Eyes-closed hybrid brain-computer interface employing frontal brain activation

Brain-computer interfaces (BCIs) have
been studied extensively in order to establish a non-muscular communication channel
mainly for patients with impaired motor functions. However, many limitations
remain for BCIs in clinical use. In this study, we
propose a hybrid BCI that is based on only frontal brain areas and can be
operated in an eyes-closed state for end users with impaired motor and
declining visual functions. In our experiment, electroencephalography (EEG) and
near-infrared spectroscopy (NIRS) were simultaneously measured while 12 participants
performed mental arithmetic (MA) and remained relaxed (baseline state: BL). To
evaluate the feasibility of the hybrid BCI, we classified MA- from BL-related
brain activation. We then compared classification accuracies using two unimodal
BCIs (EEG and NIRS) and the hybrid BCI in an offline mode. The classification
accuracy of the hybrid BCI (83.9 ± 10.3 %) was shown to be significantly higher
than those of unimodal EEG-based (77.3 ± 15.9 %) and NIRS-based BCI (75.9 ± 6.3
%). The analytical results confirmed performance improvement with the hybrid
BCI, particularly for only frontal brain areas. Our study shows that an
eyes-closed hybrid BCI approach based on frontal areas could be applied to neurodegenerative
patients who lost their motor functions, including oculomotor functions.