![]() Zhang F, Bazarevsky V, Vakunov A, Tkachenka A, Sung G, Chang CL, Grundmann G (2021) MediaPipe hands: on-device real-time hand tracking In: 2017 IEEE region 10 humanitarian technology conference (R10-HTC), Dhaka, pp 668–673 Islam MU, Mahmud H, Ashraf FB, Hossain I, Hasan MK (2017) Yoga posture recognition by detecting human joint points in real time using microsoft Kinect. In: Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), pp 7291–7299 In: 2020 5th international conference on information technology researchĬao Z, Simon T, Wei SE, Sheikh Y (2017) OpenPose: realtime multi-person 2D pose estimation using part affinity fields. Rishan F, Silva BB, Alawathugoda S, Nijabdeen S, Rupasinghe L, Liyanapathirana C (2020) Infinity Yoga Tutor: Yoga posture detection and correction system. In: 2018 2nd international conference robotics and automation science: ICRAS, pp 12–17īorkar PK, Pulinthitha MM, Pansare A (2019) Match pose-a system for comparing poses. Trejo EW, Yuan P (2018) Recognition of Yoga poses through an interactive system with kinect device. Accessed 2021Ĭhen HT, He YZ, Hsu CC (2018) Computer-assisted yoga training system. Yoga: Its Origin, History and Development: 'Yoga'%20is%20derived,and%20body%2C%20Man%20%26%20Nature. Lugaresi C, Tang J, Nash H, McClanahan C, Uboweja E, Hays M, Zhang F, Chang CL, Yong MG, Lee J, Chang WT, Hua W, Georg M, Grundmann M (2019) MediaPipe: a framework for building perception pipelines Int J Multidiscip Res 03:11–148Ĭhen Y, Tian Y, He M (2020) Monocular human pose estimation: a survey of deep learning-based methods. Sharma YK, Sharma S, Sharma E (2018) Scientific benefits of Yoga: a review. Rodríguez-Hidalgo AJ, Pantaleón Y, Dios I, Falla D (2020) Fear of COVID-19, Stress, and Anxiety in University undergraduate students: a predictive model for depression. Guddeti RR, Dang G, Williams MA, Alla VM (2019) Role of Yoga in cardiac disease and rehabilitation. ![]() ![]() ![]() The experimental findings in terms of feedback generated using the user videos gave a functional validation of the proposed procedure and its usability in modern day human life. With this inherent capability of pose feedback generation, the proposed system thus enables the naive performers to evaluate their poses and correct it when it deviates from the correct pose sequence. The method was evaluated in real-time on people of varied age groups and gender for four different asanas, and it was proven that it recognizes incorrect portions of the performed asanas for all the test cases. ![]() The system then compares the angles obtained from the instructor's pose and the users for feedback generation and provides correction if the difference is larger than a certain threshold. Our method consists of two main components: a hand gesture component that records video using hand gestures and a pose estimation component that detects body joint coordinates. We have used computer vision techniques as it can perform various visual data frame related operations in real time. In this research article, we present a user-friendly python-flask based web application that assists its registered users to perform every pose accurately. Moreover, it is difficult for beginners to identify the incorrect portions of their yoga postures on their own. However, yoga should be performed under professional supervision and in a regulated manner, as it can be harmful to one's health if done incorrectly. It is a well-known proverb that a healthy mind lives in a healthy body, and yoga is one such means for connecting the body to the mind. ![]()
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