Collection

Embodied Agents for Wellbeing

Submission status
Closed
The current COVID-19 pandemic has led to societal changes (such as social isolation and work-from-home arrangements) that have severely impacted the mental wellbeing of the worldwide population, causing depressive and anxiety symptoms. This has resulted in a greater interest in technology-based interventions to support people and promote their mental wellbeing. Embodied agents (e.g., virtual agents, robots) are finding their way into helping to improve people’s wellbeing and are currently being designed and evaluated for various applications, such as, among others, therapeutic interventions, and medical treatments. Making an embodied agent suitable to promote wellbeing is still an open challenge. Indeed, embodied agents need to engage in social interactions with humans by communicating, cooperating, and making decisions, as well as take into account humans' social cues to convey more natural and smoother interactions. Those agents also need to analyse, understand and appropriately respond and adapt to human behaviour and affective states to connect with humans empathically using nonverbal cues - e.g., facial expressions, posture - that support and add meaning to their verbal communication. However, due to the lack of publicly available large scale datasets obtained over longer periods of time, embodied agents are very limited in their capabilities to address those challenges. This often increases the risk of user disappointment and dissatisfaction, which are key factors for a successful wellbeing intervention. Within this context, the fields of psychology, social signal processing, affective computing, and human-agent interaction require continuous collaboration. This research topic aims to promote such cross-disciplinary cooperation by bringing together the most recent findings from a variety of research groups working in these areas. The topics of interest include but are not limited to: ● Embodied agent design for wellbeing ● Socially assistive robots for wellbeing ● Affective robotics and virtual agents for wellbeing ● Affective cognitive architectures ● User studies for wellbeing (both in lab and field) ● Adaptation and personalization for wellbeing applications ● Machine learning for wellbeing ● Concept papers on embodied agents for wellbeing ● Methods to measure wellbeing ● Ethics, privacy, data security and responsible innovation considerations ● Modelling users and user behaviours in wellbeing interventions ● Modelling robot behaviours to promote wellbeing ● Methodological challenges for achieving successful wellbeing interventions via human-agent interaction (HAI) ● Metrics for evaluating wellbeing and agent intervention outcomes

Editors

  • Micol Spitale Micol Spitale , 

    Micol Spitale

    Micol Spitale is currently a PostDoc at the Affective IntelligenceMicol & Robotics Laboratory (AFAR Lab), Department of Computer Science & Technology of the University of Cambridge, under the supervision of professor Hatice Gunes. Her research focuses on developing a Socio-emotionally Adaptive Robotic (ARoEQ) platform that can foster wellbeing through coaching and psychologically-proven interventions. She has just finalised her Ph.D. (end of October 2021) in Information Technology (Computer Science and Engineering Area) affiliated with IBM Italy and co-funded by EIT Digital.

  • Katie Winkle Katie Winkle , 

    Katie Winkle

    Katie Winkle is an Assistant Professor at the Department ofKatie Information Technology, Uppsala University, where she is developing new lines of research around trustworthy Human Robot Interaction (and what that means) at the Social Robotics Lab. Her research interests cover the design, development, evaluation and application of socially assistive robotics, with a focus on human-in-the-loop design/development and mutual shaping approaches which recognise the two-way interaction between robots and society.

  • Emilia I. Barakova Emilia I. Barakova  &

    Emilia I. Barakova

    Emilia I. Barakova received a Ph.D. degree in mathematics andEmilia physics from Groningen University, Groningen, The Netherlands, in 1999 and holds a Master’s degree from the Technical University of Sofia, Bulgaria. She is currently with the Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands, and leads the Social Robotics Lab of the Eindhoven University of Technology. She has held research positions at RIKEN Brain Science Institute (Japan), GMD-Japan Research Laboratory (Japan), Groningen University (The Netherlands), and the Bulgarian Academy of Science (Bulgaria).

  • Hatice Gunes Hatice Gunes

    Hatice Gunes

    Hatice Gunes is a Professor of Affective Intelligence andHatice Robotics (AFAR) and the Head of the AFAR Lab at the University of Cambridge's Department of Computer Science and Technology. Her expertise is in the areas of affective computing and social signal processing cross-fertilising research in multimodal interaction, computer vision, signal processing, machine learning and social robotics. She has published over 125 papers in these areas (H-index=34, citations > 6,500), with most recent works on lifelong learning for facial expression recognition, fairness and affective robotics; and longitudinal HRI for wellbeing.

Articles (10 in this collection)