Detection of fixation points using a small visual landmark for brain–computer interfaces

Abstract

Objective. The speed of visual brain–computer interfaces (v-BCIs) has been greatly improved in recent years. However, the traditional v-BCI paradigms require users to directly gaze at the intensive flickering items, which would cause severe problems such as visual fatigue and excessive visual resource consumption in practical applications. Therefore, it is imperative to develop a user-friendly v-BCI. Approach. According to the retina-cortical relationship, this study developed a novel BCI paradigm to detect the fixation point of eyes using a small visual stimulus that subtended only 0.6° in visual angle and was out of the central visual field. Specifically, the visual stimulus was treated as a landmark to judge the eccentricity and polar angle of the fixation point. Sixteen different fixation points were selected around the visual landmark, i.e. different combinations of two eccentricities (2° and 4°) and eight polar angles (, , , , , , and ). Twelve subjects participated in this study, and they were asked to gaze at one out of the 16 points for each trial. A multi-class discriminative canonical pattern matching (Multi-DCPM) algorithm was proposed to decode the user’s fixation point. Main results. We found the visual stimulation landmark elicited different spatial event-related potential patterns for different fixation points. Multi-DCPM could achieve an average accuracy of 66.2% with a standard deviation of 15.8% for the classification of the sixteen fixation points, which was significantly higher than traditional algorithms (). Experimental results of this study demonstrate the feasibility of using a small visual stimulus as a landmark to track the relative position of the fixation point. Significance. The proposed new paradigm provides a potential approach to alleviate the problem of irritating stimuli in v-BCIs, which can broaden the applications of BCIs.

A novel visual brain-computer interfaces paradigm based on evoked related potentials evoked by weak and small number of stimuli

“…Previous studies indicated that spatial features of ERPs commonly appeared at 100–200 ms after the presentation of stimuli ( Chen et al, 2018 ; Xu et al, 2018 ; Zhou et al, 2021 ). For one trial arranged in this paradigm, various stimuli presented at 0 ms, 100 ms, 200 ms, and 300 ms corresponding to four stimulus patterns S1, S2, S3, and S4 individually ( Figure 1 ).…”

“…Moreover, although there was no significance between S4 and the other patterns, the accuracy of it was still higher than S1 and S2. This may be attributed to the difference between left and right hemispheres of the brain is higher than that between upper and lower hemispheres ( Zhou et al, 2021 ).…”

“…Thus, decreasing the number of decoding templates becomes significant. For this paradigm using characteristic of spatial features, the relative position and distance between visual stimuli and the gazed character are two vital aspects of paradigm designing ( Zhou et al, 2021 ). According to the analysis of spatial features in Figure 4 , distinct spatial features of EEG were evoked by four stimulus patterns.…”

“…It has been demonstrated that Discriminative Spatial Pattern (DSP) could effectively identify the spatial feature of EEG evoked by very small stimuli ( Xu et al, 2018 ; Zhou et al, 2021 ). Thus, this study used DSP for extracting and recognizing EEG features, which consisted of two major parts: (1) the construction of DSPs and (2) pattern matching.…”

“…In 2021, we further designed a 16-command ERP-BCI with only one small visual stimulus. In this study, the spatial ERPs induced by a small visual stimulus was highly related to the distances and directions between the stimulus and the 16 gazed positions ( Zhou et al, 2021 ). Inspired by these results, we believe that there is huge potential to design user-friendly and multi-instructions ERP-BCIs using tiny lateralized ERPs.…”