Cristian Barruè

Teresa Scantamburlo, Atia Cortés, Francesca Foffano et al.

This paper presents the results of an extensive study investigating the opinions on Artificial Intelligence (AI) of a sample of 4,006 European citizens from eight distinct countries (France, Germany, Italy, Netherlands, Poland, Romania, Spain, and Sweden). The aim of the study is to gain a better understanding of people's views and perceptions within the European context, which is already marked by important policy actions and regulatory processes. To survey the perceptions of the citizens of Europe we design and validate a new questionnaire (PAICE) structured around three dimensions: people's awareness, attitude, and trust. We observe that while awareness is characterized by a low level of self-assessed competency, the attitude toward AI is very positive for more than half of the population. Reflecting upon the collected results, we highlight implicit contradictions and identify trends that may interfere with the creation of an ecosystem of trust and the development of inclusive AI policies. The introduction of rules that ensure legal and ethical standards, along with the activity of high-level educational entities, and the promotion of AI literacy are identified as key factors in supporting a trustworthy AI ecosystem. We make some recommendations for AI governance focused on the European context and conclude with suggestions for future work.

Aniol Civit, Antonio Andriella, Alba Martínez et al.

Frailty assessments are crucial to evaluate the risk of adverse events and the health and social care needs of older adults, yet their administration remains resource-intensive and typically relies on coarse clinical outcomes, such as task completion times, which may overlook biomechanical indicators of functional decline. To address this, we present a robotic framework that guides older adults through standardised frailty and fall-risk tests while capturing clinical scores and additional frailty-related metrics, offering a deeper insight into a user's condition. The system uses a Behaviour Tree architecture that coordinates perception, decision-making, interaction, and measurement modules. Using vision-based skeleton tracking, the robot evaluates established clinical tests, including the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG). The framework was co-designed with healthcare professionals and evaluated in situ during six months in a rehabilitation centre's research lab with N=81 older adults. Robot-derived measurements were compared against therapist assessments and clinical reference instruments, including a gait analysis walkway and an inertial measurement unit (IMU). Results showed excellent agreement for most test completion times and gait-related parameters ($ICC > 0.9$). And, substantial agreement for the overall SPPB score comparing the robot and the therapist ($k = 0.67$) and moderate agreement comparing the robot and the IMU ($k=0.55$). The findings highlight that social robots can provide reliable and objective frailty assessments in healthcare settings while enabling the collection of relevant mobility indicators beyond conventional outcomes.