Abstract

As the light reflex of the pupil relies on covert attention, it has been suggested for use as a non-contact, calibration-free human–computer interface. A vital aspect of the widespread adoption of this interface is the elevated information transfer rate. This study involved the design and assessment of binary light stimulation under conditions where the stimulation and discrimination systems operate asynchronously. Binary light stimulation, characterized by uniquely timed light flickering, enables the discrimination system to identify the gazed target through variations in pupil diameter. To enhance the temporal efficiency, a cyclic code was selected for binary coding. Algorithms for selecting optimal codes, determining phase-shift relationships, and designing binary codes with strategic location arrangements were developed. An experimental application of a template-matching-based classification algorithm yielded over 83% accuracy in identifying a gazed target among nine possibilities. The average information transfer rate was 30 bits/min under stable conditions. Additionally, by analyzing the values of the proposed evaluation functions, we can predict combinations prone to misclassification in the target classification. Practically, this research offers a robust method for brain–computer interfaces, potentially benefiting users with severe motor restrictions or in contexts requiring hands-free operation.

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