The healthcare sector is experiencing a profound transformation, fueled by the rapid evolution of sixth-generation (6G) cellular networks and Internet of Things (IoT) technologies. At the heart of this shift lies the concept of medical digital twins (MDTs), which serve as dynamic virtual representations of physical systems or biological processes. MDTs offer a secure environment to simulate and evaluate therapeutic strategies, leading to reduced costs and more informed clinical decision-making. They also enable real-time support and in-depth data analysis, setting new standards for patient care. Nonetheless, realizing the full capabilities of MDTs remains challenging due to the inherent complexity of human life cycles. Crucial aspects include selecting appropriate data sources and defining robust communication protocols between the physical and digital realms. In particular, integrating wearable technologies with edge computing and WiFi-based Channel State Information (CSI) can significantly enhance health monitoring and activity recognition for elderly individuals within indoor settings. The synergy of IoT advancements and 6G networks paves the way for improved data exchange and continuous synchronization between digital and physical counterparts. This paper, part of the HIPPOCRATES project, presents an IoT-driven architecture for MDTs that incorporates wearable sensors and CSI data to strengthen health monitoring and early intervention strategies, with a focus on elderly care.

Medical digital twins for elderly care: human-centered technologies for continuous health monitoring

Jose A.;Marcello F.;Pilloni V.;
2025-01-01

Abstract

The healthcare sector is experiencing a profound transformation, fueled by the rapid evolution of sixth-generation (6G) cellular networks and Internet of Things (IoT) technologies. At the heart of this shift lies the concept of medical digital twins (MDTs), which serve as dynamic virtual representations of physical systems or biological processes. MDTs offer a secure environment to simulate and evaluate therapeutic strategies, leading to reduced costs and more informed clinical decision-making. They also enable real-time support and in-depth data analysis, setting new standards for patient care. Nonetheless, realizing the full capabilities of MDTs remains challenging due to the inherent complexity of human life cycles. Crucial aspects include selecting appropriate data sources and defining robust communication protocols between the physical and digital realms. In particular, integrating wearable technologies with edge computing and WiFi-based Channel State Information (CSI) can significantly enhance health monitoring and activity recognition for elderly individuals within indoor settings. The synergy of IoT advancements and 6G networks paves the way for improved data exchange and continuous synchronization between digital and physical counterparts. This paper, part of the HIPPOCRATES project, presents an IoT-driven architecture for MDTs that incorporates wearable sensors and CSI data to strengthen health monitoring and early intervention strategies, with a focus on elderly care.
2025
979-8-3315-7782-7
979-8-3315-7781-0
Digital twin
IoT
CSI
Edge Computing
Elderly care
Assistive technology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/494230
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