Big data medical behavior analysis based on machine learning and wireless sensors

To improve the scientificity and reliability of medical behavior analysis, this paper combines machine learning and wireless sensor technology to construct an intelligent data mining system that can be used for medical behavior analysis and uses association rules to analyze and mine the implicit relationships between structural monitoring parameters. Moreover, this paper establishes strong association rules between different monitoring variables based on historical monitoring data under normal structural conditions to predict whether the structural conditions are normal. In addition, this paper constructs a system function module according to actual needs, obtains the overall system architecture, and implements the system function module in combination with algorithms. Finally, this paper designs experiments to verify the performance of the system constructed in this paper and discusses the experimental results through mathematical graph analysis methods. From the research point of view, it can be observed that the system constructed in this paper has a specific effect.