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SIMION, Alexandru, and Gabriel MANGRA. "STRATEGIC OPTIMIZATION OF THE MANAGEMENT OF SPORTS ORGANIZATIONS." Management & Marketing 21, no. 1 (April 30, 2023): 151–61. http://dx.doi.org/10.52846/mnmk.21.1.09.
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The ways in which sport organizations monitor their operations and evaluate their performance involves careful analysis with a focus on the special characteristics of sport organizations and how these characteristics create the need for sport-specific performance management models. The purpose of the research is the development of models for the analysis of the management of sports organizations, in order to identify the factors of influence and ways to improve their efficiency and effectiveness, respectively to increase the performance of sports organizations. The importance of using performance management models is highlighted, not only by the need to respond to the conflicting requirements of several interested parties, but also by the need to manage risk. We have found a systematic treatment of performance management to be an essential tool for identifying strengths and weaknesses and discovering ways in which overall organizational performance can be improved. Thus, a performance management model is crucial for the long-term success of sports organizations.
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Pérez-Castilla, Alejandro, and Felipe García-Pinillos. "Sports Biomechanics Applied to Performance Optimization." Applied Sciences 14, no. 9 (April 24, 2024): 3590. http://dx.doi.org/10.3390/app14093590.
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Morriën, Floor, Matthew J. D. Taylor, and Florentina J. Hettinga. "Biomechanics in Paralympics: Implications for Performance." International Journal of Sports Physiology and Performance 12, no. 5 (May 2017): 578–89. http://dx.doi.org/10.1123/ijspp.2016-0199.
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Purpose:To provide an overview of biomechanical studies in Paralympic research and their relevance for performance in Paralympic sports.Methods:The search terms paralympic biomechanics, paralympic sport performance, paralympic athlete performance, and paralympic athlete were entered into the electronic database PubMed.Results:Thirty-four studies were found. Biomechanical studies in Paralympics mainly contributed to performance enhancement by technical optimization (n = 32) and/or injury prevention (n = 6). In addition, biomechanics was found to be important in understanding activity limitation caused by various impairments, which is relevant for evidence-based classification in Paralympic sports (n = 6). Distinctions were made between biomechanical studies in sitting (41%), standing (38%), and swimming athletes (21%). In sitting athletes, mostly kinematics and kinetics in wheelchair propulsion were studied, mainly in athletes with spinal-cord injuries. In addition, kinetics and/or kinematics in wheelchair basketball, seated discus throwing, stationary shot-putting, hand-cycling, sit-skiing, and ice sledge hockey received attention. In standing sports, primarily kinematics of athletes with amputations performing jump sports and running and the optimization of prosthetic devices were investigated. No studies were reported on other standing sports. In swimming, mainly kick rate and resistance training were studied.Conclusions:Biomechanical research is important for performance by gaining insight into technical optimization, injury prevention, and evidence-based classification in Paralympic sports. In future studies it is advised to also include physiological and biomechanical measures, allowing the assessment of the capability of the human body, as well as the resulting movement.
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Donohue, Brad, Yulia Gavrilova, Marina Galante, Elena Gavrilova, Travis Loughran, Jesse Scott, Graig Chow, Christopher P. Plant, and Daniel N. Allen. "Controlled Evaluation of an Optimization Approach to Mental Health and Sport Performance." Journal of Clinical Sport Psychology 12, no. 2 (June 1, 2018): 234–67. http://dx.doi.org/10.1123/jcsp.2017-0054.
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Athletes experience unique stressors that have been indicated to compromise their mental wellness and sport performance, yet they underutilize mental health services. Indeed, very few mental health interventions for athletes have been developed to fit sport culture, and well-controlled mental health outcome research in athlete populations is warranted. In this randomized controlled trial, a sport specific optimization approach to concurrent mental health and sport performance (The Optimum Performance Program in Sports; TOPPS) was examined. Seventy-four collegiate athletes (NCAA = 42; club = 11; intramural = 21) formally assessed for mental health diagnostic severity were randomly assigned to TOPPS or campus counseling/psychological services as usual (SAU) after baseline. Dependent measures assessed general mental health, mood, mental health factors affecting sport performance in training, competition and life outside of sports, days using substances, sexual risk behaviors, happiness in relationships, relationships affecting sport performance, and contributions of relationship to sport performance. Intent to treat repeated measures analyses indicated that participants in TOPPS consistently demonstrated better outcomes than SAU up to 8-months post-randomization and for mental health/substance use measures, particularly when diagnostic criteria were most severe. Recommendations are provided in light of the results to assist sport-specific mental health intervention development and implementation within athlete populations.
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Tan, Xuefeng, Chenggen Guo, Pu Sun, and Shaojie Zhang. "Performance Optimization Method of Community Sports Facilities Configuration Based on Linear Planning Model." Complexity 2022 (March 29, 2022): 1–7. http://dx.doi.org/10.1155/2022/4489802.
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The conventional community sports facility allocation methods have high minimum costs, and a new community sports facility allocation performance optimization method is designed based on a linear programming model in order to reduce the performance capital investment. The standardized community sports facility allocation performance objective function is established, and a pairwise model is built to divide the feasible and optimal solutions, and the feasible solutions and their constraints are found out. Establish a community sports facility configuration performance optimization model, delineate the boundaries of the optimal solution by bifurcation, and set the feasible domain of the performance optimization model. The performance optimization algorithm is designed to improve the speed of community sports facility allocation performance optimization. In the experiment, the method is compared with data-driven method, digital management method, and evolutionary game algorithm, which requires less capital investment in spring, autumn, and winter than digital management method and evolutionary game algorithm, and the minimum capital investment in summer is less than the other three methods. From the above experimental data, it is clear that the performance optimization method has the smallest minimum capital investment and achieves the purpose of reducing the input cost.
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Deuster, Patricia A., and Francis G. OʼConnor. "Human Performance Optimization." Journal of Strength and Conditioning Research 29 (November 2015): S52—S56. http://dx.doi.org/10.1519/jsc.0000000000001118.
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Podgorelec, Vili, Špela Pečnik, and Grega Vrbančič. "Classification of Similar Sports Images Using Convolutional Neural Network with Hyper-Parameter Optimization." Applied Sciences 10, no. 23 (November 27, 2020): 8494. http://dx.doi.org/10.3390/app10238494.
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With the exponential growth of the presence of sport in the media, the need for effective classification of sports images has become crucial. The traditional approaches require carefully hand-crafted features, which make them impractical for massive-scale data and less accurate in distinguishing images that are very similar in appearance. As the deep learning methods can automatically extract deep representation of training data and have achieved impressive performance in image classification, our goal was to apply them to automatic classification of very similar sports disciplines. For this purpose, we developed a CNN-TL-DE method for image classification using the fine-tuning of transfer learning for training a convolutional neural network model with the use of hyper-parameter optimization based on differential evolution. Through the automatic optimization of neural network topology and essential training parameters, we significantly improved the classification performance evaluated on a dataset composed from images of four similar sports—American football, rugby, soccer, and field hockey. The analysis of interpretable representation of the trained model additionally revealed interesting insights into how our model perceives images which contributed to a greater confidence in the model prediction. The performed experiments showed our proposed method to be a very competitive image classification method for distinguishing very similar sports and sport situations.
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Chen, Si, and Gang Zhao. "High-Performance Server-Based Live Streaming Transmission Optimization for Sports Events in Smart Cities." Mobile Information Systems 2021 (April 9, 2021): 1–7. http://dx.doi.org/10.1155/2021/9958703.
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Smart cities allow cities to run more efficiently and have been approved by a lot of cities. During the process of building smart cities, a large amount of data is generated. Particularly, live sports events have been regarded as the inalienable part of smart cities. However, with the improvement in the quality of life, people tend to obtain better watching experience in terms of sports events. For such purpose, this paper proposes the live streaming transmission optimization method based on high-performance server, called HPTO, including two main modules, that is, high-performance server optimization and transmission optimization. Specifically, for the server optimization, this paper devises a distributed storage strategy to avoid producing the internal disk fragments and improve the writing efficiency of sports videos. For the transmission optimization, this paper devises a deep-learning-based video compression strategy to save the storage space of server and accelerate the transmission of sports videos. In addition, this paper makes simulation experiments based on PyCharm. The experimental results show that HPTO has higher storage efficiency, smaller transmission time, and lower packet loss rate than benchmarks, which indicates that the proposed two aspects of optimization strategies (server optimization and transmission optimization) are efficient.
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Hood, Simon, Thomas McBain, Matt Portas, and Iain Spears. "Measurement in Sports Biomechanics." Measurement and Control 45, no. 6 (July 2012): 182–86. http://dx.doi.org/10.1177/002029401204500604.
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One of the major roles of a sports biomechanist or coach is to assess the movement patterns within sports performances. Movements can be analysed to enhance an individual's technique in terms of efficiency or to provide technical advantage. This paper aims to highlight the different measurement techniques available for the biomechanist to assess the movement characteristics of the technical and mechanical aspects of athletic performance.
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Sun, Wei Min, Bin Gao, and Wei Shou Zhang. "Long Jump Technique Based on the Method of Mechanical Analysis." Advanced Materials Research 507 (April 2012): 208–11. http://dx.doi.org/10.4028/www.scientific.net/amr.507.208.
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It is the development characteristics of modern sports to use of modern science and technology such as computers and others. In a variety of sports science, the application of science and technology in modern sport based on the mechanical analysis play an important role in order to improve athletic performance and motor skills, as well as the optimization of sports equipment. Therefore, The analysis on mechanical optimal motion can provide the athletes the best sports attitude and sports skills, thereby improving athletes scientific training result.To provide scientific theoretical basis and promote the development of sports, this paper focused on the scientific mechanics analysis on long jump technique.
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VIGH-LARSEN, JEPPE F., NICKLAS JUNGE, LYNN CIALDELLA-KAM, RITA TOMÁS, LAURA YOUNG, PETER KRUSTRUP, MAGNI MOHR, and LARS NYBO. "Testing in Intermittent Sports—Importance for Training and Performance Optimization in Adult Athletes." Medicine & Science in Sports & Exercise 56, no. 8 (March 9, 2024): 1505–37. http://dx.doi.org/10.1249/mss.0000000000003442.
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ABSTRACT Performance in intermittent sports relies on the interplay between multiple physiological systems determining the capacity to perform short explosive efforts as well as repeated intense actions with limited recovery over the course of an entire game. Testing should reflect these demands to allow for sport- and position-specific capacity analyses that eventually may translate into optimized training and improved performance. This may include individual load management and optimized training prescription, intensity targeting for specific positions or individual athletes, as well as benchmarking for monitoring of training progression and enhanced engagement of athletes. This review provides an overview of available tests in different exercise domains identified as relevant (from assessment of single explosive actions to intermittent endurance capacity), forming the basis for recommendations on how to compose a comprehensive yet feasible test battery that may be integrated into the seasonal competition and training plan. The test procedures should cover the performance spectrum of relevance for the individual athlete—also in team sports to account for positional differences. We emphasize the benefits of sport-specific tests, highlight parameters of importance for test standardization, and discuss how the applied test battery may be supplemented with secondary tests directed toward specific energy systems to allow for more in-depth analyses when required (e.g., in terms of an underperforming athlete). The synergy between testing and tracking of match performance (utilizing time-motion or global positioning systems) is highlighted, and although tracking cannot substitute for testing, combining the tools may provide a comprehensive overview of the physiological demands and performance during competition contextualized to the athletes’ maximal exercise capacity.
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Penichet-Tomas, Alfonso. "Applied Biomechanics in Sports Performance, Injury Prevention, and Rehabilitation." Applied Sciences 14, no. 24 (December 12, 2024): 11623. https://doi.org/10.3390/app142411623.
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Sun, Wei. "Sports Performance Prediction Based on Chaos Theory and Machine Learning." Wireless Communications and Mobile Computing 2022 (June 26, 2022): 1–11. http://dx.doi.org/10.1155/2022/3916383.
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In order to combine chaos theory and machine learning technology to predict sports performance, a research on sports performance prediction based on chaos theory and machine learning is proposed. This paper takes the sports performance as the goal to predict the data; introduce the chaos theory algorithm, and combine the neural network system and particle swarm optimization algorithm to actively train sports results and ensure the quality of performance prediction. The comparison between shot put data prediction and real data shows that the prediction results given by the model have little deviation and can provide technical services for performance prediction for special sports training. When predicting the sports performance of college students, the prediction accuracy of sports performance of each subject is no less than 90%, which proves that this system can be used in college sports management. The delay time of the model data is short, which is mainly related to the correlation coefficient. When the coefficient is determined to be 0.02, the prediction delay time is 5 s, which can effectively complete the prediction and analysis of sports performance. The combined model has various technical advantages such as chaos theory, neural system, and particle optimization. It has strong sports performance prediction ability and can provide technical support for performance prediction for athletes’ training, college sports management, and other related sports industries.
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Nindl, Bradley C., Dianna P. Jaffin, Michael N. Dretsch, Samuel N. Cheuvront, Nancy J. Wesensten, Michael L. Kent, Neil E. Grunberg, et al. "Human Performance Optimization Metrics." Journal of Strength and Conditioning Research 29 (November 2015): S221—S245. http://dx.doi.org/10.1519/jsc.0000000000001114.
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Wang, Caixia. "Optimization of sports effect evaluation technology from random forest algorithm and elastic network algorithm." PLOS ONE 18, no. 10 (October 20, 2023): e0292557. http://dx.doi.org/10.1371/journal.pone.0292557.
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This study leverages advanced data mining and machine learning techniques to delve deeper into the impact of sports activities on physical health and provide a scientific foundation for informed sports selection and health promotion. Guided by the Elastic Net algorithm, a sports performance assessment model is meticulously constructed. In contrast to the conventional Least Absolute Shrinkage and Selection Operator (Lasso) algorithm, this model seeks to elucidate the factors influencing physical health indicators due to sports activities. Additionally, the incorporation of the Random Forest algorithm facilitates a comprehensive evaluation of sports performance across distinct dimensions: wrestling-type sports, soccer-type sports, skill-based sports, and school physical education. Employing the Top-K criterion for evaluation and juxtaposing it with the high-performance Support Vector Machine (SVM) algorithm, the accuracy is scrutinized under three distinct criteria: Top-3, Top-5, and Top-10. The pivotal innovation of this study resides in the amalgamation of the Elastic Net and Random Forest algorithms, permitting a holistic contemplation of the influencing factors of diverse sports activities on physical health indicators. Through this integrated methodology, the research achieves a more precise assessment of the effects of sports activities, unveiling a range of impacts various sports have on physical health. Consequently, a more refined assessment tool for sports performance detection and health development is established. Capitalizing on the Elastic Net algorithm, this research optimizes model construction during the pivotal feature selection phase, effectively capturing the crucial influencing factors associated with different sports activities. Concurrently, the integration of the Random Forest algorithm augments the predictive prowess of the model, enabling the sports performance assessment model to comprehensively unveil the extent of impact stemming from various sports activities. This study stands as a noteworthy contribution to the arena of sports performance assessment, offering substantial insights and advancements to both sports health and research methodologies.
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Yang, Xiaojing, and Sunkai Qi. "Research on optimization and design of sports teaching actions based on biomechanics." Molecular & Cellular Biomechanics 21, no. 4 (December 11, 2024): 495. https://doi.org/10.62617/mcb495.
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The design of sports teaching approaches is an important part of improving athletic performance and skill development among players. As sports grow more competitive, the demand for new and effective teaching methods has never been higher. The limitations of conventional coaching techniques sometimes depend on anecdotal evidence and subjective assessments, which provide inconsistent outcomes for training. The purpose of this study is to enhance athletic performance and reduce injury risks by developing sports teaching actions based on biomechanics. The proposed novel chaos sparrow search fine-tuned efficient random forest (CSS-ERF) employed the relationship between biomechanical parameters and performance outcomes. Biomechanical data was gathered from athletes utilizing wearable sensors and motion capture technologies as they performed several sports-related activities. The data preprocessing will be cleaned to remove noise and outliers from the dataset. Ground Reaction Forces (GRF) are used to extract key features relevant to performance and injury risk from the preprocessed data. Findings show that training strategies and athlete performance have significantly improved, and the CSS-ERF model has demonstrated a high degree of accuracy in forecasting the best biomechanical configurations with an F1 value of 0.984, accuracy of 0.989, recall of 0.985, and precision of 0.986. By offering an innovative approach to enhancing sports actions through biomechanical insights and promoting a greater comprehension of movement mechanics and their impact on athletic performance, this research advances the area of sports science.
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Paulson, Thomas, and Victoria Goosey-Tolfrey. "Current Perspectives on Profiling and Enhancing Wheelchair Court Sport Performance." International Journal of Sports Physiology and Performance 12, no. 3 (March 2017): 275–86. http://dx.doi.org/10.1123/ijspp.2016-0231.
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Despite the growing interest in Paralympic sport, the evidence base for supporting elite wheelchair sport performance remains in its infancy when compared with able-bodied (AB) sport. Subsequently, current practice is often based on theory adapted from AB guidelines, with a heavy reliance on anecdotal evidence and practitioner experience. Many principles in training prescription and performance monitoring with wheelchair athletes are directly transferable from AB practice, including the periodization and tapering of athlete loads around competition, yet considerations for the physiological consequences of an athlete’s impairment and the interface between athlete and equipment are vital when targeting interventions to optimize in-competition performance. Researchers and practitioners are faced with the challenge of identifying and implementing reliable protocols that detect small but meaningful changes in impairment-specific physical capacities and on-court performance. Technologies to profile both linear and rotational on-court performance are an essential component of sport-science support to understand sport-specific movement profiles and prescribe training intensities. In addition, an individualized approach to the prescription of athlete training and optimization of the “wheelchair–user interface” is required, accounting for an athlete’s anthropometrics, sports classification, and positional role on court. In addition to enhancing physical capacities, interventions must focus on the integration of the athlete and his or her equipment, as well as techniques for limiting environmental influence on performance. Taken together, the optimization of wheelchair sport performance requires a multidisciplinary approach based on the individual requirements of each athlete.
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Lyu, Xiangjialin. "Research on Volleyball Fluid Rehydration and Physical Fitness Optimization from the Perspective of Multiple Positions." BCP Education & Psychology 4 (May 31, 2022): 219–26. http://dx.doi.org/10.54691/bcpep.v4i.795.
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Volleyball players in the process of training and competition need timely fluid to maintain good physical fitness and excellent performance. In volleyball, players at different positions have different tasks and performance and energy expenditure. There are different roles on the volleyball court, including attack, side attack, setter, receiver and free man. At present, the amount of research on sports fluid replenishment of volleyball players is relatively less than other sports. In view of the development trend of "full, high, fast, turn and change" in modern volleyball and the present situation of the various roles of volleyball players, this paper puts forward some thoughts on the design of fluid replenishment plan for volleyball players and the design of fluid replenishment plan according to the position of volleyball players on the court. In order to solve the above problem, this paper analyzed and summarized the sports rehydration research, explore the formation of volleyball athletes sport fatigue mechanism, and based on the special movement quality and physiology characteristics of volleyball players from each department job position classification under the new Angle of view put forward the corresponding requirement of the volleyball players movement rehydration and focus, targeted to help the volleyball coach team to design and improve the rehydration solution of athletes in each department job position and rehydration regulation, so as to improve the level of the whole movement of volleyball sports teams, promote the development of volleyball and volleyball sports in our country.
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Ogugua Chimezie Obi, Samuel Onimisi Dawodu, Shedrack Onwusinkwue, Femi Osasona, Akoh Atadoga, and Andrew Ifesinachi Daraojimba. "Data science in sports analytics: A review of performance optimization and fan engagemen." World Journal of Advanced Research and Reviews 21, no. 1 (January 30, 2024): 2663–70. http://dx.doi.org/10.30574/wjarr.2024.21.1.0370.
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The intersection of data science and sports analytics has emerged as a powerful catalyst in revolutionizing the landscape of sports performance and fan engagement. This review explores the multifaceted role of data science in optimizing athlete performance and enhancing the overall experience for sports enthusiasts. In the realm of performance optimization, data science has become an indispensable tool for coaches, analysts, and athletes alike. Advanced statistical models, machine learning algorithms, and predictive analytics are employed to extract actionable insights from massive datasets encompassing player statistics, biomechanical data, and in-game dynamics. These insights not only aid in strategic decision-making but also facilitate personalized training regimens, injury prevention strategies, and the fine-tuning of game tactics. The integration of wearables and sensors further amplifies the granularity of data, enabling a more comprehensive understanding of an athlete's physical and mental well-being. Beyond the confines of the playing field, data science has significantly reshaped the landscape of fan engagement. Leveraging big data, social media analytics, and user behavior patterns, sports organizations can tailor content and interactions to create a more immersive and personalized experience for fans. Predictive modeling allows for the anticipation of fan preferences, enabling targeted marketing strategies and the creation of interactive platforms that foster a deeper connection between fans and their favorite teams. In conclusion, the symbiotic relationship between data science, sports analytics, performance optimization, and fan engagement is at the forefront of innovation in the sports industry. As technology continues to evolve, the integration of cutting-edge data-driven methodologies will undoubtedly redefine the way athletes train, compete, and captivate audiences worldwide. This review provides a comprehensive overview of the current landscape, highlighting the transformative impact of data science in shaping the future of sports.
