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| Autori principali: | , , |
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| Natura: | Artículo Open Access |
| Pubblicazione: |
Wiley
2025
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| Soggetti: | |
| Accesso online: | https://onlinelibrary.wiley.com/doi/10.1002/cav.70072 |
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Sommario:
- Human‐Robot Interaction: Integrating BCI ‐Controlled Virtual Robotic Arm With Manual Control in VR Environment Jian Teng Sukyoung Cho Shaw‐mung Lee Computer Animation and Virtual Worlds ABSTRACT This study presents a novel tri‐manual interaction framework that enables users to control two physical hands via VR controllers and a virtual robotic arm through a hybrid brain‐computer interface (32‐channel EEG and eye‐tracking). The virtual robotic arm, implemented as a 6‐DOF industrial manipulator in Unity, is controlled through simplified BCI commands: forward/backward movement along the z‐axis based on motor imagery strength, with automatic grasping triggered by sustained attention thresholds. Twenty‐five participants completed 30 trials, each following a 60‐s protocol with five phases: rest, target presentation, preparation, execution, and feedback. Results demonstrated that the hybrid BCI system achieved superior performance compared to EEG‐only control: 8.5% improvement in task success rate, 34.5% increase in positioning accuracy, and 46.2% reduction in cognitive load. The CNN‐LSTM architecture achieved 86.3% motor imagery classification accuracy. Learning effects were observed within trials, with performance plateauing after 3.8 ± 0.7 attempts. Time‐frequency analysis revealed hierarchical neural coordination mechanisms underlying the tri‐manual control. This research validates the feasibility of augmented manipulation in virtual environments, establishing a foundation for advanced human‐robot collaboration in animation and VR applications. 10.1002/cav.70072 http://onlinelibrary.wiley.com/termsAndConditions#vor