An Intelligent Monitoring System for Sports Mental Health Status based on Big Data

Abstract

This provides an effective way to break away from traditional inefficient evaluation methods for monitoring and analyzing the psychological status of a large number of school sports athletes, the author proposes an intelligent monitoring system for sports psychological health status based on big data. Applying big data technology to mental health assessment, using real-time monitoring and analysis of athlete unified EEG waves, dividing athlete EEG waves into frequency bands, and conducting mental health analysis. The author validated the effectiveness of the system through simulation experiments, and the results showed that the psychological states of the subjects were not the same during the early and fatigue stages of training. In the early stages of training, the brainwave frequency band was mainly in the Beta and Gamma bands, accounting for 37% and 41%, respectively. Concentration was greater than relaxation, while in the fatigue stage of homework, the brainwave frequency band was mainly in the Delta and Thata bands, accounting for 43% and 45%, respectively, and concentration was less than relaxation. The psychological monitoring system designed by the author can provide a technical foundation for a series of strategies to promote training efficiency while ensuring the mental health of athletes.