4 Contributo in Atti di Convegno (Proceeding)

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Enhancing Adaptive Robotic Coaches with Multimodal Workload Estimation

Social robots are increasingly being explored as interactive coaches capable of delivering personalized physical and cognitive training sessions. Improving their effectiveness entails personalized interventions through adaptive robotic systems with continuous workload quantification. This study presents a workload estimation methodology based on physiological and kinematic monitoring, designed for integration into a social robotic coach. Physical, mental, and dual-task activities were adminis...

Parameterized Models of Double-D Coils for DWPT Applications Through Deep Learning Techniques

Double-D (DD)-coils are essential components in dynamic wireless power transfer (DWPT) systems as they are bipolar in character, allowing a smooth flux passage through them. This paper presents a deep-learning model that helps predict the coils' mutual inductance, the coupling coefficient with and without lateral and angular offsets, and other design parameters. It is shown that the proposed deep-learning models work orders of magnitudes of times faster than conventional numerical software.

Eye-tracking metrics as a new tool to assess patient’s adherence to robot-assisted gait training*

The growing use of robotic rehabilitation in clinical practice has changed the dyadic interaction between physiotherapist and patient, introducing novel elements such as performance-based feedback (FB). The latter has a strong impact on patients' motivation, participation and error-driver learning, which are crucial aspects to consider in order to optimize the rehabilitation session to achieve successful outcomes. In addition, the presence of FB has a relevant contribution in promoting the ac...

A Novel Real-World Dataset of Italian Clinical Notes for NLP-based Decision Support in Low Back Pain Treatment

Low back pain represents a leading source of disability worldwide and poses a significant challenge for evidence-based clinical decision support. In contexts where Italian-language resources for diversified therapeutic pathways are lacking, we have assembled a novel, annotated dataset comprising up to three pre-treatment documents per patient (MRI report, X-ray report, and patient visit notes), alongside demographic information (age and sex). The cohort consists of 176 patient records, strati...

Doctor, Is That You? Evaluating Large Language Models on Italy’s Medical School Entrance Exams

In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a variety of linguistic and cognitive tasks. This study investigates whether such models can succeed in one of Europe’s most selective academic assessments: the Italian medical school entrance exam. We evaluate a wide selection of open-weights LLMs, ranging from natively Italian-pretrained models to multilingual and Italian-specialised variants, on a benchmark dataset comprising over 3,300 real-worl...

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