Spectrum intensity ratio and thresholding based SSVEP detection

Abstract

Brain Computer Interface (BCI) is a powerful tool to control a computer or machine without body movement. There has been great interest in using Steady-State Visual Evoked Potential (SSVEP) for BCI [1]. Various signal processing and classification techniques are proposed to extract SSVEP from Electroencephalograph (EEG). The feature extraction of SSVEP is developed in the frequency domain regardless of the limitation in hardware architecture, i.e. a low power and simple calculation. We introduced a spectrum intensity ratio as a simple characterization and separation of SSVEP. However, it is difficult to classify an unseeing state of subjects. In addition, we only tried the wide band flickering frequency as visual stimuli. In this paper, we adopt a classification using a simple calculation with threshold to detect the unseeing state from SSVEP in a narrow frequency band. © Springer-Verlag 2013.