NeuroGaze: a hybrid EEG and eye-tracking brain-computer interface for hands-free interaction in virtual reality

Area of Science:

• Human-Computer Interaction
• Neuroscience
• Virtual Reality

Background:

• Consumer-grade Brain-Computer Interfaces (BCIs) enable real-world applications beyond clinical settings.
• Virtual Reality (VR) presents challenges for existing input methods, balancing speed, accuracy, and effort.
• Hybrid interfaces combining multiple input modalities can enhance VR interaction.

Purpose of the Study:

• To introduce and evaluate NeuroGaze, a novel hybrid BCI integrating electroencephalography (EEG) and eye tracking for hands-free VR interaction.
• To assess the performance (task completion time, error rate) and workload (NASA-TLX) of NeuroGaze compared to traditional VR controllers and gaze-pinch gestures.
• To explore the feasibility of consumer-grade BCIs for immersive VR environments and identify speed-accuracy-accessibility trade-offs.

Main Methods:

• Developed NeuroGaze, a hybrid interface combining EEG and eye tracking for VR.
• Recruited 20 participants for a 360° cube-selection task in VR.
• Compared NeuroGaze against VR controllers and gaze-pinch gestures, measuring task completion time, error rates, and NASA-TLX workload scores.

Main Results:

• NeuroGaze demonstrated fewer errors in target selection compared to alternative methods.
• NeuroGaze exhibited longer task completion times, indicating a speed-accuracy trade-off.
• Workload analysis revealed reduced physical demand with NeuroGaze, though overall user preference was mixed.

Conclusions:

• NeuroGaze is a feasible hybrid BCI for hands-free VR interaction using off-the-shelf hardware.
• Consumer-grade BCIs show promise for long-duration VR use, despite current limitations in speed and mixed user feedback.
• Future improvements in EEG signal processing and multimodal integration are crucial for optimizing BCI performance in VR.