KMAN Publication Inc. International Journal of Sport Studies for Health 2588-5782 9 Serial Number 24 2026 01 01 An Interactive Real-Time System for Pose Classification in Children’s Yoga and Kavayat Exercises An Interactive Real-Time System for Pose Classification in Children’s Yoga and Kavayat Exercises 1 9 10.61838/kman.intjssh.4381 EN Journal Article 2025 08 20 <p><strong>Objective:</strong> Vision-based motion identification and categorization of human movement through machine learning is a crucial aspect of various applications, including healthcare, surveillance, and sports analysis.</p> <p><strong>Methods:</strong> Through the analysis of movement data, the system differentiates between diverse actions with high precision,  offering valuable insights for monitoring and analysis in real-time.</p> <p><strong>Results:</strong> This investigation demonstrates yoga and Kavayat (abbreviated as YK) that leverages machine learning techniques,  specifically  Logistic  Regression,  to precisely discern and categorize physical action patterns and classify with real-time feedback and inform the accuracy of the posture. For children, Yoga and Kavayat, sometimes called mock drill, improve the physical as well as mental health.</p> <p><strong>Conclusion:</strong> The lightweight model called  PoseHeatMapachieves a remarkable 98.00%  accuracy,  demonstrating its capability to effectively detect and classify patterns of physical action and give real-time feedback.</p> https://journals.kmanpub.com/index.php/Intjssh/article/download/4381/8697