Exercise performance monitoring system by Hybrid Intelligence tools: Architecture

Recieved: 01/22/2026

Accepted: 02/10/2026

Keywords: computer vision, human pose estimation, fuzzy logic, hybrid intelligence

Available in the on-line version with: 15.09.2026

To cite this article

Shergin I.A., Ryjov A.P., Novikova N.K., Akhmedzhanov N.M. Exercise performance monitoring system by Hybrid Intelligence tools: Architecture. // Moscow University Journal. Series 15. Computational Mathematics and Cybernetics. 2026. N 3, p.79-86 https://doi.org/10.55959/MSU/0137–0782–15–2026–50–3–79–86.

This work is licensed under a Сreative Commons Atribiution - NonCommercial 4.0 International (CC BY-NC 4.0)

Shergin I.A. (Lomonosov Moscow State University (MSU))
Ryjov A.P. (Lomonosov Moscow State University (MSU))
Novikova N.K. (National Medical Research Center for Therapy and Preventive Medicine)
Akhmedzhanov N.M. (National Medical Research Center for Therapy and Preventive Medicine)

Abstract

Physical education is the foundation of a healthy lifestyle. The effectiveness and correctness of physical exercises can't be ensured without the supervision of an expert. The article proposes a system architecture based on hybrid intelligence, in particular, methods for human pose estimation and fuzzy logical inference, which makes it possible to determine the indicators necessary to evaluate exercise performance and form personal recommendations with adjustments to achieve correct performance.