Indonesian Journal of Electrical Engineering and Computer Science Vol. 32, No. 3, December 2023, pp. 1639~1647 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v32.i3.pp1639-1647  1639 Journal homepage: http://ijeecs.iaescore.com Yoga pose annotation and classification by using time- distributed convolutional neural network Somashekhar S. Dhanyal, Suvarna S. Nandyal Department of Computer Science and Engineering, Poojya Doddappa Appa College of Engineering, Kalaburagi, India Article Info ABSTRACT Article history: Received Mar 24, 2023 Revised Aug 21, 2023 Accepted Sep 26, 2023 In India, people have been practicing yoga for thousands of years to improve their health and well-being on all levels. As the pace of technological development increases, this presents a great opening for computational probing across all areas of social domains. Nevertheless, it remains difficult to integrate artificial intelligence (AI) and machine learning (ML) methods to an interdisciplinary field like yoga. The proposed study aims to develop a yoga pose annotation and classification for yogasana recognition in real time. The study considers TensorFlow for better implementation of data automation, performance monitoring. TensorFlow yields better numerical computation and hat helps ML and efficiently develops the neural network. The proposed composed of time-distributed convolutional neural network (CNN) through the Softmax function. Also, a poseNet algorithm is considered to estimate the user’s real-time yoga pose. The use of a database i.e., poseTrack in the proposed method offers annotation to the evaluation of yoga pose and tracking of it. The performance analysis of the proposed yoga pose annotation and classification model suggests that it offers higher accuracy than traditional, support vector machines (SVM) and K-nearest neighbor (KNN). Keywords: Accuracy Annotation Classification Convolutional neural network Machine learning Yoga pose This is an open access article under the CC BY-SA license. Corresponding Author: Somashekhar S. Dhanyal Department of Computer Science and Engineering, Poojya Doddappa Appa College of Engineering Kalaburagi, Karnataka, India Email: sdhanyalresearch@gmail.com 1. INTRODUCTION Technological and scientific progress is accelerating at an unprecedented rate, simplifying people's daily lives. Its importance to modern society has become universally recognized [1]. Throughout the healthcare industry and other fields closely associated with it, the impact of computers and technology driven by computing is well-known, just as it is in all other sectors. Other than conventional medicine, many people turn to disciplines like martial art, zumba, and yoga, to improve their health [2], [3]. Yoga, which has its origins in ancient India, is a collection of techniques for improving one's mental, spiritual, and physical well-being. There has been a significant rise in the importance of yoga in the field of medicine [4]. One is physical and emotional well-being, as well as weight, can all benefit from yoga practice. However, yoga should only be done under the guidance of a trained professional, as improper form can cause serious injuries including sprained ankles, neck pain, and muscular pulls [5]. During training, the yoga teacher must make adjustments to the students' postures. Individual practice of yoga is possible only after receiving appropriate training. Nevertheless, in the present day, individuals are more used to staying at home, thus they have switched to doing practically anything online. In light of the aforementioned, a yoga practice that incorporates modern technologies is essential [6], [7]. For this purpose, there are virtual tutoring and smartphone programs available. Both have a great deal of room for improvement in terms of computational power, intelligence, and efficiency [8].