Special Session #02

SPECIAL SESSION #02

Maria Giovanna Bianco

University Magna Graecia of Catanzaro, Italy

• mg.bianco@unicz.it

Camilla Calomino

University Magna Graecia of Catanzaro, Italy

• camilla.calomino@unicz.it

The integration of artificial intelligence and multimodal sensing technologies into clinical workflows is opening new frontiers in disease diagnosis, longitudinal monitoring, and personalized healthcare. Driven by advances in biomedical signal and image processing, wearable systems, and contactless sensing platforms, these technologies are increasingly enabling the transition from lab-based prototypes to real-world clinical tools.

This Special Session focuses on innovative engineering methods for the extraction, analysis, and integration of multimodal digital biomarkers in translational healthcare applications.

Topics of interest include, but are not limited to:

• Multimodal biomarker extraction and data fusion;
• Biomedical signal and image processing for clinical applications;
• Neuroimaging analytics and brain-based biomarkers;
• Wearable, flexible, and implantable sensing systems for continuous monitoring;
• Contactless sensing approaches, including radar- and vision-based physiological monitoring;
• Remote patient monitoring and digital health platforms;
• Explainable AI and machine learning for clinical decision support;
• Validation, standardization, and regulatory aspects of AI-driven biomarkers.

Maria Giovanna Bianco is an Assistant Professor in Applied Medical Technology and Methodology at the Neuroscience Research Center, Department of Medical and Surgical Sciences, University of Magna Graecia of Catanzaro, Italy. She received her Ph.D. in Biomedical and Computer Engineering in 2016. From 2014 to 2015, she was a visiting scientist at the Montreal Neurological Institute, McGill University (Montreal, QC, Canada).
She has authored over 70 peer-reviewed publications in artificial intelligence, neuroimaging, and biomedical signal processing.
Her research focuses on artificial intelligence and machine learning for the development and validation of multimodal digital biomarkers in translational medicine, with applications in neuroimaging and neuropsychological data for the differential diagnosis of neurodegenerative diseases. Her work also includes the design of advanced methods for biomedical signal processing (EMG, EEG, ECoG, and LFP) and pattern recognition from wearable and sensing technologies for clinical applications.

Camilla Calomino is a Researcher in Applied Medical Technology and Methodology at the Neuroscience Research Center, Department of Medical and Surgical Sciences, University of Magna Graecia of Catanzaro, Italy. She received her Ph.D. in Biomarkers of Complex and Chronic Disease in 2025. Her research focuses on the analysis of data acquired from multiple neuroimaging modalities and sensor-based technologies, using artificial intelligence and machine learning techniques in the field of neurodegenerative diseases. Her work also includes the development of software pipelines for multimodal data integration.