SMARTTEST is a European Doctoral Network for Resilient Remote Healthcare using Intelligent Sensing and Communication Technologies.

It is funded by Horizon Europe (HORIZON) through the Marie Sklodowska-Curie Actions (MSCA) Training & Mobility Actions (TMA) in the form of a Doctoral Networks (DN) which will host 11 doctoral candidates across Europe and beyond.

These inter-disciplinary engineers will develop a holistic view on the design and development of integrated sensing and communication devices, as well as algorithms for contact-free, continuous and proactive remote health monitoring.

The project consortium is coordinated by University of Twente, and participated by Politecnico di Milano with other 7 academic partners, 8 companies, 1 state inspectorate, 1 hospital and 1 healthcare service organization.

The goal is training a future generation of engineers that are capable of bridging advanced wireless technologies and radio signal processing, biomedical signal analytics and health monitoring to maximize the effectiveness of personalized healthcare.

The SMARTTEST research programme is designed on two backbone principles:
(1) it must address the challenges of the personalized health monitoring paradigm, being contact-free and proactive and able to perform early alarm of disease complication, health restoration monitoring and chronic disease prevention;
(2) it must address the challenges of the core enabling technology - integrating intelligent human sensing into communication networks.

The POLIMI team, led by Professor Monica Nicoli, from the Department of Management, Economics and Industrial Engineering (DIG), includes the researchers of the IoTLab Dr. Mattia Brambilla and Zhaorui Yin, as well as Professor Michele d'Amico from Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB).

The IoT Lab team is leader of the Work Package WP6 whose objective is to create a European Doctoral School for intelligent sensing and communication for remote health monitoring and develop the training programme.

Furthermore, Politecnico di Milano is leader of the task on models and algorithms for human sensing and gesture recognition in WP2, and it also contributes to WP3 and WP4. The goal of the research is to design models and algorithms for human sensing exploiting the high-precision sensing/positioning capability of future generation cellular networks with the aid of machine learning methods.