A Brain Computer Interface based Communication System using SSVEP and EOG

Abstract

This study aims to design a high performance communication system using steady state visual evoked potential (SSVEP) and electro-oculogram (EOG) signal. The proposed keyboard system consists of twenty three randomly chosen characters and they were indexed into different flickering visual stimuli designed using three SSVEP stimulus frequencies. The same frequency valued visual stimuli were used many times (more than once) in the keyboard layout. In this approach an oddball paradigm is introduced and it randomly highlights three/two unique frequency valued visual stimuli at a time. The system identifies a desired target by user eye blink in accordance to the oddball paradigm and recognized SSVEP frequency value. The signal to noise ratio (SNR) of the real time SSVEP electroencephalogram signal gets increased by the introduction of oddball paradigm in the SSVEP based keyboard system. The paradigm will increase the subject’s attention and concentration on the flickering target stimulus. The real time SSVEP data were classified using extended multivariate synchronization index (EMSI) method. The thresholding method is used for single blink detection. The offline and online experiments were performed by all the subjects for evaluating the proposed communication system. The average classification accuracy and information transfer rate of the system are 96.73 % and 76.02 bits/min respectively.