An Efficient Asynchronous High-Frequency Steady-State Visual Evoked Potential-Based Brain-Computer Interface speller: The Problem of Individual Differences

Abstract

Background: Brain-computer interfaces (BCIs) based on steady-state visual evoked potentials(SSVEPs) provide high rates of accuracy and information transfer rate, but need user's attention to flickering visual stimuli. This quickly leads to eye-fatigue when the flickering frequency isin the low-frequency range. High-frequency flickering stimuli (>30 Hz) have been proposedwith significantly lower eye-fatigue. However, SSVEP responses in this frequency range areremarkably weaker, leading to doubts about usability of high-frequency stimuli to develop efficient BCI systems. The purpose of this study was to evaluate if a practical SSVEP Speller can bedeveloped with Repetitive Visual Stimuli in the high-frequency range. Methods: An asynchronous high-frequency (35-40 Hz) speller for typing in Persian language was developed using five flickering visual stimuli. Least absolute shrinkage and selection operator algorithm with two user-calibrated thresholds was used to detect the user's selections. A total of 14 volunteers evaluated the system inan ordinary office environment to type 9 sentences consist of 81 characters with a multistage virtualkeyboard. Results: Despite very high performance of 6.9 chars/min overall typing speed, averageaccuracy of 98.3%, and information transfer rate of 64.9 bpm for eight of the participants, the other six participants had serious difficulty in spelling with the system and could not complete the typing experiment. Conclusions: The results of this study in accordance with some previous studies suggest that high rate of illiteracy in high-frequency SSVEP-based BCI systems may be a major burden fortheir practical application.