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Exercise Posture Correction Application: A comprehensive review

  • Unique Paper ID: 171747
  • Volume: 11
  • Issue: 8
  • PageNo: 849-853
  • Abstract:
  • People often learn to perform exercises with proper form through personal research or guidance from experienced individuals, such as personal trainers. However, incorrect form still accounts for 33.3% of exercise-related injuries. Studies have shown that having a personal trainer significantly reduces injury rates. Despite this benefit, factors such as cost, scheduling conflicts, and the preference for training alone often limit access to personal trainers. Given that 91% of UK adults own a smartphone, a mobile app could potentially serve as an alternative to a personal trainer. This paper explores solutions proposed by various studies on Exercise Form Correctors utilizing convolutional neural networks (CNN) and other machine learning techniques. It provides an in-depth review of these studies, including insights into the tools, technologies, and algorithms employed, as well as their accuracy. Additionally, it discusses the implementation of an Exercise Posture Correction application developed using Flutter and OpenCV. The paper also highlights future trends and research opportunities, emphasizing the potential benefits of larger, more diverse datasets and the integration of wearable sensors with machine learning algorithms. Finally, it summarizes the key findings from the reviewed studies.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 8
  • PageNo: 849-853

Exercise Posture Correction Application: A comprehensive review

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