A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks

This paper presents a personalized fitness mobile application with the use of Artificial Intelligence (AI), namely Artificial Neural Networks (ANN), which contributes to injury rehabilitation. It automatically generates customized workout plans on a weekly basis, taking into consideration user-supplied data on issues such as injury type, fitness level, body mass index, and available equipment. The system continuously updates the workout plans with the help of feedback provided by the user to achieve the best recovery process. Built with React Native for the frontend and Django for the backend, this application guarantees access anytime, anywhere, with smooth data treatment. The paper further reflects on the general implications of using AI in e-fitness, stresses intuitive user interfaces, and furthers possibilities such technologies could undergo.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/smap63474.2024.00020
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.71
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A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks

Akrivi Krouska, Cleo Sgouropoulou, Phivos Mylonas, Christos Troussas et al.
1 citations
Artificial Intelligence in Healthcare
0.71
article

A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks

Akrivi Krouska, Cleo Sgouropoulou, Phivos Mylonas, Christos Troussas, Nikolaos Kalofonos
article en
1 citations

Abstract

This paper presents a personalized fitness mobile application with the use of Artificial Intelligence (AI), namely Artificial Neural Networks (ANN), which contributes to injury rehabilitation. It automatically generates customized workout plans on a weekly basis, taking into consideration user-supplied data on issues such as injury type, fitness level, body mass index, and available equipment. The system continuously updates the workout plans with the help of feedback provided by the user to achieve the best recovery process. Built with React Native for the frontend and Django for the backend, this application guarantees access anytime, anywhere, with smooth data treatment. The paper further reflects on the general implications of using AI in e-fitness, stresses intuitive user interfaces, and furthers possibilities such technologies could undergo.

University of West Attica (GR)
Openalex Percentile: Top 18%
Artificial Intelligence in Healthcare
0.71
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A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks — Akrivi Krouska, Cleo Sgouropoulou, et al. · (2024) | TGRS Research Map | TGRS