Massimo Bergamasco’s research while affiliated with Scuola Normale Superiore and other places

Virtual reality (VR) is increasingly employed in archaeology to showcase reconstructions of ancient sites to the general public, yet its utilization for professional purposes by archaeologists remains less common. To address this gap, we introduce a VR application specifically designed to streamline the storage and access of critical data for archaeological studies. This application provides experts with an immersive visualization of excavation sites and related information during the postexcavation analysis phase. The application interface facilitates direct interaction with 3-D models generated through photogrammetry and modeling techniques, enabling detailed examination of collected data and enhancing research activities. We applied this system to the case study of excavations at the Temple of Juno in Agrigento, Italy. In addition, we present the findings of a pilot user study involving archaeologists, which evaluates the effectiveness of immersive technologies for professionals in documenting, preserving, and exploring archaeological sites, while also driving potential future developments.

Attachment is one of the foundational themes in the history of the psychological development of human beings. For this reason, we assume that it must be approached by taking into account multiple scientific perspectives. The present review aims at analyzing the state of the art regarding the genetic, neurobiological and cognitive mechanisms underlying the development of attachment bonding, considering the child as the frame of reference. We hypothesize that attachment may be present in prototypical forms even in the prenatal period, thus our analysis has a temporal origin in the intrauterine period preceding birth. The intrauterine period is assumed to be a period of maximum sensitivity to stimuli and in particular to those coming from a potential primary caregiver: the biological mother. We conclude with a reframing of the state of the art and propose that future research work would benefit from a superordinate model of attachment, capable of containing and regulating all its components and variables.

Background An app providing material for education and entertaining is a possible way to support patients and healthcare providers in achieving person-centered care. Methods An app tailored on the Fondazione Toscana Gabriele Monasterio (FTGM), a research hospital treating cardiac and lung disorders, was created. A pilot evaluation project was conducted on consecutive patients hospitalized for heart or lung disorders. Patients were asked to complete an assessment questionnaire. Results The FTGM app provides information on diagnostic and therapeutic investigations, hospital and healthcare personnel, and includes content for entertainment and learning. It was tested on 215 consecutive patients (75% men, 66% aged >60 years, and 40% with a primary or middle school degree). Sixty-nine percentage of patients used the FTGM app, including 67% of patients aged >80 years and 65% of those with an elementary education (65%). Patients gave positive feedback on the app layout. Many (76%) looked for information on doctors and nurses in the ‘People’ section. Sixty-five percent of responders had used at least one of the sections called ‘Music’ and ‘Museum visits’. The app helped many patients perceive the hospital as a more liveable place (68%), and to feel less anxious (76%), and more engaged in the diagnostic and therapeutic workup (65%). Overall, the majority of responders (87%) rated the app as ‘excellent’ or ‘good’, and almost all (95%) would have recommended other patients to use the app. Conclusions The FTGM app is a possible tool to improve patient wellbeing during hospitalization.

Despite the automatization of many industrial and logistics processes, human workers are still often involved in the manual handling of loads. These activities lead to many work-related disorders that reduce the quality of life and the productivity of aged workers. A biomechanical analysis of such activities is the basis for a detailed estimation of the biomechanical overload, thus enabling focused prevention actions. Thanks to wearable sensor networks, it is now possible to analyze human biomechanics by an inverse dynamics approach in ecological conditions. The purposes of this study are the conceptualization, formulation, and implementation of a deep learning-assisted fully wearable sensor system for an online evaluation of the biomechanical effort that an operator exerts during a manual material handling task. In this paper, we show a novel, computationally efficient algorithm, implemented in ROS, to analyze the biomechanics of the human musculoskeletal systems by an inverse dynamics approach. We also propose a method for estimating the load and its distribution, relying on an egocentric camera and deep learning-based object recognition. This method is suitable for objects of known weight, as is often the case in logistics. Kinematic data, along with foot contact information, are provided by a fully wearable sensor network composed of inertial measurement units. The results show good accuracy and robustness of the system for object detection and grasp recognition, thus providing reliable load estimation for a high-impact field such as logistics. The outcome of the biomechanical analysis is consistent with the literature. However, improvements in gait segmentation are necessary to reduce discontinuities in the estimated lower limb articular wrenches.

