The effect of distractors on SSVEP-based brain-computer interfaces

Abstract

Objective. This study analyses the effect of distractors on steady-state visually evoked potentials (SSVEP) to establish how these nuisance signals, typically present in the real-world, would effect an SSVEP-based brain-computer interface (BCI). The distractors introduced to the SSVEP-based experiments are auditory, visual and movement distractors, specifically selected to reflect the use of various BCIs outside the laboratory. Approach. An assessment on the influence of these nuisance signals on SSVEP data as compared to SSVEP data with no distractors is presented. This is done by examining the frequency spectrum of the SSVEP responses followed by the implementation of feature extraction techniques, specifically canonical correlation analysis (CCA) and power spectral density analysis (PSDA), and a statistical analysis on the results obtained. As an added contribution, this study is designed to have each subject repeat the same experiments on different days such that the variation in performance with and without distractors may be investigated longitudinally. Main results. The results revealed that the spectra and the classification performance of the auditory distractors condition are comparable with the no distractors condition. On the other hand, there is a decrease in the signal-to-noise ratios (SNRs) of the visual and movement distractors conditions. This is reflected with a significant decrease in the SSVEP performance of 4.29% and 12.14% for the two distractor conditions respectively compared to the no distractors condition. A significant above-chance level SSVEP performance could still be obtained with all the distractor conditions. The longitudinal analysis revealed that the difference in performance between the SSVEP experimental conditions was consistent across sessions. Significance. This study provides a comparison on the performance of an SSVEP-based BCI with various external distractors. This analysis is necessary for the transition of BCI applications to be used every day in uncontrolled environments.