Abstract
AbstractImplementing higher speed and larger command sets for brain-computer interfaces (BCIs) has always been the pursuit of researchers, which is helpful to realize the technological applications. The hybrid BCIs jointly induce different electroencephalogram (EEG) signals and could improve system performance effectively. This study designed an online BCI with 120 commands and high-speed by hybrid P300 and steady-state visual evoked potential (SSVEP) features. A time-frequency-phase encoding strategy was used to encode 120 commands in a short time, this strategy used time-locked P300s and frequency and phase-locked SSVEPs with a wide frequency band. The step-wise linear discriminant analysis (SWLDA) and ensemble task-related component analysis (eTRCA) were severally used to decode P300s and SSVEPs. As a result, online average spelling ac-curacy across six subjects was 83.89%. Average and highest information transfer rate (ITR) for this system was 151.53 bits/min and 175.09 bits/min, respectively. Meanwhile, the shortest time for out-putting one command was only 1.45 s. These results demonstrate the feasibility and effectiveness of this high-speed BCI with 120 commands, furthermore, this study used a wider frequency band of SSVEPs to encode 120 commands, which is helpful to extend larger command sets and achieve higher system performance.KeywordsBrain-computer interface (BCI)Hybrid BCIP300Steady-state visual evoked potential (SSVEP)High-speedLarge command sets
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.