Application of Embedded System in the Analysis Model of Factors Affecting College Students’ Running Performance

In modern educational environments, the cultivation of physical fitness and the design of embedded system software also require detailed analysis and optimization. In order to comprehensively understand and optimize this system, this paper adopts the method of embedding correlation analysis, which is similar to the in-depth exploration of the interaction between software and hardware in embedded system software design. By constructing an embedded correlation analysis model, this paper analyzes the impact of various factors on running performance, providing a scientific basis for teaching adjustments and training plans. In embedded system software design, this analysis model is also applicable as it can help us identify and optimize the interaction relationship between software and hardware, and improve the overall performance of the system. The research results show that the key factors affecting college students’ running performance include training frequency, psychological stress, and height. This discovery corresponds to the identification and optimization of key performance indicators in embedded system software design. In embedded system design, we also need to focus on and optimize the factors that have the greatest impact on system performance. The results of this study not only provide inspiration for physical education teaching in universities, but also provide a new perspective and tool for researchers in the field of embedded system software design. The effectiveness of embedded-related analysis models has been validated in both fields, demonstrating their practicality and effectiveness in analyzing complex system problems.