Using Machine Learning “AI Software” for Real-Time Posture Correction in Yoga

Abstract

This paper explores the application of machine learning (ML) algorithms in real-time posture correction for yoga practitioners and yogachrya. In 21century these tools help in rise of at-home fitness solutions and virtual yoga classes, maintaining correct posture. A yoga teacher can check the yoga poses but can’t be make correction 100 % in the asana but now  ML-powered systems using computer vision such as (Mediapipe, PoseNet, MoveNet, and OpenPose) and sensor-based data analysis help resolve the all issue. This research investigates is totally technological based and aware the society about the new AI technology for the improvement of yoga practice. In yoga competition judges check the alignment and stability of the students and players but now after this technology judgment become quick and accurate. In the results of a study, it’s also proved that accuracy of the Mediapipe architecture has the better accuracy other apps.

Keywords: Yoga, AI Technology, Machine Learning, Sensor, Virtual Yoga