Paper Title
YogAI: An AI Based Yoga Trainer
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Registration ID: IJNRD_214443
Published ID: IJNRD2402342
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Keywords
Android development, Machine Learning, Pose Detection, Text to Speech, Feedback generation, Yoga and Fitness.
Abstract
The project “YogAI” addresses the need for an innovative solution to enhance yoga practice by leveraging real-time pose detection and intelligent feedback generation. In a world increasingly focused on physical and mental well-being, YogAI aims to provide a unique and accessible approach to personalized yoga training through a user-friendly Android application. The specific objectives of YogAI include guiding users through their yoga practice, ensuring correct posture and alignment, tracking progress over time, providing a real time voiced feedback based on user performance hence offering a comprehensive yoga companion experience. To achieve these goals, YogAI utilizes machine learning models for pose detection, allowing users to receive instant feedback on their poses. The app also offers guided workouts and the ability to monitor vital signs for safe and effective yoga sessions. The approach of YogAI involves the integration of machine learning frameworks, Android app development and voiced feedback generation. The results expected include an engaging and effective yoga training tool that caters to users of all skill levels. YogAI will empower users to improve their yoga practice, manage stress, and prioritize their well-being. YogAI represents an innovative fusion of technology and wellness, offering a practical solution for individuals seeking to enhance their yoga experience. This project aims to make yoga accessible, enjoyable, and effective for everyone, promoting physical and mental health in an increasingly hectic world.
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How To Cite (APA)
Jay Kiran Shimpi, Mayur Hiraman Raut, Sanket Suresh Patil, & Arpit Anil Ahire (February-2024). YogAI: An AI Based Yoga Trainer. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(2), d400-d404. https://ijnrd.org/papers/IJNRD2402342.pdf
Issue
Volume 9 Issue 2, February-2024
Pages : d400-d404
Other Publication Details
Paper Reg. ID: IJNRD_214443
Published Paper Id: IJNRD2402342
Research Area: Computer EngineeringÂ
Author Type: Indian Author
Country: Nashik, Nashik, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2402342.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2402342
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