Dynamic Monitoring and Evaluation System of Modern Leisure and Fitness Behavior Based on Multimodal Data

This study aims to develop a modern leisure fitness behavior dynamic tracking and performance evaluation system based on multimodal data, enhance the accuracy of sports activity monitoring and real-time data collection capabilities, provide scientific support for customized fitness plans, use a variety of sensors to implement data collection operations, use wireless communication technology to achieve real-time data transmission, and use multimodal data fusion strategies to process and analyze the collected information. Research data shows that the system has the ability to accurately identify various types of sports behaviors, and calculates and outputs sports intensity and calorie consumption data in real time based on indicators such as heart rate changes, cadence, and acceleration. The recognition technology achieves a perfect combination of high recognition accuracy and low error rate. The system shows its excellent real-time data response performance and stable operation status.