Graph-structured simulation of infrared thermal imaging for load assessment in sports motion analysis

In terms of training load evaluation of athletes, traditional evaluation methods often rely on physiological indicators and subjective feelings, and it is difficult to fully reflect the true state of athletes. This paper explores the application of infrared thermal energy image based on optical sensing in the evaluation of exercise training load, and studies the construction of an effective exercise thermal energy control model to improve the training effect and safety of athletes. Then, aiming at human motion monitoring, the mathematical model of motion information is established, and the monitoring accuracy is analyzed. The research shows that the infrared thermal energy image can accurately reflect the change of muscle temperature during exercise, and can reflect the load state of athletes more timely than the traditional monitoring method. Multi-sensor information fusion technology significantly improves the evaluation accuracy of motion load intensity, and verifies the feasibility of the model in practical application.