This study examines seniors’ creative engagement in group activities using synchronous communication tools and explores automatic assessment methods through behavioral and psychophysiological measurements. Working with a small senior group on collaborative creative tasks, we implemented a comprehensive data collection approach using audio-visual and physiological measurements. Machine learning models were used to evaluate group creative engagement levels using various data subsets. Results show that engagement assessment can be effective with different feature combinations, allowing flexibility across contexts and constraints. The multimodal approach, combining facial, audio, and body analysis, achieved optimal performance and is recommended when conditions permit. Our research provides insights into seniors’ online creative participation and presents an automated system for detecting creative engagement in virtual teams, supporting active participation strategies.

Recent years have seen a growing research interest towards designing computer-assisted health interventions aiming to improve mental health services. Digital technologies are becoming common methods for diagnosis, therapy, and training. With the advent of lower-cost VR head-mounted-displays (HMDs) and high internet data transfer capacity, there is a new opportunity for applying immersive VR tools to augment existing interventions. This study is among the first to explore the use of a Multi-User Virtual Reality (MUVR) system as a therapeutic medium for participants at high-risk for developing Eating Disorders. This paper demonstrates the positive effect of using MUVR remote psychotherapy to enhance traditional therapeutic practices. The study capitalises on the opportunities which are offered by a MUVR remote psychotherapeutic session to enhance the outcome of Acceptance and Commitment Therapy, Play Therapy and Exposure Therapy for sufferers with body shape and weight concerns. Moreover, the study presents the design opportunities and challenges of such technology, while strengths on the feasibility, and the positive user acceptability of introducing MUVR to facilitate remote psychotherapy. Finally, the appeal of using VR for remote psychotherapy and its observed positive impact on both therapists and participants is discussed.

Here, we introduce the design and preliminary validation of a general-purpose architecture for affective-driven procedural content generation in virtual reality (VR) applications in mental health and wellbeing. The architecture supports seven commercial physiological sensing technologies and can be deployed in immersive and non-immersive VR systems. To demonstrate the concept, we developed the "The Emotional Labyrinth," a non-linear scenario in which navigation in a procedurally generated three-dimensional maze is entirely decided by the user, and whose features are dynamically adapted according to a set of emotional states. During navigation, affective states are dynamically represented through pictures, music, and animated visual metaphors chosen to represent and induce affective states. The underlying hypothesis is that exposing users to multimodal representations of their affective states can create a feedback loop that supports emotional self-awareness and fosters more effective emotional regulation strategies. We carried out a first study to, first, assess the effectiveness of the selected metaphors in inducing target emotions, and second, identify relevant psycho-physiological markers of the emotional experience generated by the labyrinth. Results show that the Emotional Labyrinth is overall a pleasant experience in which the proposed procedural content generation can induce distinctive psycho-physiological patterns, generally coherent with the meaning of the metaphors used in the labyrinth design. Furthermore, collected psycho-physiological responses such as electrocardiography, respiration, electrodermal activity, and electromyography are used to generate computational models of users' reported experience. These models enable the future implementation of the closed loop mechanism to adapt the Labyrinth procedurally to the users' affective state.

This paper reports the design and assessment of a neuro-fuzzy model to support clinicians during virtual reality therapy. The implemented model is able to automatically recognize the perceived stress levels of the patients by analyzing physiological and behavioral data during treatment. The model, consisting of a self-organizing map and a fuzzy-rule-based module, was trained unobtrusively recording electrocardiogram, breath rate and activity during stress inoculation provided by the exposure to virtual environments. Twenty nurses were exposed to sessions simulating typical stressful situations experienced at their workplace. Four levels of stress severity were evaluated for each subject by gold standard clinical scales administered by trained personnel. The model's performances were discussed and compared with the main machine learning algorithms. The neuro-fuzzy model shows better performances in terms of stress level classification with 83% of mean recognition rate. RESEARCH HIGHLIGHTS Stress levels were predicted on the basis of physiological computing using a neuro-fuzzy model during virtual reality therapy. Features were extracted from ECG and respiration obtaining high accuracy and optimization of computational costs. The neuro-fuzzy model shows better performance than the more frequently adopted classifiers. This approach may enhance the use of physiological computing for stress treatment in clinical practice.

In this paper we describe the results of a controlled study of a social game, Magpies, which was built on the Facebook Online Social Network (OSN) and enhanced with contextual social information in the form of a variety of social network indices. Through comparison with a concurrent control trial using an identical game without the enhanced social information, it was shown that the additional contextual data increased the frequency of social activity between players engaged in the game. Despite this increase in activity, there was little increase in growth of the player-base when compared to the control condition. These findings corroborate previous work that showed how socio-contextual enhancement can increase performance on task-driven games, whilst also suggesting that it can increase activity and engagement when provided as context for non task-driven game environments.

Stress and its related comorbid diseases are responsible for a large proportion of disability worldwide. In particular, chronic stress is the main responsible for the dramatic increase of premature mortality in the Western countries. However, advanced simulation and sensing technologies, such as virtual reality and mobile biosensors offer interesting opportunities for innovative personal health-care solutions to stress. In this work, we describe a technology-based approach to the assessment and treatment of stress that is based on the vision of Interreality. The main feature of interreality is the creation of a hybrid-augmented experience merging the physical and virtual world. This is achieved through: a) an extended sense of presence: in interreality advanced simulations (3-D virtual worlds) are used to transform health guidelines and provisions into experience; b) an extended sense of community (social presence): interreality uses hybrid social interaction and dynamics of group sessions to provide each user with targeted social support in both the physical and virtual world; c) real-time feedback between the physical and virtual worlds: interreality uses bio and activity sensors and devices (e.g. smartphones) to track both the behavior and the health status of the user in real time and to provide targeted suggestions and guidelines. The feedback activity is twofold: (1) behavior in physical world influences the experience in the virtual one, and (2) behavior in the virtual world influences the experience in the real one.