Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

Abstract

In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions. In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured. To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI. As a result, the hybrid BCI (85.54 % ± 8.59) showed significantly higher classification accuracy than those of unimodal EEG (80.77 % ± 11.15) and NIRS BCI (77.12 % ± 7.63) (Wilcoxon signed rank test, Bonferroni corrected p < 0.05). The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.