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Wang, Yuanshuo. "Optimization Strategy of Basketball Players' Sports Performance Based on Literature Analysis." Advances in Economics, Management and Political Sciences 138, no. 1 (January 3, 2025): 198–204. https://doi.org/10.54254/2754-1169/2024.19235.
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With the change and development of The Times, our sports continue to have new technologies into the integration, the same has been improved, the world record is constantly refreshed. In the field of basketball, international events such as the Olympic Games and the World Cup have attracted wide attention around the world, which has promoted the globalization of basketball. At the same time, with the development of science and technology, training has become more and more scientific, and the physical quality of athletes has also been strengthened, for example, the height of players in basketball has been increasing. Looking forward to the future, there will be more and more players over 200cm, and the global basketball strength will gradually be balanced, and there will not be a situation where only a few countries dominate. If the athlete has a good training environment and a professional back team, and the athlete is very hard, through scientific training and diet, it will also perform very well on the court. Through research and data analysis, this paper explores how to improve the basic quality of athletes through scientific and reasonable techniques and methods.
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Bădescu, Delia, Nicoleta Zaharie, Iulian Stoian, Mircea Bădescu, and Cristian Stanciu. "A Narrative Review of the Link between Sport and Technology." Sustainability 14, no. 23 (December 6, 2022): 16265. http://dx.doi.org/10.3390/su142316265.
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Background: Research on the application of technology in sports in Romania is completely lacking, and the existing studies at the international level have mainly been carried out in recent years. We considered it appropriate to highlight the best practice models of technology application in sports that can be multiplied, adapted, improved, and widely used. The paper aims to identify the use of technology and devices in sports, with an emphasis on their role in training and competitions with the aim of improving sports performance, to provide sports specialists, organizations, and authorities with a wide range of information regarding the connection between sport and technology. The results obtained regarding the application of technology in sports refer mainly to the following: techniques and technologies used in training and competition (portable localization technology and global positioning systems (GPS); Virtual Reality (VR) technology; video analysis; digital technologies integrated into sports training); aspects of sports training targeted through the use of technology (use of technology for athlete health, recovery, and injury management; use of technology for monitoring sports performance and various body indicators); training optimization and ecological dynamics and the sustainable development of sports. Conclusions: Unitary research, at a European or even global level, in a uniform theoretical and practical framework, could lead to much more efficient training with large increases in sports performance. The coaches and specialists working with the athlete determine the specificity of some elements of the training, depending on the characteristics of each athlete. Large clubs could become a factor in generating and disseminating knowledge related to training and competition monitoring, sports performance enhancement, and health, recovery, and injury management. Research directions for the use of technology in sport and the formation of connections with other fields can be extended. For example, combined technologies assisted by specialized software can be used. Creativity must be the starting point for the use and combination of existing technologies in sports and for the creation of new ones. Their creation and use involve the teamwork of athletes, coaches, and specialists from different fields, such as sports, physiology, psychology, biomechanics, informatics, etc.
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Tiwari, Ashish. "The Role of Friction in Athletic Performance: A Descriptive Analysis." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 28, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31958.
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Friction is a fundamental force that has a substantial impact on athletic performance across all sports disciplines. This descriptive research investigates the varied impact of friction in building athletic skill. This study looks at how friction affects running, jumping, throwing, and other sports activities by examining static and kinetic frictional forces, as well as elements that influence frictional interactions. The research examines the interaction of athletes, footwear, surfaces, and equipment to explain how friction governs propulsion, stability, and efficiency in sports activity. The findings of this study have important significance for players, coaches, and sports scientists, as they provide avenues for optimizing training techniques, equipment design, and performance tactics for increased athletic achievement. Keywords Friction , Athletic Performance , Role , Descriptive Analysis , Surface Friction , Footwear Friction , Sports Science , Biomechanics , Performance Optimization , Surface Interaction , Traction , Stability , Movement Efficiency , Injury Prevention ,Training Strategies
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Donohue, Bradley, Elena Gavrilova, Michelle Strong, and Daniel N. Allen. "A sport-specific optimization approach to mental wellness for youth in low-income neighborhoods." European Physical Education Review 26, no. 3 (August 2020): 695–712. http://dx.doi.org/10.1177/1356336x20905324.
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Psychiatric disorders, particularly substance use disorders, are an impactful and highly prevalent public health concern in youth from low-income neighborhoods (YLINs). Indeed, prevention and intervention programs for mental health disorders that have evidenced improvements in youth from general population are not well integrated into community resources of YLINs and appear to be a poor fit for YLINs. Along this vein, experts have indicated there is an immediate need to empirically refine existing evidence-based mental health programs to be less stigmatizing, more culturally sensitive, relevant, and engaging for YLINs. To assist in addressing this need, we describe an innovative sport-specific optimization approach to mental wellness that is tailored for use in YLINs. Derived from Family Behavior Therapy, The Optimum Performance Programme in Sports (TOPPS) was developed to be implemented within the umbrella of well-established sport organizations that are accepted within low-income communities (e.g. YMCA, Boys & Girls Club) or primary and secondary school systems. TOPPS is designed to address both prevention and intervention of mental health disorders through a focus on overall wellness and sport performance, and incorporation of engagement methods, significant others, sport/physical education, and evidence-supported methods of addressing culture. Given the absence of sport-specific mental health intervention for youth, TOPPS may be appropriate in this population. However, formal evaluation of TOPPS in youth samples is warranted.
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McDevitt, Sam, Haley Hernandez, Jamison Hicks, Russell Lowell, Hamza Bentahaikt, Reuben Burch, John Ball, et al. "Wearables for Biomechanical Performance Optimization and Risk Assessment in Industrial and Sports Applications." Bioengineering 9, no. 1 (January 13, 2022): 33. http://dx.doi.org/10.3390/bioengineering9010033.
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Wearable technologies are emerging as a useful tool with many different applications. While these devices are worn on the human body and can capture numerous data types, this literature review focuses specifically on wearable use for performance enhancement and risk assessment in industrial- and sports-related biomechanical applications. Wearable devices such as exoskeletons, inertial measurement units (IMUs), force sensors, and surface electromyography (EMG) were identified as key technologies that can be used to aid health and safety professionals, ergonomists, and human factors practitioners improve user performance and monitor risk. IMU-based solutions were the most used wearable types in both sectors. Industry largely used biomechanical wearables to assess tasks and risks wholistically, which sports often considered the individual components of movement and performance. Availability, cost, and adoption remain common limitation issues across both sports and industrial applications.
