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Dataset · Mendeley Data · July 23, 2026

EEG-XR: A Cross-Reality EEG Dataset for Neuroergonomic Analysis Across Desktop, Virtual, and Mixed Reality

Syed Muhammad Umair Arif, Adai Shomanov, Min-Ho Lee

Adai Shomanov
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Abstract

EEG-XR is a controlled cross-reality electroencephalography dataset collected during a functionally matched visual-attention task presented across Desktop, immersive virtual reality, and optical see-through mixed reality. The dataset was designed to support research on cognitive workload, short-term time-on-task dynamics, visual-fatigue-related activity, repeated-session stability, and EEG signal quality across different display modalities. Seventeen healthy adult participants completed two measurement sessions. In each session, participants performed the same 6 × 6 row-column visual-stimulation task under three presentation conditions: a 24-inch Desktop monitor, an Oculus Quest 2 virtual-reality headset, and a Microsoft HoloLens 2 mixed-reality headset. Each modality included two task blocks using the target strings COMPUTER_SCIENCE and WORLD_UNIVERSITY. The task layout, target structure, stimulation sequence, color configuration, nominal event timing, and participant instructions were maintained across modalities. Continuous EEG was recorded at 500 Hz from 16 channels: F3, Fz, F4, FC1, FC2, C3, Cz, C4, CP1, CP2, P3, Pz, P4, O1, Oz, and O2. The recordings are provided in BrainVision format with synchronized row and column event markers. The dataset contains all 204 expected participant-condition recordings. Of these, 203 are complete, while one Session 1 VR recording for participant S06 contains a documented partial usable interval and is retained with an explicit quality flag. The repository includes anonymized participant folders, continuous EEG recordings, event-marker files, task and condition metadata, participant and recording inventories, channel definitions, recording-quality and eligibility information, file checksums, preprocessing configurations, and data-loading resources. Participants are identified only by codes S01-S17. The dataset supports participant-level regional and temporal EEG analyses, including frontal theta, parietal alpha, occipital alpha, occipital beta, theta-to-alpha measures, beta-to-alpha measures, Early-Middle-Late task phases, task comparisons, modality comparisons, and repeated-session analyses. It provides a reproducible resource for investigating EEG responses across non-immersive, immersive, and mixed-reality display environments.

EEG and Brain-Computer InterfacesVirtual Reality Applications and ImpactsGaze Tracking and Assistive TechnologyEEGvirtual realitymixed reality

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