Development of a practical high frequency brain–computer interface based on steady-state visual evoked potentials using a single channel of EEG

Abstract

Brain–computer interfaces based on steady-state visual evoked potentials have recently gained increasing attention due to high performance and minimal user training. Stimulus frequencies in the range of 4–60Hz have been used in these systems. However, eye fatigue when looking at low-frequency flickering lights, higher risk of induced epileptic seizure for medium-frequency flickers, and low signal amplitude for high-frequency flickers complicate appropriate selection of flickering frequencies. Here, different flicker frequencies were evaluated for development of a brain–computer interface speller that ensures user's comfort as well as the system's efficiency. A frequency detection algorithm was also proposed based on Least Absolute Shrinkage and Selection Operator estimate that provides excellent accuracy using only a single channel of EEG. After evaluation of the SSVEP responses in the range of 6–60Hz, three stimulus frequency sets of 30–35, 35–40 and 40–45Hz were adopted and the system's performance and corresponding eye fatigue were compared. While the accuracy of the asynchronous speller for all three stimulus frequency sets was close to the maximum (average 97.6%), repeated measures ANOVA demonstrated that the typing speed for 30–35Hz (8.09char/min) and 35–40Hz (8.33char/min) are not significantly different, but are significantly higher than for 40–45Hz (6.28char/min). On the other hand, the average eye fatigue scale for 35–40Hz (80%) is comparable to that for 40–45Hz (85%), but very higher than for 30–35Hz (60%). Therefore, 35–40Hz range was proposed for the system which resulted in 99.2% accuracy and 67.1bit/min information transfer rate.