Introduction
Within the framework of the IDUNN project, we are excited to present this latest research article titled “Exploring the Potential of EEG for Real-Time Interactions in Immersive Virtual Reality”. This study is a collaborative effort involving researchers from the University of Oulu and the University of West Attica.
Research Team
- Mikko Korkiakoski, Oskari Rajala, Mikael Sarkiniemi, Markus Hirsimaki, Jere Kinnunen, Paula Alavesa, Panos Kostakos (Center for Ubiquitous Computing, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland), Theodoros Anagnostopoulos (DigiT.DSS.Lab, Department of Business Administration, University of West Attica, Greece)
Abstract
Brain-computer interfaces (BCIs) leverage non-invasive electroencephalogram (EEG) data to convert brain signals into binary code, which can be used to control devices like a mouse cursor. Recent advancements in wearable and immersive technologies have enabled the integration of EEG with virtual reality (VR) headsets, paving the way for new user studies that aim to enhance our understanding of various VR design challenges such as cybersickness and locomotion.
Study Overview
The primary challenge in merging EEG-based BCIs with VR environments lies in developing communication architectures that ensure robust, reliable, and lossless data transmission. Additionally, user comfort and near real-time interactivity pose further obstacles. Our research involved two experiments utilizing a consumer-grade EEG headband (Muse2) to evaluate the feasibility of EEG-based BCIs in virtual environments.
Experiments Conducted
- Pilot Experiment: This initial experiment involved a simple task of object re-scaling within the VR space using focus values derived from the user’s EEG.
- Study Experiment: In this follow-up experiment, participants were divided into control and experimental groups, each performing tasks related to telekinesis and teleportation.
Findings
Our user research indicates that EEG is a viable method for real-time interactions in non-serious applications, such as games. We found that calculating the mean EEG values in a simplified manner is sufficient for these purposes. The findings also offer insights for improving the design of user research studies that employ similar EEG-based BCIs in VR environments.
Conclusion
This research contributes to the growing field of BCIs and their application in immersive VR environments. By addressing the challenges and demonstrating the feasibility of EEG-based interactions, we hope to inspire further innovation and research in this area.
For more detailed information, please refer to the full article published in the framework of the IDUNN project.