title: Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface.
abstract: The hybrid brain-computer interface (BCI)'s multimodal technology enables precision brain-signal classification that can be used in the formulation of control commands. In the present study, an experimental hybrid near-infrared spectroscopy-electroencephalography (NIRS-EEG) technique was used to extract and decode four different types of brain signals. The NIRS setup was positioned over the prefrontal brain region, and the EEG over the left and right motor cortex regions. Twelve subjects participating in the experiment were shown four direction symbols, namely, "forward," "backward," "left," and "right." The control commands for forward and backward movement were estimated by performing arithmetic mental tasks related to oxy-hemoglobin (HbO) changes. The left and right directions commands were associated with right and left hand tapping, respectively. The high classification accuracies achieved showed that the four different control signals can be accurately estimated using the hybrid NIRS-EEG technology.
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University Busan, Republic of Korea.
authors.forename: M Jawad
authors.initials: MJ
authors.lastname: Khan
authors.affiliation: Department of Education Policy and Social Analysis, Columbia University New York, NY, USA.
authors.forename: Melissa Jiyoun
authors.initials: MJ
authors.lastname: Hong
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University Busan, Republic of Korea ; School of Mechanical Engineering, Pusan National University Busan, Republic of Korea.
authors.forename: Keum-Shik
authors.initials: KS
authors.lastname: Hong
keywords: arithmetic mental task; electroencephaelography; hybrid brain-computer interface; linear discriminant analysis; motor execution; near-infrared spectroscopy