AI Yoga Pose Detection and Feedback System

Zen Pose is an Al-driven yoga training system designed to enhance posture detection, track practice sessions, and provide real-time feedback for users. Utilizing React for the frontend and TensorFlow for machine learning-based pose estimation, the system ensures accurate yoga posture recognition. The backend, powered by Python, manages user data and analytics while integrating a database for personalized training insights. Key features of Zen Pose include Al-powered pose detection, time tracking for each yoga posture, and an analytics dashboard that visualizes training frequency and progress. The system offers a seamless user experience with interactive feedback, helping practitioners refine their postures. Additionally, it integrates a calming music feature to enhance focus and relaxation during sessions. The platform aims to make yoga training more accessible by providing users with structured feedback on their form, helping them improve flexibility and alignment. Future developments include incorporating IoT-based wearables for deeper performance analysis and expanding Al models for personalized training recommendations. Zen Pose represents a modern approach to digital fitness, blending Al and real-time analytics for an immersive and effective yoga experience.

Keywords: Yoga Pose Detection, Al-Powered Training, TensorFlow, React, Python, Machine Learning, Real-Time Feedback, Analytics Dashboard, Personalized Training, Fitness Technology.

Prema. M, Devadharshini. C. J, Bindhu Shree. K, Agilandeshwari. V, Kalaivani. V (2026). AI Yoga Pose Detection and Feedback System. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).