The molecular docking results revealed that 17α-hydroxyprogesterone and 6β-hydroxyandrosterone exhibited the lowest binding energies (-8.82 and -8.81 kcal/mol, respectively) with 17β-hydroxysteroid dehydrogenase. These metabolites also had favorable RMSD values (13.35 Å and 13.27 Å) and formed two hydrogen bonds each. The stable binding conformations of these metabolites suggest that they may be retained in biological systems for longer periods, making them potential long-term biomarkers for the detection of androstenedione abuse. In contrast, interactions with cytochrome P450 17α showed weaker binding affinities, with epitestosterone displaying the lowest binding energy (-7.29 kcal/mol). The hydroxylation of 6β-hydroxyandrosterone was found to correlate with enhanced polar interactions, which may delay renal excretion. This is particularly relevant in the context of exercise physiology, where hydration status and metabolic rates can significantly influence detection thresholds. This study identifies 17α-hydroxyprogesterone and 6β-hydroxyandrosterone as promising biomarkers for detecting androstenedione abuse. These findings align with prior research on prolonged clearance rates of hydroxylated metabolites. Future research should integrate dynamic physiological models and experimental assays to refine detection thresholds. This CADD-driven approach offers a scalable framework for personalized anti-doping strategies, potentially enabling late-stage sample collection to reduce false positives caused by transient physiological fluctuations. Limitations include reliance on in silico predictions and the need for in vivo validation