Examination of optimal cognitive task for Near-infrared spectroscopy-based brain-computer interfaces

Abstract

Brain-computer interface (BCI) is a new technology that enables communication using brain activities for patients in totally locked-in state. In this research, we examined optimal mental task for near-infrared spectroscopy-based BCI from among six tasks. SVM was used for learning, and the classification accuracy for each tasks through k-fold cross validation was calculated. As a result, it was suggested that the mental figure rotation is a task with high discrimination accuracy and less sense of burden.