A Conceptual Framework for Athlete Health Using AIoT, Wearables, and Personalized Performance Intelligence
Source abstract
Abstract
Advancing athlete health requires a shift from reactive sports medicine toward proactive, personalized, and longitudinal care. This article presents a conceptual framework for an Interdisciplinary AI Center for Longevity and Well-Being designed to integrate Artificial Intelligence of Things (AIoT), wearable sensing, and multimodal analytics into a unified athlete health ecosystem. The manuscript contextualizes the proposed framework with relevant literature across key technical domains and presents a reference edge–fog–cloud architecture together with a proof-of-concept dashboard pipeline to illustrate technical feasibility. Within this framework, heterogeneous data streams from wearable physiological sensors, biomechanical devices, non-invasive biomarker monitors, and environmental trackers are organized to support multimodal analysis and individualized performance intelligence. The paper outlines five target application domains: real-time health monitoring, injury risk assessment, performance optimization, holistic well-being evaluation, and longevity-oriented health management. Privacy-preserving and interpretable AI components, including federated learning, differential privacy, and explainability-oriented design considerations, are presented as key architectural priorities, while several elements are explicitly identified as future development directions. Rather than claiming full real-world validation, this work provides an interdisciplinary blueprint and prototype-informed foundation for future research and implementation at the intersection of computer science, biomedical engineering, and sports science.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Artificial Intelligence in Healthcare and Education · Context-Aware Activity Recognition Systems · Physical Activity and Health
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Engineering Sciences, Università degli Studi Guglielmo Marconi, Via Plinio 44, 00193 Rome, Italy
Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Universitätspl. 2, 39104 Magdeburg, Germany
Department of Neurosciences, Biomedicine, and Movement Sciences, Università degli Studi di Verona, Strada le Grazie 15, 37134 Verona, Italy
Department of Medicine and Health Sciences, Università degli Studi del Molise, Via Francesco De Sanctis 1, 86100 Campobasso, Italy
Department of Human Sciences, Università degli Studi Guglielmo Marconi, Via Plinio 44, 00193 Rome, Italy
Department of Movement, Human and Health Sciences, Università di Roma “Foro Italico”, Via dei Robilant 1, 00135 Roma, Italy
Department of Experimental Medicine, Università del Salento, Via Provinciale Lecce-Monteroni, 73100 Lecce, Italy
Faculty of Electrical and Information Technology, Otto-von-Guericke-University Magdeburg, Universitätspl. 2, 39104 Magdeburg, Germany
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