A case for hybrid BCIs: combining optical and electrical modalities improves accuracy

Abstract

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only.

Keywords: BCI; EEG; LASSO; NIRS system design; classification; matching pursuit; monitoring brain activity; multi-modal BCI.