Smartfit: Artificial Intelligence-Powered Exercise Recognition

The growing need for smart fitness apps requires precise exercise recognition and real-time feedback. Conventional workout tracking techniques are imprecise and non-interactive, resulting in incorrect exercise form and injuries. To overcome this, SmartFit presents an AI-based exercise recognition system based on Mediapipe and OpenCV for real-time pose estimation and movement analysis. The system detects significant body landmarks, computes joint angles, and recognizes exercises using machine learning algorithms. An intuitive interface offers immediate feedback, maintaining correct form and engaging the user. The suggested system allows for personalized training, reduces risk of injury, and optimizes exercise efficiency. Experimental results yield accuracy in movement recognition that is high, with implications for fitness and rehabilitation applications.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1109/iccies63851.2025.11033069
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
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article

Smartfit: Artificial Intelligence-Powered Exercise Recognition

Divya Rani, T. S., Naveen Raj K
Context-Aware Activity Recognition Systems
article

Smartfit: Artificial Intelligence-Powered Exercise Recognition

Divya Rani, T. S., Naveen Raj K
article en

Abstract

The growing need for smart fitness apps requires precise exercise recognition and real-time feedback. Conventional workout tracking techniques are imprecise and non-interactive, resulting in incorrect exercise form and injuries. To overcome this, SmartFit presents an AI-based exercise recognition system based on Mediapipe and OpenCV for real-time pose estimation and movement analysis. The system detects significant body landmarks, computes joint angles, and recognizes exercises using machine learning algorithms. An intuitive interface offers immediate feedback, maintaining correct form and engaging the user. The suggested system allows for personalized training, reduces risk of injury, and optimizes exercise efficiency. Experimental results yield accuracy in movement recognition that is high, with implications for fitness and rehabilitation applications.

Velammal Medical College Hospital and Research Institute (IN)
Openalex Percentile: Top 88%
Context-Aware Activity Recognition Systems
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