2025/09/09 by Kyle Coutray, Coutray, Kyle, Wanyea Barbel +5
Computer Science · Neuroscience · Psychology · #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Gaze Tracking and Assistive Technology #Human-Automation Interaction and Safety #Human-Computer Interaction (cs.HC)
paper · pdf · doi:10.48550/arxiv.2509.07863
openalex publication_date 2025/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Brain-Computer Interfaces (BCIs) have traditionally been studied in clinical and laboratory contexts, but the rise of consumer-grade devices now allows exploration of their use in daily activities. Virtual reality (VR) provides a particularly relevant domain, where existing input methods often force trade-offs between speed, accuracy, and physical effort. This study introduces NeuroGaze, a hybrid interface combining electroencephalography (EEG) with eye tracking to enable hands-free interaction in immersive VR. Twenty participants completed a 360° cube-selection task using three different input methods: VR controllers, gaze combined with a pinch gesture, and NeuroGaze. Performance was measured by task completion time and error rate, while workload was evaluated using the NASA Task Load Index (NASA-TLX). NeuroGaze successfully supported target selection with off-the-shelf hardware, producing fewer errors than the alternative methods but requiring longer completion times, reflecting a classic speed-accuracy tradeoff. Workload analysis indicated reduced physical demand for NeuroGaze compared to controllers, though overall ratings and user preferences were mixed. These findings demonstrate the feasibility of hybrid EEG+gaze systems for everyday VR use, highlighting their ergonomic benefits and inclusivity potential. Although not yet competitive in speed, NeuroGaze points toward a practical role for consumer-grade BCIs in accessibility and long-duration applications, and underscores the need for improved EEG signal processing and adaptive multimodal integration to enhance future performance.