TY - GEN
T1 - Brain-Metaverse Interaction for Anxiety Regulation
AU - Jin, Nanlin
AU - Wu, Ye
AU - Park, Jeongyeong
AU - Qin, Zihui
AU - Liang, Hai Ning
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Metaverse has become a powerful tool for conducting research in many domains, including education, social science, and healthcare. It mixes the virtual and physical environments and can produce various stimuli for users to experience and be immersed in the virtual-real environment. However, at present, these stimuli are preset and immobile, not responding to the user's changing requirements. In addition, it lacks studies on how brain signals might suggest the demand or preference for specific VR content and if/how VR can interact with users' brains directly, hands-free, and without verbal instructions. As metaverse's natural association with learning and brain activities, receiving signals directly from the user's brain will offer a firm edge to explore mental health issues. This research proposes a new framework, namely Brain-Metaverse Interaction (BMI), which enables the direct interaction between users' brain signals and the adaptation of VR content in an iterative and evolving manner. Our experiment based on this framework shows promising results, although suffering from the typical limitations of hardware devices and data acquisition, such as signal noise of EEG data and sensitivity and latency of the EEG device.
AB - Metaverse has become a powerful tool for conducting research in many domains, including education, social science, and healthcare. It mixes the virtual and physical environments and can produce various stimuli for users to experience and be immersed in the virtual-real environment. However, at present, these stimuli are preset and immobile, not responding to the user's changing requirements. In addition, it lacks studies on how brain signals might suggest the demand or preference for specific VR content and if/how VR can interact with users' brains directly, hands-free, and without verbal instructions. As metaverse's natural association with learning and brain activities, receiving signals directly from the user's brain will offer a firm edge to explore mental health issues. This research proposes a new framework, namely Brain-Metaverse Interaction (BMI), which enables the direct interaction between users' brain signals and the adaptation of VR content in an iterative and evolving manner. Our experiment based on this framework shows promising results, although suffering from the typical limitations of hardware devices and data acquisition, such as signal noise of EEG data and sensitivity and latency of the EEG device.
KW - AI-adapted Content
KW - Brain-Metaverse Interaction
KW - EEG
KW - Metaverse
UR - http://www.scopus.com/inward/record.url?scp=85166379208&partnerID=8YFLogxK
U2 - 10.1109/ICVR57957.2023.10169785
DO - 10.1109/ICVR57957.2023.10169785
M3 - Conference Proceeding
AN - SCOPUS:85166379208
T3 - 2023 9th International Conference on Virtual Reality, ICVR 2023
SP - 385
EP - 392
BT - 2023 9th International Conference on Virtual Reality, ICVR 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Virtual Reality, ICVR 2023
Y2 - 12 May 2023 through 14 May 2023
ER -