Eye-gaze Independent Brain Machine Interface Using Steady-State Response of Brain Wave to Light and Auditory Stimuli

The present study proposes a novel binary class of brain machine interface (BMI) system which is independent of eye-gaze control including eye-movement using steady state response of electroencephalogram to photic and auditory stimuli. The proposed BMI system consists of a BMI based on event related modulation of steady-state visual evoked potential (SSVEP) associated with mental task under flicker stimuli (SSVEP-BMI) and another BMI based on auditory steady-state response (ASSR) to sinusoidally modulated auditory stimuli (ASSR-BMI). For the SSVEP-BMI, eighteen healthy subjects aged 21-24 years old participated in the experiment in which they were directed to relax (non-task) or engage in each of the mental focusing on the stimuli, image recalling and mental arithmetic under the stimulus conditions of the flickering frequency of 10 Hz for 10 subjects and 14 Hz for 8 subjects. The offline classification accuracy and information transfer rate of the SSVEP-BMI were from 80 to 88 % and from 1.5 to 2.6 bits/min in average for 10 Hz stimuli, while those were from 74 to 88 % and from 0.8 to 2.6 bits/min in average for 14 Hz stimuli. For the ASSR-BMI, enhancement of ASSR with addition of noise, namely, stochastic resonance (SR) effect, was investigated for the aim of boost of classification performance of a ASSR-BMI. Eight healthy students aged 22-24 years old volunteered to participate in the experiment. Enhancement of ASSR was observed under the appropriate auditory noise level (40-50dB) for four subjects, indicating the feasibility of application to ASSR-BMI.