earticle

영어

Purpose: With the development of sports science, some major sports have made significant progress over the past few years by introducing big data analysis technology. Whereas, fitness sports events that are closer to the general public, such as weight training, are slow to use big data analysis techniques to increase the accuracy and precision of exercise methods. This study aimed to review the current big data analysis technology and discuss sports scientific application methods that can be used in the fitness field. Methods: A total of 10 articles related to big data published within the last ten years in sports science and medical fields were reviewed, and key contents were summarized to suggest a future fitness exercise case using big data and sports scientific research methodology. Results: The successful use of big data analysis in the sports field requires core technologies, including data collection ans storage, analysis algorithm accuracy, user experience-based interface, network protocols and security etc. As a result of reviewing all articles, an integrated platform was derived that technically provides a function of coaching and notifying accurate posture in 3D model simulation while capturing trainee's posture and movements in real time during fitness exercise, and in terms of research methodology, it was confirmed that the integrated big data platform needs to be verified through randomized controlled studies on bodybuilding performance, health fitness level, quality of life, and user satisfaction etc. Conclusion: Through the results of this study, it was confirmed that advanced industries and services can be expected by using big data analysis technology in fitness sports in the future, and technical and clinical verification should be actively conducted academically.