Thematic Session 7

THEMATIC SESSION #07

Ersilia Vallefuoco

University of Naples Federico II, Italy

• ersilia.vallefuoco@unina.it

Michela Russo

University of Naples Federico II, Italy

• michela.russo2@unina.it

Vittorio Santoriello

University of Naples Federico II, Reykjavik University

• vittorio.santoriello@unina.it

Extended Reality (XR) technologies are increasingly impacting biomedical research, clinical practice, and patient-centered care by enabling immersive and interactive experiences tailored to complex healthcare scenarios.

This Special Session explores XR-based biomedical applications from two complementary perspectives: tools designed for clinicians and applications designed for patients. From the clinical side, XR supports diagnostic reasoning, surgical planning, and medical training through immersive visualization of anatomic models, medical data and simulation-based environments. From the patient perspective, XR is widely adopted in rehabilitation, chronic disease management, and health education, where serious games and virtual training enhance engagement, motivation, and adherence to specific programs. Additionally, the integration of Artificial Intelligence (AI) into XR system enables adaptive and personalized environments, while biosignals such as EEG, EMG, ECG, eye tracking, and motion data allow XR applications to become context-aware and biofeedback-driven.

Submissions are encouraged on, but not limited to, the following topics:

• XR (Virtual Reality, Augumented Reality, Mixed Reality) applications for clinical practice, diagnosis, surgical planning, and medical training
• XR-based systems for patient rehabilitation, mental health, chronic disease management, and health education
• Serious games and immersive environments for biomedical and healthcare applications
• Human–machine interaction and user modeling for adaptive VR/XR healthcare applications
• Applications and Case Studies: implementation and evaluations of XR applications in healthcare
• Integration of AI in XR-based biomedical systems
• Adaptive and personalized XR environments driven by AI models
• Biosignal integration in XR applications (e.g., EEG, EMG, ECG, eye tracking, motion and physiological signals)
• Biofeedback and closed-loop XR systems for clinical and patient-centered use

Ersilia Vallefuoco is a researcher in Biomedical Engineering at the Department of Electrical Engineering and Information Technology of the University of Naples Federico II. Her main areas of expertise include serious games for rehabilitation applications, technologies for inclusion, assistive technologies, and extended reality and simulation in healthcare. In detail, her research focuses on the validation and the use of serious games-based interventions for people with neurodevelopmental disorders and neurodegenerative disorders. She is the author and co-author of several publications, and she was a speaker at national and international conference.

Michela Russo is a post-doc researcher in biomedical engineering at Department of Chemical, Material and Industrial Production Engineering, University of Naples FEDERICO II, Naples, Italy. Her main scientific areas involve biomedical signal processing, artificial intelligence, simulation and extended reality in healthcare. Her currently research is directed toward the gait analysis in extended reality with attention to neurodegenerative diseases. She is the author and co-author of several publications, and she was a speaker at national and international conference.

Vittorio Santoriello is a Ph.D. candidate in Information and Communication Technology for Health at the University of Naples "Federico II", conducting research in collaboration with Reykjavik University. He holds a Master’s Degree in Biomedical Engineering with a specialization in Medical Devices, graduating with top honors (110 cum laude) from the University of Naples "Federico II." His research focuses on the analysis of biosignals for personalized medicine, including heart rate variability (HRV), center of pressure, EEG, and electrodermal activity (EDA). His work is applied in various contexts such as automatic pain assessment, rehabilitation monitoring in Amyotrophic Lateral Sclerosis (ALS) patients, and postural control challenges.