SPECIAL SESSION #01

Juri Taborri

University of Tuscia, Italy

• juri.taborri@unitus.it

Ilaria Mileti

University Niccolò Cusano, Italy

• ilaria.mileti@unicusano.it

The integration of wearable sensors and artificial intelligence is gaining increasing relevance within the Industry 4.0 framework, with strong applications in both clinical and sport domains. These technologies enable the development of advanced decision support systems, improving the management of information, the quality of insights, the interpretation of surrounding contexts, and fostering a more personalized and data-driven approach in medicine and training.

The rapid technological progress requires continuous updates of methodologies: the design of innovative sensors and the development of data-processing algorithms are essential for diagnosis, monitoring of physical and physiological parameters, and optimization of performance. In this scenario, the metrological characterization of novel sensors and the validation of AI-based algorithms are crucial steps to ensure data reliability, both in healthcare systems and in elite sports contexts.

Another key aspect is the correlation between data collected from sensors and AI-based algorithms with established clinical scales or sport performance metrics: this is necessary to foster the effective adoption and recognition of these technologies.

This Special Session aims to discuss innovative methodologies based on wearable sensors and advanced AI algorithms, addressing applications in clinical, sport, and more broadly cyber-physical systems within Industry 4.0.

Topics of interest include, but are not limited to:

• Design and characterization of innovative sensors for clinical and sport applications;
• Development and validation of AI algorithms for analyzing physical and physiological parameters;
• Correlation between sensor-derived indices and clinical scales or sport performance metrics;
• Definition of protocols and methods to support decision-making in healthcare and sport systems;
• Innovative approaches to enable personalized medicine and training in the Industry 4.0 era.

Juri Taborri is a Tenure-Track Researcher in Mechanical and Thermal Measurements at University of Tuscia in Viterbo, Italy. He received the master’s degree cum laude in biomedical engineering from the Sapienza, University of Rome, Italy, in 2014. He received the PhD in Industrial and Management Engineering in 2017. His research interests include biomechanical measurements, validation and metrological characterization of innovative sensor systems, electromyography and muscle synergies, machine-learning algorithms for human motion identification and control of robotic device for rehabilitation. He is co-founder of Tech4All, an innovative startup that realizes supporting digital tools based on artificial intelligence for dyslexic people

Ilaria Mileti is an Associate Professor in mechanical and thermal measurements at the Department of Engineering, University Niccolò Cusano, Rome. She received the master’s degree in biomedical engineering from Sapienza University of Rome, Rome, Italy, in 2015, and the Ph.D. degree in industrial and management engineering from the Sapienza University of Rome, in 2019. She is currently a member of Ph.D. Course Advanced Modelling, Materials and Technologies. Her research interests include measurements for experimental biomechanics, wearable systems, machine learning algorithms, and robotic devices.