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Sañudo, Sánchez-Hernández, Bernardo-Filho, Abdi, Taiar, and Núñez. "Integrative Neuromuscular Training in Young Athletes, Injury Prevention, and Performance Optimization: A Systematic Review." Applied Sciences 9, no. 18 (September 12, 2019): 3839. http://dx.doi.org/10.3390/app9183839.
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The aim of this systematic review was to evaluate the current evidence by assessing the effectiveness of integrative neuromuscular training programs in injury prevention and sports performance in young athletes. Different data sources were analyzed up to January 2018. Eligible studies contained information on population (young athletes), intervention (neuromuscular training), comparator (control group or another exercise intervention), outcomes (injury prevention or sport performance), and study design (randomized trials or prospective studies). The trials were restricted based on the language (English) and for publication date (after January 1st, 2007). Fourteen randomized controlled trials were included: Seven included dynamic stability-related outcomes. Three assessed the coordination performing fundamental movements and sport-specific skills, while other five studies analyzed muscle strength and two assessed plyometric tests. Agility was evaluated in three studies and speed tests were also considered by four studies. Finally, fatigue resistance in three studies and injury risk in four were assessed. This review provides evidence that integrative neuromuscular training programs can enhance performance and injury prevention in young athletes, taken into account that adherence to the training program is adequate. Collectively, well-designed, randomized studies are necessary to collaborate with the present findings.
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Computer Engineering, Journal of Electrical and. "Retracted: Improved Blockchain Technology for Performance Optimization Model Design of Sports Clubs." Journal of Electrical and Computer Engineering 2023 (December 20, 2023): 1. http://dx.doi.org/10.1155/2023/9862625.
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Gavrilova, Yulia, Bradley Donohue, and Marina Galante. "Mental Health and Sport Performance Programming in Athletes Who Present Without Pathology: A Case Examination Supporting Optimization." Clinical Case Studies 16, no. 3 (January 24, 2017): 234–53. http://dx.doi.org/10.1177/1534650116689302.
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Athletes are exposed to unique stressors that often negatively impact the way they think, behave, and feel in athletic, academic, and social domains. The Optimum Performance Program in Sports (TOPPS), an adaptation of Family Behavior Therapy, is an innovative approach to optimization science that has demonstrated positive outcomes in student-athletes evidencing substance use disorders. However, this approach has yet to be evaluated in athletes who are interested in optimizing their mental health and sport performance, but have no indication of pathology. We describe the administration of TOPPS in a female student-athlete who presented for intervention with no assessed mental health pathology. Although experimental methodology was uncontrolled, many of the methodological features in this examination were advanced. Treatment integrity was reliably assessed and the athlete demonstrated significant improvements in psychometrically validated measurements of mental health and sport performance from baseline to 5-months post-treatment, including psychiatric domains (somatization, obsessive–compulsive, interpersonal sensitivity, depression, anxiety, phobic anxiety, paranoid ideation, and psychoticism), relationships with teammates, family members, coaches, and peers, and measures of sport performance. Future directions are reported in light of the results.
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Ariyaratne, M. K. A., and R. M. Silva. "Meta-heuristics meet sports: a systematic review from the viewpoint of nature inspired algorithms." International Journal of Computer Science in Sport 21, no. 1 (March 1, 2022): 49–92. http://dx.doi.org/10.2478/ijcss-2022-0003.
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Abstract This review explores the avenues for the application of meta-heuristics in sports. The necessity of sophisticated algorithms to investigate different NP hard problems encountered in sports analytics was established in the recent past. Meta-heuristics have been applied as a promising approach to such problems. We identified team selection, optimal lineups, sports equipment optimization, scheduling and ranking, performance analysis, predictions in sports, and player tracking as seven major categories where meta-heuristics were implemented in research in sports. Some of our findings include (a) genetic algorithm and particle swarm optimization have been extensively used in the literature, (b) meta-heuristics have been widely applied in the sports of cricket and soccer, (c) the limitations and challenges of using meta-heuristics in sports. Through awareness and discussion on implementation of meta-heuristics, sports analytics research can be rich in the future.
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Wen, Yuan. "Optimization design of biomechanical parameters based on advanced mathematical modelling." Molecular & Cellular Biomechanics 21, no. 3 (November 14, 2024): 463. http://dx.doi.org/10.62617/mcb463.
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In recent years the use of biomechanics in athletic training and performance has received a lot of attention, especially in university sports programs. Biomechanics is the study of the mechanical principles that control how biological things move or are constructed. It is critical for understanding the intricate relationships between physical performance, body mechanics, and injury prevention. The objective of this study is to establish how biomechanical variables can be designed and optimized in universities using mathematical modeling. In this study, a novel Emperor Penguin Search-driven Dynamic Feedforward Neural Network (EPSO-DFNN) is proposed to optimize the biomechanical parameters of athletes. Various biomechanical data are utilized from athletes participating in different sports. Biomechanical parameters include muscle activation patterns, joint angles, forces, and movement. The data was preprocessed using Z-score normalization from the obtained data. The Fast Fourier Transform (FFT) using features is extracted from preprocessed data. The proposed method is to identify the optimal configurations for athlete’s movements tailored to their sports and individual biomechanical profiles. The proposed method is the performance of various evaluation metrics such as F1-score (92.76%), precision (91.42%), accuracy (90.02%), and recall (89.69%). The result demonstrated that the proposed method effectively improved the performance in athletic capabilities compared to other traditional algorithms. This study demonstrates how mathematical modeling may be used to optimize biomechanical characteristics, providing insightful information that can be used to improve athletic performance and encourage safer behaviors in athletic settings.
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Anghel, Lucreția, Tudor Vladimir Gurau, Gabriela Gurau, Carmina Liana Mușat, Doina Carina Voinescu, Ilie Onu, Mariana Cordun, Corneliu-Mircea Codreanu, and Daniel Andrei Iordan. "The Role of Biomarkers in Elite Sports." Balneo and PRM Research Journal, Vol.14, no.3 (September 1, 2023): 581. http://dx.doi.org/10.12680/balneo.2023.581.
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Biomarkers have emerged as valuable tools in the realm of elite sports, providing objective measures of athletes' physiological responses and potential for performance optimization. This article review delves into the significance and implications of biomarkers in elite sports, emphasizing their crucial role in supporting athletes' training, recovery, and overall success. The integration of biomarkers offers unprecedented opportunities for evidence-based decisions, personalized strategies, and injury prevention, revolutionizing the landscape of elite sports. Through comprehensive literature review and analysis, this article highlights the tremendous promise of biomarkers in optimizing athletic performance while also addressing the ethical considerations surrounding their implementation. As research continues to advance, biomarkers are poised to reshape the future of elite sports, enhancing performance and paving the way for the next generation of sporting legends.
