A Self Learning Yoga Monitoring System Based on Pose Estimation

被引:1
|
作者
Movva, Prahitha [1 ]
Pasupuleti, Hemanth [1 ]
Sarma, Himangshu [1 ]
机构
[1] Indian Inst Informat Technol, Comp Vis Grp, Dept Comp Sci & Engn, Sri City, Chittoor, India
关键词
Yoga; Physical activity; Motion; COVID-19;
D O I
10.1007/978-3-031-05409-9_7
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Modern life is stressful - long working hours, poor diets, inactivity, and increasing social isolation in the digital age have all contributed to rising rates of anxiety and depression. The COVID-19 pandemic escalated this situation with a series of quarantines. Without physical interaction, learning a new skill can be frustrating and stressful, especially a skill like Yoga that requires balance and physical coordination. On the one hand, many people cannot afford a personal trainer, but on the other, books and video tutorials do not offer personalized feedback. These limitations make learning Yoga on our own an overwhelming task. We propose a minimal investment model that will help people learn and practice correct Yoga forms from the comfort of their homes in an easy, stress-free manner - just by using their camera. A deep learning model is proposed based on PoseNet which gives an accuracy of 96.77% on the test dataset. We also conducted a survey to measure the satisfaction, efficiency and effectiveness of our system. Overall, 81.8% of the participants felt that our system helped them learn and perform the exercises better and 52.2% of them rated it as being "very good".
引用
收藏
页码:81 / 91
页数:11
相关论文
共 50 条
  • [1] Deep Learning Models for Yoga Pose Monitoring
    Swain, Debabrata
    Satapathy, Santosh
    Acharya, Biswaranjan
    Shukla, Madhu
    Gerogiannis, Vassilis C.
    Kanavos, Andreas
    Giakovis, Dimitris
    [J]. ALGORITHMS, 2022, 15 (11)
  • [2] Yoga Pose Estimation and Feedback Generation Using Deep Learning
    Thoutam, Vivek Anand
    Srivastava, Anugrah
    Badal, Tapas
    Mishra, Vipul Kumar
    Sinha, G. R.
    Sakalle, Aditi
    Bhardwaj, Harshit
    Raj, Manish
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [3] A Proposal of Yoga Pose Assessment Method Using Pose Detection for Self-Learning
    Thar, Maybel Chan
    Winn, Khine Zar Ne
    Funabiki, Nobuo
    [J]. 2019 INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION TECHNOLOGIES (ICAIT), 2019, : 137 - 142
  • [4] Yoga Pose Estimation Using Angle-Based Feature Extraction
    Borthakur, Debanjan
    Paul, Arindam
    Kapil, Dev
    Saikia, Manob Jyoti
    [J]. HEALTHCARE, 2023, 11 (24)
  • [5] ReferPose: Distance Optimization-Based Reference Learning for Human Pose Estimation and Monitoring
    Wang, Miaohui
    Xu, Zhuowei
    Xie, Wuyuan
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (03) : 4440 - 4450
  • [6] Gait Pose Estimation Based on Manifold Learning
    Zhao, Fan
    Ma, Shiwei
    Hao, Zhonghua
    Wen, Jiarui
    [J]. LIFE SYSTEM MODELING AND SIMULATION, 2014, 461 : 82 - 90
  • [7] Pose Estimation of Yoga Poses using ML Techniques
    Krishnan, Hema
    Jayaraj, Anagha
    Anagha, S.
    Thomas, Christy
    Joy, Grace Mol
    [J]. 2022 IEEE 19TH INDIA COUNCIL INTERNATIONAL CONFERENCE, INDICON, 2022,
  • [8] Active Learning for Human Pose Estimation based on Temporal Pose Continuity
    Mori, Taro
    Deguchi, Daisuke
    Kawanishi, Yasutomo
    Ide, Ichiro
    Murase, Hiroshi
    Inoshita, Tetsuo
    [J]. INTERNATIONAL WORKSHOP ON ADVANCED IMAGING TECHNOLOGY (IWAIT) 2022, 2022, 12177
  • [9] SELF-SUPERVISED LEARNING FOR HUMAN POSE ESTIMATION IN SPORTS
    Ludwig, Katja
    Scherer, Sebastian
    Einfalt, Moritz
    Lienhart, Rainer
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA & EXPO WORKSHOPS (ICMEW), 2021,
  • [10] Novel deep learning models for yoga pose estimator
    Talaat, Amira Samy
    [J]. SN APPLIED SCIENCES, 2023, 5 (12)