Guiding role of infrared thermal radiation images based on sensors in sports training: Application of artificial intelligence

In recent years, infrared thermal radiation image technology based on sensors has provided a new perspective for sports training because of its ability to monitor the temperature distribution of the human body surface noninvascularly. This study discusses how to use sensor-based infrared thermal radiation image technology combined with artificial intelligence algorithm to guide sports training. The thermal radiation images of athletes in different sports are collected by using high-precision infrared thermal imager. The acquired infrared thermal radiation images need to be pre-processed, including denoising, correction and standardization, etc., and the processed images are analyzed by deep learning and machine learning algorithms. Through the training algorithm to identify the patterns and features in the thermal radiation image, the association model between the athlete training state and the thermal image is established. Based on the above analysis results, an intelligent training guidance system is developed. The system can receive infrared thermal radiation image data in real time, and provide training suggestions for coaches after analysis by artificial intelligence algorithm. The results show that the sensor-based infrared thermal radiation image technology combined with artificial intelligence algorithm has significant application value in sports training guidance. The application examples in several sports show that the technology can effectively identify the heat load distribution of athletes, predict the accumulation of fatigue, and provide scientific training adjustment suggestions for coaches.