Research on Load Monitoring and Regulation of Human Movement Training Assisted by Intelligent Algorithms

A unique sports-based heavy load state monitoring approach is intended to understand human exercise monitoring and management science with intelligence algorithms. Wireless sensor network nodes are used to collect the state of unlimited sports, and use the joint information to achieve the integration and coordination. The detection and analysis of the characteristics of the model of the sports heavy load state abnormal characteristics is designed together with the ZigBee IoT network and RF address recognition method, which can be achieved spectral characteristic analysis and observation of non-competitive characteristics in the state in real-time sports conditions. Based on the results, sports performance can be monitored in time and health can be determined. The results show that the sports load monitoring system has high accuracy in monitoring the sports load and can avoid the sports load due to excessive exercise.