This research is dedicated to designing a detailed construction plan for an action recognition and optimization system for gymnasts and making a detailed plan for its subsequent experimental procedures. When the system construction and experiments are still in the preliminary theoretical exploration and preparation stage, through in-depth analysis of aspects such as the establishment of deep learning models, the layout of the interactive interface, and the collaborative architecture of cloud and edge computing, as well as a comprehensive conception of the experimental design. It lays a solid theoretical foundation for the subsequent actual implementation of relevant work, provides a detailed planning blueprint, helps transform this system from a theoretical concept into practical application step by step, and promotes the intelligent transformation in the field of gymnastics training.

Xu Yun, Lu Ruitong, Zhao Zhuo, Chen Xueliang, Zhang Xinyu. Construction Strategies and Experimental Design of the Action Recognition and Optimization System for Gymnasts. International Journal of Frontiers in Engineering Technology (2025), Vol. 7, Issue 3: 27-34. https://doi.org/10.25236/IJFET.2025.070305.

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