Yoga Pose Detection and Correction Application using AI & ML

Q: How many days will it take for my paper to be published?

The review time for papers is not fixed. However, if the paper is accepted and the author completes the processing charges formalities, the paper will be published within a few working days.

Q: I would like to receive a hard copy of the journal materials. Are there any additional charges?

You can log in to the author portal and pay 500 INR to receive the hard copy materials.

Srushti Shridhar Joshi; Arati Uttam Kumbhar; Bhakti Appayya Swami; Samrudhi Rajaram Sutar; Pravin Kumar Karve

Yoga Pose Detection and Correction Application using AI & ML

Authors: Srushti Shridhar Joshi, Arati Uttam Kumbhar, Bhakti Appayya Swami, Samrudhi Rajaram Sutar, Pravin Kumar Karve

Unique Paper ID: 168374
Volume: 11
Issue: 5
PageNo: 651-658

Keywords: Artificial intelligence deep learning machine learning techniques pose estimation techniques skeleton and yoga

Abstract:
Yoga is a traditional Indian way of keeping the mind and body fit, through physical postures (asanas), voluntarily regulated breathing (pranayama), meditation, and relaxation techniques. The recent pandemic has seen a huge surge in numbers of yoga practitioners, many practicing without proper guidance.This paper presents a novel application for yoga pose detection and correction leveraging artificial intelligence (AI) and machine learning (ML) techniques. As the popularity of yoga grows, the need for effective instructional tools to ensure correct postures has become paramount. Our application employs computer vision algorithms to analyze users’ body positions in real-time, providing instant feedback on alignment and pose accuracy. By utilizing deep learning models trained on a diverse dataset of yoga poses, the system identifies key landmarks and assesses deviations from optimal alignment. We implement a user-friendly interface that offers personalized corrections and suggests modifications to enhance practice. The effectiveness of the application is evaluated through user studies, demonstrating significant improvements in pose accuracy and user engagement. This work contributes to the intersection of technology and wellness, promoting safe and effective yoga practices through innovative AI solutions. Future research directions include expanding the dataset for enhanced model robustness and integrating additional wellness metrics for a holistic user experience.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 5
PageNo: 651-658

Yoga Pose Detection and Correction Application using AI & ML

Available:https://ijirt.org/article?manuscript=168374

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now