Application of digital entertainment experience based on intelligent interactive system in personalized fitness training system

Abstract

The application of digital media in fitness environments can improve the entertainment of the fitness process, allowing users to watch entertainment videos while engaging in fitness activities. At the same time, we can add relevant game elements to the fitness process, such as playing tennis through gesture movements, thereby increasing user interest in fitness participation. Therefore, this article has developed a personalized fitness training system using optical sensors and intelligent algorithms, and conducted testing experiments on blood oxygen saturation under two sports states: running and cycling. This article analyzes the intelligent optimization algorithm for optical signals. This algorithm has strong adaptability and intelligence level, and can directly learn and adjust the model based on the characteristics of the data. The automation performance of the intelligent algorithm can effectively reduce labor costs and improve efficiency. Finally, this article provides a basic analysis and testing of the personalized fitness training system. Through the obtained data, personalized guidance is provided to users, helping people make fitness more scientific and intelligent, and improving fitness efficiency.