Indoors Fitness Training Monitoring based on OpenPose

Authors

  • J.Haoran Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan.
  • S. Karungaru Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan.
  • K. Terada Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan.

Keywords:

Image Processing, Deep learning, Body part Recognition

Abstract

With the continuation of the COVID-19 pandemic, people's daily life has changed. The changing life habits are reflected in the increasing number of hours working at home. Mostly affected is physical fitness, because of limitations or fear of the gym/outdoors or effective exercise indoors.  However, with the arrival of the post-pandemic era, although working at home has improved, the fitness problem still haunts people. Some people have become accustomed to home fitness and are no longer limited to the traditional gym or gymnasium. However, proper and safe exercising is still a challenge due to the lack of live coaching.  With the advent of artificial intelligence and the improvement of virtual reality (VR) and augmented reality (AR) capabilities, the options for live off-site coaching have become feasible. This study is based on OpenPose technology in artificial intelligence to monitor the standard of people's movements in-home fitness. The study results are encouraging.

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Published

2024-05-30

How to Cite

J.Haoran, S. Karungaru, & K. Terada. (2024). Indoors Fitness Training Monitoring based on OpenPose. JOURNAL OF ADVANCED APPLIED SCIENTIFIC RESEARCH, 6(3). Retrieved from http://mail.joaasr.com/index.php/joaasr/article/view/947