ArticleFrontiers in neurorobotics2025
Tri-manual interaction in hybrid BCI-VR systems: integrating gaze, EEG control for enhanced 3D object manipulation.
Article in Frontiers in neurorobotics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- The Effectiveness of Cognitive Training Using Electroencephalography in Acute Stroke Cases.Journal of clinical medicine · 2026Article
- EEG Feature Extraction and Classification for Upper Limb Flexion and Extension Motor Imagery Based on Discriminative Filter Bank Common Spatial Pattern.Brain sciences · 2026Article
- Physiological sensing systems and AI-based signal analysis in immersive virtual reality learning and training: A scoping review.PloS one · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interface (BCI) integration with virtual reality (VR) has progressed from single-limb control to multi-limb coordination, yet achieving intuitive tri-manual operation remains challenging. This study presents a consumer-grade hybrid BCI-VR framework enabling simultaneous control of two biological hands and a virtual third limb through integration of Tobii eye-tracking, NeuroSky single-channel EEG, and non-haptic controllers. The system employs e-Sense attention thresholds (>80% for 300 ms) to trigger virtual hand activation combined with gaze-driven targeting within 45° visual cones. A soft maximum weighted arbitration algorithm resolves spatiotemporal conflicts between manual and virtual inputs with 92.4% success rate. Experimental validation with eight participants across 160 trials demonstrated 87.5% virtual hand success rate and 41% spatial error reduction (
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