A Yoga Pose Difficulty Level Estimation Method Using OpenPose for Self-Practice System to Yoga Beginners

Yoga is an exercise preferable for various users at different ages to enhance physical and mental health. To help beginner yoga self-practitioners avoid getting injured by selecting difficult yoga poses, the information of the difficulty level of yoga poses is very important to provide an objective metric to assist yoga self-practitioners in selecting appropriate exercises on the basis of their skill level by using the yoga self-practice system. To enhance the developed yoga self-practice system, the yoga difficulty level estimation function will enable users to clearly understand whether the selected yoga poses are suitable for them. In this paper, the newest difficulty level estimation method of yoga poses is proposed by using and analyzing OpenPose two-dimensional (2D) human body keypoints. The proposed method effectively uses the selected six keypoints areas of the upper and lower body, body support types, center of gravity calculations, and body tilt angles and slopes to produce estimations. Firstly, the method calculates the weighted centers of the upper and lower human body for each pose by using keypoints. Secondly, it refers the slope of the centroid line between the two centers and infers the body's balance state. Lastly, the system estimates the difficulty level by additionally considering the keypoints of the body to contact the ground. For evaluations of the proposal, more than one hundred yoga poses are collected from the Internet and applied to classify them into five difficulty levels. Through comparisons with subjective levels from one instructor and 10 users, the validity of the estimation results is confirmed, a comparison is performed with existing designs, and it is implemented in embedded systems.