| Summary: | This paper presents a method of binocular visual stimulation for brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs) using phase-coded symbols. The proposed method's emphasis is on a binocular phase-coded visual stimulus, which is based on the phase differences between the left- and right-eye stimuli, and a symbol detection and recognition procedure based on SSVEP response of the left and right occipital lobes of the user's scalp, where the SSVEP response is obtained as electroencephalography (EEG) signaling. The symbols are coded as phase differences and maintain the same frequency of the sine wave-modulated light provided to the user's left and right eyes as a binocular visual stimulation. Based on this method, a basic system setup is presented to explore the possibilities of binocular phase-coded visual stimuli for virtual or augmented reality applications, where the binocular visual stimulation was achieved by the specially designed head-mounted displays. Multiple visually coded targets are realized as eight different phase-coded binocular symbols and further evaluated as a random sequence of single targets, thus representing the situations in virtual or augmented reality, where multiple visually coded targets are present but not visualized to the user simultaneously within the same field of view. The offline results obtained from ten healthy subjects revealed that an average symbol recognition accuracy of 90.63% and an information transfer rate (ITR) of 70.55 bits/min were achieved for a symbol stimulation time of 2 s. The results of this paper demonstrate the feasibility of using binocular visual stimuli for SSVEP-based BCIs, where reasonable ITR is achieved using single-frequency binocular phase-coded symbols. The proposed method indicates the possibility of combining it with 3D wearable visualization technologies, such as binocular head-mounted displays (HMDs), in order to improve the intuitiveness of the interaction with more immersive user experience using BCI modalities.
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