A Tri-Hybrid Brain-Computer Interface for Neuro-Information Systems

Brain-computer interfaces (BCIs) are computerized systems that convert brain activity into control commands to operate software or external devices. Though promising, BCIs currently have limited practicality and usership due to poor signal classification and large training data requirements. The present study aims to overcome both challenges by combining three brain signals. This paradigm could improve existing BCI technical efficacy, and extrapolate to applications where hands-free visual interfaces could equip users with communication and information resources that improve work processes.