Paper Title
Gym-Buddy
Article Identifiers
Authors
Kritika Pandey , Snehal Kumbhar , Rhea Malpekar , Prof.Poonam Vengurlekar
Keywords
:Machine Learning,Computer Vision,Deep Learning,Pose estimation,Mediapipe blazepose,Convolution neural network.
Abstract
Over the past few years, there has been a notable increase in interest within the fitness industry, as more people are actively participating in a variety of exercises and sports. The provision of precise and immediate feedback on exercise form is paramount for optimizing performance, reducing the risk of injuries, and attaining fitness objectives. The ”Gym-Buddy” initiative represents a machine learning endeavor aimed at transforming the fitness landscape by delivering comprehensive pose detection capabilities for exercise and sports enthusiasts. Gym-Buddy utilizes cutting-edge computer vision and deep learning methodologies to analyze and evaluate users’ body positions during different exercise regimens and sports engagements. The key objectives of this project en- compass: Pose Detection: Gym-Buddy employs advanced algorithms for pose estimation to identify and monitor crucial body joints and movements in real-time. This functionality enables the system to furnish accurate feedback re- garding exercise form, posture, and movement precision. Exercise Guidance: The Gym-Buddy system is crafted to provide interactive exercise guidance, assisting users in aligning their bodies correctly, refining their movements, and maintaining proper form throughout their workout sessions. Users can receive visual prompts and auditory feedback via their preferred device, making it a versatile companion for home workouts, gym sessions, and outdoor activities. Gym-Buddy is Accessible via a user-friendly web application, Gym-Buddy is designed to be seamlessly integrated into the routines of individuals at all fitness levels. The machine learning models within the system continuously enhance based on user input, ensuring personalized and precise feedback. The overarching goal of this project is to empower individuals to achieve their fitness and sports performance aspirations by furnishing them with an intelligent and supportive training ally. Gym-Buddy not only enhances workout experiences but also advocates for healthier lifestyles and injury prevention, thereby contributing signif- icantly to the overall well-being of its users.
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How To Cite (APA)
Kritika Pandey, Snehal Kumbhar, Rhea Malpekar, & Prof.Poonam Vengurlekar (March-2024). Gym-Buddy. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), d58-d65. https://ijnrd.org/papers/IJNRD2403308.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : d58-d65
Other Publication Details
Paper Reg. ID: IJNRD_215717
Published Paper Id: IJNRD2403308
Downloads: 000121989
Research Area: Computer Science & TechnologyÂ
Country: Ambernath (East),Thane, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403308.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403308
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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