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<p>Practicing yoga benefits both mental and nervous system and helps mitigate several health problems. However, not performing yoga in the correct manner can worsen the symptoms as well. This work presents a novel technology-driven approach named spondylitis-related yoga MediaPipe angle-based regularized network (SpY_MARNet) to assist people to perform yoga postures for treating spondylitis in the correct way. This work enables real-time interaction and provides immediate feedback, assisting in correcting postures and suggesting modifications if necessary. This work also monitors the duration for which each pose is retained which is a vital aspect of yoga practice. Also, the users are categorized into beginner, intermediate, and advanced levels based on their yoga performance. By using the model we achieved an accuracy of 99.7%. The results indicate significant promise in aiding individuals with spondylitis, opening avenues for further research and application in other physical therapies and wellness practices.</p>

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Angle-based regularized deep learning model for gauging effectiveness in performing yoga postures

  • 期刊论文

  • 发表日期：

    2025年2月27日

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  • Akshansh Rawat,
  • Ananthakrishnan Balasundaram,
  • Chockalingam Aravind Vaithilingam

摘要

Practicing yoga benefits both mental and nervous system and helps mitigate several health problems. However, not performing yoga in the correct manner can worsen the symptoms as well. This work presents a novel technology-driven approach named spondylitis-related yoga MediaPipe angle-based regularized network (SpY_MARNet) to assist people to perform yoga postures for treating spondylitis in the correct way. This work enables real-time interaction and provides immediate feedback, assisting in correcting postures and suggesting modifications if necessary. This work also monitors the duration for which each pose is retained which is a vital aspect of yoga practice. Also, the users are categorized into beginner, intermediate, and advanced levels based on their yoga performance. By using the model we achieved an accuracy of 99.7%. The results indicate significant promise in aiding individuals with spondylitis, opening avenues for further research and application in other physical therapies and wellness practices.