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

Xiaolin Xiao; Runyuan Gao; Xiaoyu Zhou; Weibo Yi; Fangzhou Xu; Kun Wang; Minpeng Xu; Dong Ming

doi:10.3389/fnins.2023.1178283

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

Front Neurosci. 2023 Jun 5:17:1178283. doi: 10.3389/fnins.2023.1178283. eCollection 2023.

Authors

Xiaolin Xiao^{1

2}, Runyuan Gao¹, Xiaoyu Zhou¹, Weibo Yi³, Fangzhou Xu⁴, Kun Wang², Minpeng Xu^{1

2

4}, Dong Ming^{1

2}

Affiliations

¹ School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
² Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
³ Beijing Institute of Mechanical Equipment, Beijing, China.
⁴ International School for Optoelectronic Engineering, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China.

Abstract

Introduction: Traditional visual Brain-Computer Interfaces (v-BCIs) usually use large-size stimuli to attract more attention from users and then elicit more distinct and robust EEG responses, which would cause visual fatigue and limit the length of use of the system. On the contrary, small-size stimuli always need multiple and repeated stimulus to code more instructions and increase separability among each code. These common v-BCIs paradigms can cause problems such as redundant coding, long calibration time, and visual fatigue.

Methods: To address these problems, this study presented a novel v-BCI paradigm using weak and small number of stimuli, and realized a nine-instruction v-BCI system that controlled by only three tiny stimuli. Each of these stimuli were located between instructions, occupied area with eccentricities subtended 0.4°, and flashed in the row-column paradigm. The weak stimuli around each instruction would evoke specific evoked related potentials (ERPs), and a template-matching method based on discriminative spatial pattern (DSP) was employed to recognize these ERPs containing the intention of users. Nine subjects participated in the offline and online experiments using this novel paradigm.

Results: The average accuracy of the offline experiment was 93.46% and the online average information transfer rate (ITR) was 120.95 bits/min. Notably, the highest online ITR achieved 177.5 bits/min.

Discussion: These results demonstrate the feasibility of using a weak and small number of stimuli to implement a friendly v-BCI. Furthermore, the proposed novel paradigm achieved higher ITR than traditional ones using ERPs as the controlled signal, which showed its superior performance and may have great potential of being widely used in various fields.

Keywords: discriminative spatial patterns; evoked related potential; information transfer rate; v-BCI; weak stimuli.