Evidence map›Paper›PMID 37342465›Full record

ArticleFrontiers in neuroscience2023

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

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiaolin XiaoSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Runyuan GaoSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Xiaoyu ZhouSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Weibo YiBeijing Institute of Mechanical Equipment, Beijing, China.
Fangzhou XuInternational School for Optoelectronic Engineering, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China.
Kun WangAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
Minpeng XuSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Dong MingSchool of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

discriminative spatial patternsevoked related potentialinformation transfer ratev-BCIweak stimuli

Identifiers

PMID37342465
PMCPMC10278229

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.