Personalized Sports Training Strategy Optimization Method Based on Multi-Task Deep Deterministic Policy Gradient

With the continuous development of big data technology, its application in the field of sports health management is becoming more and more in-depth. Compared with traditional methods, big data has the advantages of large capacity, multiple types, fast processing and high precision, providing new technical support for the precision of health management. In the past, our methods of collecting and analyzing health data have been difficult to meet the current needs of people for personalized and intelligent services. Although traditional methods can process health data to a certain extent, they often seem to be unable to cope with large-scale data processing, real-time monitoring and the generation of personalized suggestions. With the help of big data technology, we can now realize the real-time collection, processing and analysis of large-scale health data, bringing new ideas and methods to improve the health level of the whole people. However, there are still many problems in the current sports health management system, especially in scientific guidance and personalized strategies. Many people lack accurate guidance when exercising, which not only affects the effect of exercise, but also may increase the risk of injury. In response to these problems, we proposed a set of intelligent sports health management system based on big data. The system integrates sensor networks, Internet of Things devices and cloud computing platforms, and can automatically complete the collection, collation, storage and dynamic analysis of health data. At the same time, it can accurately monitor personal health status and provide personalized exercise suggestions based on the analysis results. Compared with traditional methods, this system has obvious advantages in providing personalized guidance and preventing sports injuries. It can effectively make up for the shortcomings of existing methods and bring people more scientific and efficient health management solutions.

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Publication Details

Published
2025-03-14
DOI
https://doi.org/10.1145/3736426.3736501
Primary Topic
E-commerce and Technology Innovations
Type
article
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article

Personalized Sports Training Strategy Optimization Method Based on Multi-Task Deep Deterministic Policy Gradient

Yu Zhang, Rongxiu Chen
E-commerce and Technology Innovations
article

Personalized Sports Training Strategy Optimization Method Based on Multi-Task Deep Deterministic Policy Gradient

Yu Zhang, Rongxiu Chen
article en

Abstract

With the continuous development of big data technology, its application in the field of sports health management is becoming more and more in-depth. Compared with traditional methods, big data has the advantages of large capacity, multiple types, fast processing and high precision, providing new technical support for the precision of health management. In the past, our methods of collecting and analyzing health data have been difficult to meet the current needs of people for personalized and intelligent services. Although traditional methods can process health data to a certain extent, they often seem to be unable to cope with large-scale data processing, real-time monitoring and the generation of personalized suggestions. With the help of big data technology, we can now realize the real-time collection, processing and analysis of large-scale health data, bringing new ideas and methods to improve the health level of the whole people. However, there are still many problems in the current sports health management system, especially in scientific guidance and personalized strategies. Many people lack accurate guidance when exercising, which not only affects the effect of exercise, but also may increase the risk of injury. In response to these problems, we proposed a set of intelligent sports health management system based on big data. The system integrates sensor networks, Internet of Things devices and cloud computing platforms, and can automatically complete the collection, collation, storage and dynamic analysis of health data. At the same time, it can accurately monitor personal health status and provide personalized exercise suggestions based on the analysis results. Compared with traditional methods, this system has obvious advantages in providing personalized guidance and preventing sports injuries. It can effectively make up for the shortcomings of existing methods and bring people more scientific and efficient health management solutions.

Tianjin University of Technology (CN)
Openalex Percentile: Top 70%
E-commerce and Technology Innovations
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