A Multimodal Cardiovascular-Safety-Aware System for Personalized Diet and Exercise

Personalized diet and exercise applications com-monly rely on demographic and anthropometric information such as age, gender, height, weight, body mass index, activity level, fitness goals, and food preferences. Although some systems inte-grate wearable data, heart rate is frequently used for monitoring rather than as a transparent safety constraint in recommendation generation; blood-pressure information, body-pose analysis, and non-diagnostic facial-skin observations are also rarely integrated into one explainable decision pipeline. This paper proposes a multimodal, cardiovascular-safety-aware mobile health framework that generates adaptive diet and exercise recommendations using anthropometric characteristics, optional body and facial images, heart-rate monitoring, and repeated blood-pressure readings. The system contains six modules: user profiling and health screening; body-pose analysis using MediaPipe Pose; optional facial-skin analysis for acne-like lesion severity estimation; cardiovascular risk and safety classification; constraint-based diet planning; and adaptive exercise recommendation. The facial-image component is intentionally non-diagnostic: it identifies only visible acne-like skin features and does not infer digestive disorders, nutritional deficiencies, hormonal disorders, or internal-organ conditions from facial location. Heart rate and blood pressure are used as primary safety signals to determine exercise intensity, progres-sion, alerts, and relevant dietary constraints such as lower-sodium alternatives where repeated elevated blood-pressure readings are observed. The proposed system will be evaluated through an eight-week pilot study involving adult participants. Outcomes will include model performance, recommendation relevance, usability, adherence, heart-rate and blood-pressure safety events, and selected fitness indicators. The framework is intended to support health and fitness planning and does not replace diagnosis, treatment, or professional medical advice.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-21
DOI
https://doi.org/10.5281/zenodo.23511984
Primary Topic
Mobile Health and mHealth Applications
Type
article
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article

A Multimodal Cardiovascular-Safety-Aware System for Personalized Diet and Exercise

Dr.Abuzar Ansari Shruti Devdas Salvi
Zenodo (CERN European Organization for Nuclear Research)
Mobile Health and mHealth Applications
article

A Multimodal Cardiovascular-Safety-Aware System for Personalized Diet and Exercise

Dr.Abuzar Ansari Shruti Devdas Salvi
article en

Abstract

Personalized diet and exercise applications com-monly rely on demographic and anthropometric information such as age, gender, height, weight, body mass index, activity level, fitness goals, and food preferences. Although some systems inte-grate wearable data, heart rate is frequently used for monitoring rather than as a transparent safety constraint in recommendation generation; blood-pressure information, body-pose analysis, and non-diagnostic facial-skin observations are also rarely integrated into one explainable decision pipeline. This paper proposes a multimodal, cardiovascular-safety-aware mobile health framework that generates adaptive diet and exercise recommendations using anthropometric characteristics, optional body and facial images, heart-rate monitoring, and repeated blood-pressure readings. The system contains six modules: user profiling and health screening; body-pose analysis using MediaPipe Pose; optional facial-skin analysis for acne-like lesion severity estimation; cardiovascular risk and safety classification; constraint-based diet planning; and adaptive exercise recommendation. The facial-image component is intentionally non-diagnostic: it identifies only visible acne-like skin features and does not infer digestive disorders, nutritional deficiencies, hormonal disorders, or internal-organ conditions from facial location. Heart rate and blood pressure are used as primary safety signals to determine exercise intensity, progres-sion, alerts, and relevant dietary constraints such as lower-sodium alternatives where repeated elevated blood-pressure readings are observed. The proposed system will be evaluated through an eight-week pilot study involving adult participants. Outcomes will include model performance, recommendation relevance, usability, adherence, heart-rate and blood-pressure safety events, and selected fitness indicators. The framework is intended to support health and fitness planning and does not replace diagnosis, treatment, or professional medical advice.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 8%
Mobile Health and mHealth Applications
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A Multimodal Cardiovascular-Safety-Aware System for Personalized Diet and Exercise — Dr.Abuzar Ansari Shruti Devdas Salvi · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS