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Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
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Real-time yoga posture correction using deep learning for individuals with physical disabilities.

Vansh Aggarwal1, Vaibhav Yadav1, Saloni Chaudhary1

  • 1Department of Computer Science and Engineering, Netaji Subhas University of Technology, New Delhi, India.

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Summary
This summary is machine-generated.

This study introduces a deep learning system for real-time yoga pose correction, aiding individuals with physical disabilities. The AI offers pose guidance, enhancing accessibility for chair yoga practitioners.

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence
  • Rehabilitation Science

Background:

  • Growing adoption of yoga for wellness necessitates advanced pose recognition methods.
  • Existing yoga pose estimation research often excludes individuals with physical disabilities.
  • AI offers a feasible solution for remote yoga guidance, especially for those lacking instructor access.

Purpose of the Study:

  • To develop and evaluate a deep learning-based system for real-time yoga pose correction.
  • To specifically tailor pose correction for individuals with lower-body physical disabilities.
  • To improve accessibility of chair yoga for people with physical challenges.

Main Methods:

  • Utilized the Thunder variant of the MoveNet model for real-time pose estimation.
  • Applied deep convolutional neural networks (CNNs) to analyze user posture via video input.
  • Developed a novel dataset specifically for chair yoga poses.

Main Results:

  • The system accurately identifies and corrects yoga posture errors in real-time.
  • Demonstrated the effectiveness of the MoveNet model for yoga pose analysis in the target population.
  • The developed chair yoga dataset provides a new resource for research.

Conclusions:

  • Deep learning offers an effective solution for real-time yoga pose correction for individuals with disabilities.
  • The proposed system enhances the accessibility and practice of chair yoga.
  • This research contributes to inclusive wellness technologies through AI-driven pose guidance.