No. 9, pp. 59–61

Published: 25.09.2026

CC BY-SA 4.0

Abstract

Objective of the study is the development and scientific substantiation of the architecture of a personalised sports training system using the technologies of artificial intelligence and computer vision. Methods and structure of the study. The theoretical basis of the work was constituted by the concepts of the digitalisation of sport, systems analysis and the structural-functional approach to the design of the training process. The main method was structural-functional modelling, supplemented by the analysis and synthesis of scientific sources, the design of scenarios of interaction with the ChatGPT (Plus) language model, and the processing of video data by computer vision methods for the extraction of the biomechanical parameters of movements. Results and conclusions. A structural-functional model of the personalised training process was developed, uniting the target, technological, content and result blocks into a closed loop of the management of preparation. The model realises the automatic frame-by-frame analysis of video, the identification of biomechanical errors, and the generation of a report including the visualisation of deviations, comparison with a standard, text recommendations and an adapted training plan for 3-6 weeks. The subsequent expert verification confirmed the pedagogical substantiation and relevance of the recommendations generated by the system.

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