Stress is a widely known phenomenon in all societies. Due to the current COVID-19 pandemic, stress and anxiety issues are becoming more severe for a wide number of people. At the same time, relaxing becomes more challenging, because of working from home and limited activities outside of our homes. Here interactive tools can provide support for relaxation and well-being. Particularly novel interaction techniques such as virtual reality (VR) or body-sensing are promising innovations to increase our health and well-being.
Research indicates positive benefits of immersion in virtual environments for body perception and relaxation. However, a systematic exploration of the design space for communicating bio-feedback and body movement such as the respiratory frequency in virtual environments for relaxation is still missing. In the project Relaxation in VR, we study through deployed systems how VR and body-feedback can support relaxation. We build a functional prototype showcasing the potentials of VR applications for relaxation. This prototype will immersively visualize the user’s respiratory frequency and motivate the user to adapt the respiratory frequency to foster relaxation. In a longitudinal in-the-wild study we will compare our immersive VR application to a non-immersive desktop application to understand the influence of immersion on relaxation. For this study, we invite interested participants to test our new application for several weeks and contribute to our research.
At the end of the research project, we will make the application available as an open-source project and publish our research results.
Academy Assistants: Elena Maan & Timo Lek
Researchers: Miguel Barreda Angeles & Lars Litschke
 Martin Kocur, Valentin Schwind, and Niels Henze. 2019 “Utilizing the Proteus Effect to Improve Interactions using Full-Body Avatars in Virtual Reality.” Mensch und Computer 2019-Workshopband.
 Marieke van Rooij, Adam Lobel, Owen Harris, Niki Smit, and Isabela Granic. 2016. DEEP: A Biofeedback Virtual Reality Game for Children At-risk for Anxiety. In Proc. of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM, USA, 1989–1997. DOI:https://doi.org/10.1145/2851581.2892452