University of Maryland Researchers Track Brain Waves to Predict Cybersickness in Real Time
Our results show that EEG could complement traditional symptom questionnaires and support VR and AR systems that respond to cybersickness in real time,
said Mattie Johnson, a computer science Ph.D. student at the University of Maryland, as reported by News-Medical. A new study published on September 25, 2026, in the journal Virtual Reality details how scientists used electroencephalography to track brain wave activity during immersive digital experiences. The findings offer objective measurements to help virtual reality and augmented reality platforms detect and mitigate motion sickness symptoms as they happen.
Vergence-Accommodation Conflict Triggers Virtual Discomfort
Cybersickness causes nausea, dizziness, sweating, blurred vision, and disorientation during immersive digital tasks. The new study, led by University of Maryland Computer Science Professor and Dean Amitabh Varshney in collaboration with the Food and Drug Administration and Sony Group Corporation, focused specifically on the vergence-accommodation conflict. This mismatch occurs when the eyes converge on a virtual object appearing near or far while simultaneously focusing on a display set at a fixed focal plane. Previous research shows that 65.2% of virtual reality users experience cybersickness, with 23.9% reporting severe symptoms.
Electroencephalography Replaces 1993 Questionnaires for Continuous Monitoring
Researchers traditionally measure symptoms using the Simulator Sickness Questionnaire, a 16-question survey developed in 1993 for U.S. military flight simulator pilots. Sujal Bista, director of the Immersive Visualization Center at the University of Maryland Institute for Health Computing, noted that the survey is subjective and fails to provide continuous data collection during exposure. To overcome this limitation, the team recorded brain activity from 40 participants wearing a Meta Quest 2 headset using a 64-electrode electroencephalography system.
Frontal and Occipital Lobe Brain Waves Shift During Onset
The recordings revealed statistically significant changes across several brain wave frequency bands when participants experienced digital motion sickness. Johnson explained that the frontal lobe showed a decrease in high brain wave frequencies, while the occipital lobe showed a decrease in low brain wave frequencies. These distinct patterns in brain wave clusters serve as reliable predictors of an incoming cybersickness episode.
Future Headsets Adjust Focal Planes to Mitigate Symptoms
The research team ultimately aims to connect electroencephalography monitoring devices directly with headsets to adjust virtual scenes automatically when symptoms emerge. By bringing displayed content closer to the focal plane, future hardware could reduce the vergence-accommodation mismatch in real time. Investigators also plan to incorporate eye-tracking data to build a comprehensive cybersickness index that combines multiple physiological measures.
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