IoT muscle monitoring device based on thermal infrared image monitoring in sports training: real-time analysis of exercise heat consumption

Traditional sports monitoring methods often rely on the subjective feelings of athletes, lacking real-time and accuracy. This study explores the application of IoT muscle monitoring devices based on thermal infrared image monitoring in sports training, enhancing athletic performance and safety through real-time analysis of heat expenditure during exercise. The paper reviews research advancements in this field, particularly the current status of IoT technology and deep learning algorithms in sports monitoring. It introduces the theoretical foundation of thermal infrared image monitoring, emphasizing its advantages in capturing changes in muscle heat expenditure during movement. Through simulation experiments, the designed sports monitoring system was tested to verify its feasibility. The designed sports monitoring system includes a data acquisition module, processing unit, and user interface. In terms of algorithm design, deep learning technology is used to process and analyze thermal infrared images, achieving precise monitoring of heat expenditure during exercise. Experimental results show that the system can capture real-time thermal changes during exercise and provide relevant data support, assisting athletes and coaches in scientific training. Studies indicate that IoT muscle monitoring devices based on thermal infrared images have excellent real-time analysis capabilities, providing reliable technical support for sports training.