Urban Search And Rescue (USAR) personnel need to be appropriately trained to effectively operate in post-disaster conditions, as they need to quickly identify locations where the presence of survivors is more likely. Currently, the training procedure for this kind of triage is based on showing static pictures presenting different types of building collapses accompanied by cards providing additional environmental information. This article presents VRescue, a simulator for training USAR operators using the paradigm of immersive virtual reality (VR). VRescue recreates a range of operation conditions (day/night, presence of people, dangerous locations, etc.) experienced by real rescuers, and enables learning the use of the equipment commonly used in such scenarios.

Starting from the Attachment theory as proposed by John Bowlby in 1969, and from the scientific literature about developmental processes that take place early in life of human beings, the present work aims at exploring a possible approach to attachment, exploiting some aspects deriving from the Active Inference Theory. We describe how, from the prenatal stage until around the second year of life, the sensory, relational, affective and emotional dynamics could interplay in the formation of priors that get rigidly integrated into the internal generative model and that possibly affect the entire life of the individual. It is concluded that the presented qualitative approach could be of interest for experimental studies aiming at giving evidence on how Active Inference could sustain attachment.KeywordsAttachment theoryActive inferenceInternal working modelsMindPerception

The article presents an immersive multisensory simulator developed in a project co-financed by INAIL (the Italian Workers' Compensation Authority) as part of a collaborative research program for the application of innovative technologies and systems to the management of health and safety at work. Specifically, the program provides for the development of simulators for the structuring of skills qualification paths for operators in charge of running and maintaining the most dangerous work equipment. The simulator we present reproduces all the aspects that contribute to a complete driving experience of the simulated machine in an artificial working environment that replicates typical and atypical operations and hazards involved in the use of self-propelled mobile elevating work platforms (MEWPs) with an extendable articulated boom. The simulator has been designed following the analysis of the most critical working routines with aerial work platforms and using physical components of a real MEWP combined with immersive Virtual Reality technologies. The use of Extended Reality technologies to simulate challenging work scenarios makes it possible to train operators by confronting them with very risky situations without any real danger, both in terms of damage to machinery, and above all in terms of user’s safety. The presented simulation system has been designed as a high-TRL prototype to demonstrate the feasibility of developing training programs in the context of occupational safety and health, based on a mixed-reality simulator targeting MEWP operators and verifiers.

Aims: we developed a massive online open course (MOOC) through co-creation between medical students and academic staff on heart semeiotics and evaluated its teaching efficiency and user satisfaction. Methods: "The Heart, Its Signs and Symptoms" was a MOOC aimed to teach medical students to collect clinical history and perform physical examination of patients presenting with chest pain, dyspnea, palpitations, or syncope. It consisted of 4 interactive cases with preliminary, interim and final evaluation tests. A group of medical students, with the supervision of a multidisciplinary team of University professors residents, health management and informatics researchers developed the MOOC. Results: Users (n = 701) registered to the online platform over 1 month. Students from 34 of the 40 Italian medical faculties participated. 96% of those who started the online course completed at least one of the 4 modules. Among users completing both the preliminary test and the final exam (n = 239, 34% of those registered to the online platform), the percentage of subjects passing the evaluation test raised s from 74% to 95% after the course. Younger age, attendance of Universities in Southern Italy, and a lower number of correct answers during the pre-test predicted a greater increase in the number of correct answers; Almost all participants who provided a feedback (n = 238) felt satisfied by the course. Conclusions: Partnership of medical students and academic staff was a key asset for the success of the initiative. The high rate of involvement and positive feedback from learners suggest a still unmet need for online learning resources.

Mindfulness meditation usually takes place as personal, introspective activity. It is not known if this practice activates the brain differently when done alone or with someone else. Sixteen couples of expert meditators performed mindfulness-oriented meditation (MOM) and instructed mind-wandering (IMW) tasks in two conditions: once sitting in the same room (SR) and once in two different rooms (DR). Spontaneous electroencephalographic (EEG) data was collected during 7-minute recording sessions in the four experimental settings (MOM/SR, MOM/DR, IMW/SR, IMW/DR). Power in band was computed in separate clusters of independent components of the EEG signals. In addition to significant task effects, found in frontolimbic (MOM > IMW in gamma) and frontoparietal locations (MOM < IMW in theta), significant condition effects were found in frontal (SR > DR in delta) and in temporo-occipital regions (SR > DR in theta and alpha). Moreover, a significant interaction between task and condition revealed higher gamma activity in limbic areas during MOM/SR vs. MOM/DR settings. This effect was not attributable to gender, age nor the meditation expertise of participants. We thus show that the brains of two people work differently when they are doing something together or alone; some of these differences are specific to mindfulness meditation. Implications for devotional and clinical settings are discussed.