A Hybrid Brain-Computer Interface Based on Visual Evoked Potential and Pupillary Response.

ABSTRACT: Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) has been widely studied due to the high information transfer rate (ITR), little user training, and wide subject applicability. However, there are also disadvantages such as visual discomfort and "BCI illiteracy." To address these problems, this study proposes to use low-frequency stimulations (12 classes, 0.8-2.12 Hz with an interval of 0.12 Hz), which can simultaneously elicit visual evoked potential (VEP) and pupillary response (PR) to construct a hybrid BCI (h-BCI) system. Classification accuracy was calculated using supervised and unsupervised methods, respectively, and the hybrid accuracy was obtained using a decision fusion method to combine the information of VEP and PR. Online experimental results

SUBMITTER: Jiang L 

PROVIDER: S-EPMC8850273 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature