Toward the Automatic Detection of Vection in Virtual Reality Using EEG.

Area of Science:

• Neuroscience
• Human-Computer Interaction
• Virtual Reality

Background:

• Vection, the illusion of self-motion, is crucial for virtual reality (VR) user experience, influencing presence and cybersickness.
• Current subjective questionnaires for measuring vection have limitations, hindering real-time VR system adaptation.
• Real-time vection detection could enhance VR comfort and mitigate negative effects like cybersickness.

Purpose of the Study:

• To investigate electroencephalographic (EEG) markers of vection using evoked potentials.
• To establish a neurophysiological basis for real-time vection detection in VR environments.
• To understand the neural mechanisms underlying vection and its relation to visual-vestibular integration.

Main Methods:

• A VR experiment was conducted with 30 participants experiencing induced vection (forward/backward acceleration).
• Electroencephalographic (EEG) signals were recorded during vection induction.
• Subjective reports on vection perception were collected alongside EEG data.

Main Results:

• A distinct evoked potential, characterized by a positive peak around 600 ms (P600) in the parietal region, was identified as a vection marker.
• A simultaneous negative peak in the frontal region was observed.
• These EEG patterns correlated with subjective reports of vection.

Conclusions:

• The study identified specific EEG evoked potentials (P600) indicative of vection.
• This finding supports the potential for automatic, real-time vection detection using EEG.
• This research advances understanding of vection, visual-vestibular integration, and offers a pathway to improve VR user experience.