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Health Promotion Effects of Sports Training Based on HMM Theory and Big Data
Summary
Researchers developed a human health status evaluation model for post-exercise states by combining Hidden Markov Model (HMM) theory with big data analytics to collect and analyze physiological parameters during and after sports training. The system demonstrated the ability to assess health status and guide exercise recommendations with improved prediction accuracy.
In order to better analyze human health status and guide people to carry out reasonable physical training, this paper puts forward the construction method of human health status evaluation model after sports training based on big data. Firstly, the characteristic information of human health status after sports training is collected based on big data technology, and the evaluation index and evaluation algorithm of human health status after sports training are constructed. The evaluation system of human health status after sports training is constructed. Finally, the experiment proves that the proposed evaluation model of human health status after sports training based on big data has high practicability in the process of practical application and fully meets the research requirements.