АЛГОРИТМ ФОРМУВАННЯ ЦІЛЬОВИХ КОРЕКЦІЙНО-ПРОФІЛАКТИЧНИХ ПРОГРАМ: ВІД БІОМЕХАНІЧНОЇ ДІАГНОСТИКИ ДО ІНДИВІДУАЛІЗОВАНОЇ КІНЕЗІОЛОГІЧНОЇ КОРЕКЦІЇ

Abstract. Relevance. Despite a substantial body of research dedicated to specific kinesiological techniques, the issue of systemic algorithmization remains largely unaddressed. Currently, a significant methodological gap exists regarding the mechanisms for transforming objective biomechanical diagnostic data into targeted corrective strategies. The absence of a holistic algorithm that integrates instrumental screening as an imperative prerequisite for developing an individualized plan diminishes the potential of modern technologies and reduces the predictive efficacy of health-improving interventions. The aim of the study is to provide a theoretical and methodological substantiation and to develop a comprehensive algorithm for designing corrective and preventive programs. These programs ensure a high degree of individualization in health-related measures based on the integration of biomechanical diagnostic data and individualized kinesiological modeling methods to optimize the motor function of subjects. Methods. Theoretical analysis and generalization of scientific literature, postural photography and analysis, methods of mathematical statistics. Results. A holistic algorithm for developing individualized corrective and preventive programs has been theoretically substantiated, integrating biomechanical control and digital data analysis models. The algorithm is implemented in four stages: 1. Instrumental screening (utilizing markerless motion capture systems and IMU sensors for objective assessment of motor characteristics). 2. Kinesiological modeling (forming a "digital profile" of the musculoskeletal system, prioritizing intervention zones, and forecasting changes within kinematic chains). 3. Program design (differentiated selection of modalities based on the generated model). 4. Dynamic monitoring (adaptive adjustment of loads based on follow-up measurement results). It has been demonstrated that the integration of machine learning algorithms with biomechanical modeling facilitates the transition from episodic diagnostics to precision correction of motor dysfunctions within the physical education and sports system. Conclusions. A comprehensive algorithm has been developed based on a closed-loop "diagnostics – modeling – correction" cycle. In this framework, the selection of kinesiological modalities is determined by an individual profile of biomechanical deficits rather than a nosological form. This approach minimizes the risk of injury and enhances the ergonomic efficiency of motor activity.