AI-Based Personalized Workout Recommendation System

Artificial Intelligence (AI) has quickly transformed the future of health and fitness by making it possible to conduct data-driven and adaptive exercising programs. Standard workout programs tend to be generic and are not concerned with individual differences in physiology, behavioral and individual objectives. This paper introduces an individualized exercise prescription system that uses AI to process biometric and behavioral information and, thus, create personalized exercise programs. The system uses machine-learning models to analyzing the information collected by wearable devices, mobile fitness apps, and the history of past workout to prescribe exercises with the appropriate intensity and duration. The refinement of recommendations through a continuous feedback mechanism can only be done through learning based on the user interaction and performance results. The experiments also show that the approach can improve the motivation, adherence, and training efficiency by over twenty percent, which proves that AI can revolutionize personalized planning of fitness and online management of wellness.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-18
DOI
https://doi.org/10.5281/zenodo.17972991
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Personalized Workout Recommendation System

Zenodo (CERN European Organization for Nuclear Research)
Mobile Health and mHealth Applications
article

AI-Based Personalized Workout Recommendation System

article en

Abstract

Artificial Intelligence (AI) has quickly transformed the future of health and fitness by making it possible to conduct data-driven and adaptive exercising programs. Standard workout programs tend to be generic and are not concerned with individual differences in physiology, behavioral and individual objectives. This paper introduces an individualized exercise prescription system that uses AI to process biometric and behavioral information and, thus, create personalized exercise programs. The system uses machine-learning models to analyzing the information collected by wearable devices, mobile fitness apps, and the history of past workout to prescribe exercises with the appropriate intensity and duration. The refinement of recommendations through a continuous feedback mechanism can only be done through learning based on the user interaction and performance results. The experiments also show that the approach can improve the motivation, adherence, and training efficiency by over twenty percent, which proves that AI can revolutionize personalized planning of fitness and online management of wellness.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 24%
Mobile Health and mHealth Applications
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AI-Based Personalized Workout Recommendation System · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS