Volume 11 • Issue 2 • PP: 42 –49 • 2026
Scene-Level Assessment of Comfort, Legibility, and Spatial Control in Virtual Reality Interfaces
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Virtual reality interface quality is not determined by visual appeal alone. A scene may look convincing while still producing unstable gaze, uncomfortable depth switching, excessive head movement, or slow target selection. This paper presents a scene-level assessment framework for measuring comfort, legibility, and spatial control in VR interfaces. The work is deliberately organized as a design-science evaluation rather than as a conventional classifier study: it begins with interface failure mechanisms, defines observable headset and scene variables, computes a Virtual Reality Interface Comfort score, and then translates the results into review actions. The empirical analysis uses a processed feature-level extract aligned with public VR eye-tracking task structures and combines gaze stability, pupil variability, vergence error, head-turn demand, tracking loss, selection latency, contrast balance, target comfort, depth pressure, and spatial-memory support. The results indicate that comfortable VR scenes are characterized by stable fixation, consistent depth placement, strong spatial memory support, and modest interaction latency, while high-risk scenes are mainly associated with head-turn demand, tracking loss, pupil variability, and depth pressure. The paper contributes a transparent measurement model, a set of scene pattern diagnostics, and a practical governance workflow for deciding when a VR interface should be released, revised, or retested.
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