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Xu, Wei, Wenying Xiong, Zhe Shao, and Yun Li. "Analysis of Effectiveness and Performance Prediction of Sports Flipped Classroom Teaching Based on Neural Networks." Scientific Programming 2021 (July 30, 2021): 1–7. http://dx.doi.org/10.1155/2021/5284457.
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Traditional physical education methods are unable to meet this requirement due to the practical nature of sports skill teaching. As a result, as the times demanded, the flipped classroom based on neural network technology arose. It has the potential to not only promote the modernization of physical education but also to ensure that it has a positive educational impact. This is a mode of instruction. Furthermore, colleges and universities are increasingly focusing on college students’ overall quality development. A method for predicting college students’ sports performance using a particle swarm optimization neural network is proposed to accurately predict sports performance and provide a reliable analysis basis for the establishment of sports teaching goals. Neural networks are used in the model. The particle swarm optimization algorithm optimizes the variance and weights of the neural network to improve the accuracy of college students’ sports performance predicted by the neural network by updating the particle position and speed through the two extreme values of individual extreme values and global extreme values. Teachers always play the role of the facilitator and helper in the teaching process, which realizes the transformation of teachers’ and students’ self-positioning, allows students to better play the lead role, and stimulates students’ interest in learning.
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Haolin Ma. "Video Analysis of Physical Education Teaching and Design of Intelligent Assistant Teaching System: Based on Motion Recognition and Optimization Algorithm." Journal of Electrical Systems 20, no. 6s (April 29, 2024): 85–95. http://dx.doi.org/10.52783/jes.2618.
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Nowadays, science and technology has rapidly increasing due to the specific requirements of education. The main aim of this technique is to enhance the physical education activities and helps sports man to finest teaching facilities of these activities. Moreover, the body changes with sports activities based on Deep Learning (DL) frameworks and classifier technology are examined to promote the practical application. Therefore, this paper Deep Reinforcement Learning based Chimp optimization (DRLbCO) algorithm was developed to improve the teaching efficiency of physical education system through the intelligent computer aided assessment models. Also, this model improving the performance, enhancing coaching effectiveness, and gaining competitive advantages in sports. Consequently, the proposed system is based on DL based image detection model DRL, which can analyse and provides proper actions in teaching students and enhance the ability of motion analysis in sports video training quality. Moreover, the DL model is integrated with optimization algorithm to optimize the performance. This could involve reinforcement learning, and other classifiers such as Support Vector Machine (SVM). Based on this provides feedback to students and teachers during physical education classes. The developed model is significantly enhances the physical education teaching student action in virtual sports instruction. Overall intention of the video assessment system of the sports training performance in analyzed.
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Zhang, Shoudong, and Huaqing Mao. "Optimization Analysis of Tennis Players’ Physical Fitness Index Based on Data Mining and Mobile Computing." Wireless Communications and Mobile Computing 2021 (June 1, 2021): 1–11. http://dx.doi.org/10.1155/2021/9838477.
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Tennis is a very explosive, continuous, and intense sport, including many continuous short-term explosive actions. It has the characteristics of short-term, high-intensity, high-density training, and it belongs to the category of purely competitive skills. In the competition, athletes must maintain good physical condition, physical fitness, and long-term endurance in order to demonstrate outstanding technical and tactical skills. Therefore, this paper proposes a mobile processor performance data mining framework MobilePerfMiner, which uses hardware counters and iteratively uses the XGBoost algorithm to build a performance model, ranks the importance of the microarchitecture events of the big data task, and reduces the performance big data dimension, so as to optimize the big data algorithm according to the performance characteristics described. Undoubtedly, the comprehensive monitoring of the sports training process is complex system engineering. The main monitoring includes three aspects: physical condition, technical and tactical skills, and intelligence. Sports technology is reflected in the ultimate load. According to the convenience and actual needs of the research, this article will discuss the methods of evaluating tennis training load and the actual technical and tactical parameter characteristics that can be obtained by studying the characteristics of tennis, namely, kinematics. Parameters for noncontact testing, the next step is to discuss the appropriateness and necessity of the load, as well as the technical and routine monitoring of tennis training ability. The final experimental results show that it can improve the physical energy of tennis players by more than 17%.
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Sell, Timothy C., Robert H. Lutz, and Mallory S. Faherty. "The Warrior Model for Human Performance Optimization." Sports Medicine and Arthroscopy Review 27, no. 3 (September 2019): 99–106. http://dx.doi.org/10.1097/jsa.0000000000000248.
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González Parra, Gilberto C. "Optimization of swimming performance in triathlon." Journal of Human Sport and Exercise 4, no. 1 (2009): 69–71. http://dx.doi.org/10.4100/jhse.2009.41.08.
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Li, Bo, and Huaiguo Jing. "Synergizing Material Chemistry and Biomechanics for Enhanced Sports Equipment: Optimization of Carbon Nanotubes/Mg Nanocomposites." Science of Advanced Materials 15, no. 11 (November 1, 2023): 1454–61. http://dx.doi.org/10.1166/sam.2023.4583.
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The production of sports equipment necessitates a delicate balance between comfort, performance, and safety. Achieving this equilibrium depends on a profound understanding of material chemistry and the biomechanical considerations that come into play as athletes push their bodies to the limits. In recent years, composite materials have gained substantial attention for their impressive mechanical and physical properties. Among these, carbon nanotube (CNT) reinforced magnesium matrix composites (MMCs) have emerged as promising contenders. These materials are synthesized using powder metallurgy and hot extrusion techniques, capitalizing on CNTs’ unique properties to enhance the mechanical characteristics of magnesium-based materials. This study delves into the parametric optimization of CNT-reinforced MMCs, particularly focusing on microstructure design. Leveraging a homogenization-based optimization system, we investigate both material properties and shape optimization. Finite element numerical simulations validate our predictions, showcasing significant improvements in various parameters, most notably alterations in fiber layup angles, which contribute to enhanced performance characteristics. This approach serves as an invaluable tool for streamlining composite structure design while simultaneously reducing the costs associated with traditional experimental methods. By harnessing the potential of CNT-reinforced MMCs and optimization techniques, this research advances sports equipment design, ultimately ensuring athletes’ safety and the optimization of their performance.
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Xiao, Yuchun, Zhuo Bi, and Zhibin Chen. "Tech Optimization in Cybersecurity Defenses by Advanced ML Methods: The Use Case of Volleyball Industry." Computational Intelligence and Neuroscience 2022 (May 17, 2022): 1–7. http://dx.doi.org/10.1155/2022/9907427.
