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.

The outbreak of the Covid-19 pandemic has caused a severe overload of intensive care units with a consequent drastic reduction of ordinary hospitalization, diagnostic tests, and interventions that has led to a significant increase in the number of deaths due to diseases other than the new coronavirus. Information and Communication Technologies (ICT) and the forthcoming Sixth-Generation (6G) system may revolutionize the doctor-patient relationship and healthcare modalities owing to the introduction of eHealth (or digital health). In this context, Non-Terrestrial Networks (NTNs) have vital importance in providing global connectivity thus improving the availability of eHealth services, especially in rural and remote areas. In this paper, we propose a Reliable Satellite Routing Algorithm (RSRA) for a 3D NTN based on Low-Earth Orbit (LEO) satellites. RSRA enables health data detected by sensors worn by the patients to be transmitted to health professionals by selecting a chain of reliable LEO satellites in order to protect such sensitive data. The system-level performance of proposed RSRA algorithm is assessed through simulation campaigns and compared against a routing approach that neglects LEO satellite reliability.

The COVID-19 pandemic has changed the world. Today, the use of information and communications technology (ICT) in support of education, medicine, business, and administration has become a reality practically everywhere. In particular, the eHealth (digital Health) sector is on the cusp of a revolution, fueled by the worldwide health emergency due to the spread of the new coronavirus. With a view to developing new sixth-generation (6G)-oriented architectures, advanced eHealth services like telemonitoring would benefit from the support of technologies that guarantee secure data access, ultralow latency and very-high reliability targets, which are hardly achievable by the fifth generation (5G). This is the reason why this work proposes an eHealth system architecture, in which low-latency enabling technologies like Device-to-Device (D2D) communications and multiaccess edge computing (MEC) are integrated and supported by security mechanisms for an optimal management of sensitive health data collected by Internet of Medical Things (IoMT) devices. A preliminary evaluation of the proposed framework is provided that shows promising results in terms of data security and latency reduction.

Device-to-Device (D2D) communication will be one of the key enabling technologies for the future fifth generation (5G) cellular systems. A D2D communication allows nearby devices to transmit data directly, without passing through the network. Thanks to the proximity between devices, it allows to boost network performance by improving data rate, energy saving, and delay. Objective of the proposal in this paper is to securing future D2D communications. To this purpose, a new mechanism is designed which leverages (i) social trustworthiness, achieved through the Social Internet of Things (SIoT) paradigm, and (ii) encryption based on the Diffie-Hellman Key Exchange (DHKE) protocol for public key distribution. Results of a simulation campaign carried out by using MATLAB demonstrate that the proposed protocol can effectively enhance the protection of transmitted data by excluding users considered to be unreliable on the basis of both their reputation and their past behavior.