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Individual and team performance can be improved by utilizing “smart” devices and applications that are connected through networks. In sports, the Internet of Things (IoT) refers to all of the “smart” devices and applications linked through networks to reduce injuries to the bare minimum, develop advanced training techniques, and apply analytical advanced sports improvement methodologies to improve sports performance in general. The Internet of Things (IoT) in sports is closely related to the objective of both security and privacy in sports, which has become a topic of crucial concern for the sports business in recent years, as evidenced by the adoption of IoT in sports years. For this reason, security flaws can have catastrophic consequences, including the disclosure of personal data, the manipulation of statistical findings, the harming of organizations’ reputations, and enormous financial losses for the sporting organization. One or more of the consequences, as previously mentioned, is related to sports organizations and the athletes who are members of those organizations, and they have a direct impact on the corresponding set of sports-related, medical-related, and paramedical enterprises, specifically those that provide specialized sports equipment and associated services. A critical need to detect and quantify threats has long been recognized to better support decision-making when adopting or constructing a safe and reliable sports Internet-of-Things infrastructure, which is becoming increasingly common. Using advanced machine learning algorithms, this research provides a methodology for technology optimization in cybersecurity defenses that is then used in a unique case study utilizing volleyball players to demonstrate its effectiveness. In conjunction with a Monte Carlo optimization technique, an upgraded variant of fuzzy cognitive maps (FCM) is presented in greater detail. This model is utilized for a specific scenario of risk identification of volleyball industry, assessment, and optimization for IoT sports networks.
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Zuo, Ning-Ning, Jing-Guang Qian, and Qiang Ye. "A Finite Element Modeling for Performance Optimization in Elite Trampoline." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 6446–50. http://dx.doi.org/10.1166/jctn.2016.5584.
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This paper built dynamic analysis on performance optimization and simulation in sports trampoline. The validity of this method is satisfied by comparing between the actual and the simulated loading experiment. The elite gymnasts take advantage of maximizing the elastic energy of the trampoline bed with simulation analysis, which is a non-invasive method for individual optimal performance in training. Using this method, exploiting the elastic force from the trampoline bed during leg flexion and extension is available.
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Rasmussen, J., L. J. Holmberg, K. Sørensen, M. Kwan, M. S. Andersen, and M. de Zee. "Performance optimization by musculoskeletal simulation." Movement & Sport Sciences 75, no. 1 (2012): 73. http://dx.doi.org/10.3917/sm.075.0073.
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Seçkin, Ahmet Çağdaş, Bahar Ateş, and Mine Seçkin. "Review on Wearable Technology in Sports: Concepts, Challenges and Opportunities." Applied Sciences 13, no. 18 (September 17, 2023): 10399. http://dx.doi.org/10.3390/app131810399.
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Wearable technology is increasingly vital for improving sports performance through real-time data analysis and tracking. Both professional and amateur athletes rely on wearable sensors to enhance training efficiency and competition outcomes. However, further research is needed to fully understand and optimize their potential in sports. This comprehensive review explores the measurement and monitoring of athletic performance, injury prevention, rehabilitation, and overall performance optimization using body wearable sensors. By analyzing wearables’ structure, research articles across various sports, and commercial sensors, the review provides a thorough analysis of wearable sensors in sports. Its findings benefit athletes, coaches, healthcare professionals, conditioners, managers, and researchers, offering a detailed summary of wearable technology in sports. The review is expected to contribute to future advancements in wearable sensors and biometric data analysis, ultimately improving sports performance. Limitations such as privacy concerns, accuracy issues, and costs are acknowledged, stressing the need for legal regulations, ethical principles, and technical measures for safe and fair use. The importance of personalized devices and further research on athlete comfort and performance impact is emphasized. The emergence of wearable imaging devices holds promise for sports rehabilitation and performance monitoring, enabling enhanced athlete health, recovery, and performance in the sports industry.
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Li, Min, and Jianwei Zhong. "Elements and Overall Optimization of University Self-Organizing Physical Education Teaching System Based on Holistic Theory." Scientific Programming 2022 (February 3, 2022): 1–9. http://dx.doi.org/10.1155/2022/9410347.
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The fact that self-organized physical education teaching systems in universities should have diversity and imbalance has been weakened, and we need to focus on the self-thinking, self-learning, and uncertain factors in the teaching process. The components of the entire teaching system are known as teaching elements. We cannot understand the integrity of teaching elements without understanding system theory. The teaching in physical education classes is the same way. This paper analyzes the elements and overall optimization of university self-organizing physical education teaching system using the methods of literature review and logical argumentation, starting from the perspective of holism and combining with the characteristics of physical education. The effectiveness and superiority of this model are tested by comparing sports performance data with ACOA (Ant Colony Optimization Algorithm) to optimize the sports video of SVM (Support Vector Machine). The findings show that the model can improve sports performance prediction accuracy, and the prediction results are more reliable, providing useful information for sports training.
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Cong, Rui, and Hailong Wang. "Prediction of Evolution and Development Trend in Sports Industry Cluster Based on Particle Swarm Optimization." Scientific Programming 2021 (December 26, 2021): 1–8. http://dx.doi.org/10.1155/2021/7607623.
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Sports industry cluster refers to the economic phenomenon that sports related enterprises gather in a large number in a specific area. For the sports enterprises in the cluster, they can obtain huge competitive advantages through enterprise agglomeration, thus obtaining better development and rich economic benefits. The optimization of particle swarm optimization is interlinked with the agglomeration of industrial clusters. Therefore, in view of the limitation of the standard particle swarm optimization (PSO) algorithm, an improved particle swarm optimization algorithm-diaphragm particle swarm optimization (D-PSO) was proposed and used to simulate the formation of sports industry clusters. D-PSO introduces the cell membrane processing mechanism of the biological system into the PSO algorithm, which improves the ability of the PSO algorithm to get rid of local extremum points. The competitiveness value of the sports industry cluster is the value of the objective function solved by the D-PSO algorithm. The geographical coordinates of the industrial cluster were the locations in the particle search space of the D-PSO algorithm. The D-PSO algorithm is used to simulate the aggregation process of enterprises in the cluster. Compared with the standard PSO, the D-PSO algorithm has better convergence performance and optimal rate. The results of case analysis show that the proposed method can effectively predict the development trend of sports industrial clusters.
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Olha, Borysova, Shutova Svitlana, Nagorna Viktoriia, Shlonska Olha, Serebriakov Oleh, and Mytko Artur. "CHARACTERISTICS OF COMPETITIVE ACTIVITY OF UKRAINIAN NATIONAL TEAMS IN SPORTS GAMES IN THE INTERNATIONAL AREA." Sport Science and Human Health 4, no. 2 (2020): 27–37. http://dx.doi.org/10.28925/2664-2069.2020.2.3.
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Introduction. At the present development stage of the high achievement sport, global transformations are taking place all over the world, which have influenced the intensification of competitive practices and the introduction of innovative technologies in the process of training elite athletes. Unfortunately, both external factors and internal political and economic problems in Ukraine become a serious obstacle to the effective competitive activity of national teams at major international sports competitions, namely: the socio-economic situation in the country calls into question the ability to prepare quality reserve, children's and youth sports suffer as a result of the financial and economic crisis; Insufficient level of logistics and the possibility of migration of the best players and coaches abroad, negatively affects the level of performance of the national team in the international arena. The planning of preparation of highly qualified athletes for the main international competitions should take into account the peculiarities of tournament loads in team and individual sports. Why is it necessary to determine the main factors influencing the quality and effectiveness of the performances of the best athletes and teams in sports games. Aim of our research is to analyze the effectiveness of competitive activities of highly qualified athletes in sports games. Material and methods: analysis of planning and competition documents and generalization of special literature, method of expert assessments, pedagogical observation, pedagogical experiment, psychophysiological methods, methods of mathematical statistics. Conclusions: the implementation of effective performance of athletes of Ukrainian national teams in sports on the international arena requires optimization of the process of sports training based on individualization with the parallel use of technical-tactical, psychophysiological models of training of leading players in the world combined with modern capabilities.
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Mateus, Nuno, Eduardo Abade, Diogo Coutinho, Miguel-Ángel Gómez, Carlos Lago Peñas, and Jaime Sampaio. "Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management." Sensors 25, no. 1 (December 29, 2024): 139. https://doi.org/10.3390/s25010139.
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Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, particularly in team sports environments, by improving training load management, sports performance, and player well-being. It explores key dimensions such as load optimization, injury prevention and return-to-play, sports performance, talent identification and scouting, off-training behavior, sleep quality, and menstrual cycle management. Practical examples illustrate how AI applications have significantly advanced each area and how they support and enhance the effectiveness of sports scientists. This manuscript also underscores the importance of ensuring that AI technologies are context-specific and communicated transparently. Additionally, it calls for academic institutions to update their curriculums with AI-focused education, preparing future sports professionals to fully harness its potential. Finally, the manuscript addresses future challenges, such as the unpredictable nature of team sports, emphasizing the need for interdisciplinary collaboration, including clear communication and mutual understanding between sports scientists and AI experts, and the critical balance between AI-driven insights and human expertise.
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孙, 武. "Exploring the Development Dilemma and Optimization Path of China’s Sports Competition Performance Industry." Advances in Physical Sciences 10, no. 02 (2022): 158–63. http://dx.doi.org/10.12677/aps.2022.102023.
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Singh, Dr Y. Wise Bless, and MA Aleem. "Enhancing sports training: The synergy of AI and VR in athletic performance optimization." International Journal of Physiology, Nutrition and Physical Education 9, no. 1 (January 1, 2024): 174–77. http://dx.doi.org/10.22271/journalofsport.2024.v9.i1c.2914.
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Xu, Yixiong, and Peng Jia. "Analysis and Application of Gymnastics Sports Characteristics Based on Artificial Neural Network and Intelligent Optimization." Wireless Communications and Mobile Computing 2022 (July 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/2121370.
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Gymnastics has attracted people’s attention in various competitions by virtue of its beautiful movements and difficult technical performances. The research and exploration of neural network theory are to make the process from receiving instructions to completing actions in one go while sending instructions. Compared with the previous competitive gymnastics, it mainly relies on personal understanding and coach’s guidance to get high-scoring movements. Through intelligent calculation, it can decompose and calculate each movement in detail and adjust its strength, so as to further improve its excellent characteristics. We combined artificial neural network and intelligent optimization method to achieve more scientific and reasonable guidance for gymnastics, so that people can get better performance in performance and competition. The experimental summary of this paper is as follows: (1) Under the analysis of sample data 5000, it shows that the right segmentation curve is superior to the left segmentation curve and is relatively stable. (2) The BP neural network is obviously higher than the other two algorithms in the experimental test under different dimensions, and the qualified dimension value is controlled within the standard range. (3) In the experimental diagram of mean square error, the ideal error value is about 0.005, and it is possible to reach this target value only under the condition of perfect performance. (4) Convergence function is to explore the gracefulness of action analysis, and the convergence of its artificial peak group greatly shows the performance of global exploration.
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Toselli, Stefania. "Body Composition and Physical Health in Sports Practice: An Editorial." International Journal of Environmental Research and Public Health 18, no. 9 (April 24, 2021): 4534. http://dx.doi.org/10.3390/ijerph18094534.
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The assessment of the health status of athletes, at all ages, is an aspect of fundamental importance, and, in recent years, the analysis of body composition has become a fundamental and essential part in its evaluation, such as in the optimization of sports performance [...]
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Zhang, Xiang, Gongbing Shan, Ye Wang, Bingjun Wan, and Hua Li. "Wearables, Biomechanical Feedback, and Human Motor-Skills’ Learning & Optimization." Applied Sciences 9, no. 2 (January 10, 2019): 226. http://dx.doi.org/10.3390/app9020226.
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Biomechanical feedback is a relevant key to improving sports and arts performance. Yet, the bibliometric keyword analysis on Web of Science publications reveals that, when comparing to other biofeedback applications, the real-time biomechanical feedback application lags far behind in sports and arts practice. While real-time physiological and biochemical biofeedback have seen routine applications, the use of real-time biomechanical feedback in motor learning and training is still rare. On that account, the paper aims to extract the specific research areas, such as three-dimensional (3D) motion capture, anthropometry, biomechanical modeling, sensing technology, and artificial intelligent (AI)/deep learning, which could contribute to the development of the real-time biomechanical feedback system. The review summarizes the past and current state of biomechanical feedback studies in sports and arts performance; and, by integrating the results of the studies with the contemporary wearable technology, proposes a two-chain body model monitoring using six IMUs (inertial measurement unit) with deep learning technology. The framework can serve as a basis for a breakthrough in the development. The review indicates that the vital step in the development is to establish a massive data, which could be obtained by using the synchronized measurement of 3D motion capture and IMUs, and that should cover diverse sports and arts skills. As such, wearables powered by deep learning models trained by the massive and diverse datasets can supply a feasible, reliable, and practical biomechanical feedback for athletic and artistic training.
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Exel, Juliana, and Peter Dabnichki. "Precision Sports Science: What Is Next for Data Analytics for Athlete Performance and Well-Being Optimization?" Applied Sciences 14, no. 8 (April 16, 2024): 3361. http://dx.doi.org/10.3390/app14083361.
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In elite sports, athletic excellence demands meticulous performance preparation and a sound health status. This paper overviews the current propositions and applications of pervasive computing and data analytics and our vision on how they should be used in future frameworks to contribute to the optimal balance of athletes’ performance and health requirements. Two main areas will be discussed. The first area is Sports Performance Optimization, in which we consider interesting recent advancements in data analytics for performance improvement, equipment design, and team member recruitment and selection. We will also briefly discuss how the betting industry has been relaying and developing sports analytics. The second area is Athlete’s Wellness and Wellbeing, which will discuss how wearables and data analytics have been used to assess physical activity and sedentary behavior profiles, sleep and circadian rhythm, nutrition and eating behavior, menstrual cycles, and training/performance readiness. In the final part of this paper, we argue that a critical issue for managers to enhance their decision making is the standardization of acquired information and decision-making processes, while introducing an adaptable, personalized approach. Thus, we present and discuss new theoretical and practical approaches that could potentially address this problem and identify precision medicine as a recommended methodology. This conceptualization involves the integration of pervasive computing and data analytics by employing predictive models that are constantly updated with the outcomes from monitoring tools and athletes’ feedback interventions. This framework has the potential to revolutionize how athletes’ performance and well-being are monitored, assessed, and optimized, contributing to a new era of precision in sports science and medicine.