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Research Article | Open Access

A large database towards user-friendly SSVEP-based BCI

Jiangsu JITRI Brain Machine Fusion Intelligence Institute, Suzhou 215000, China
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Abstract

Background:

Brain-computer interfaces (BCIs) have gained considerable attention for their potential in assisting individuals who have motor impairments with communication and rehabilitation. Among BCIs, steady-state visual evoked potential (SSVEP)-based systems have demonstrated high efficiency in interactive applications. However, ergonomic design challenges have limited their practical implementation in industrial settings. Issues such as visual and mental fatigue caused by flickering stimuli and the time-consuming preparation process hinder user adoption of such systems.

Methods:

To evaluate these BCI solutions, we introduced an open database comprising Electroencephalogram (EEG) data collected from 59 healthy volunteers using ergonomically designed semi-dry electrodes and grid stimuli. The database was acquired without electromagnetic shielding, and the preparation time for each participant was <5 min. A 40-target SSVEP speller system with cues was used in the experiment.

Results:

We validate the database by temporal and spectral analyzing methods. To further investigate the database, filter bank canonical correlation analysis (FBCCA), ensemble task-related component analysis (e-TRCA) and multi-stimulus task-related component analysis (msTRCA) were used for classification. The database can be downloaded from the following link: https://drive.google.com/drive/folders/1TXuxU863nZoniZRgNWZy0PRuL8lhBuP4?usp=sharing.

Conclusions:

This research contributes to enhancing the use of SSVEP-based BCIs in practical settings by addressing user experience and system design challenges. The proposed user-friendly visual stimuli and ergonomic electrode design improve comfort and usability. The open dataset serves as a valuable resource for future studies, enabling the development of robust and efficient SSVEP-BCI systems suitable for industrial applications.

Keywords

steady-state visual evoked potentialbrain-computer interfacehydrogel electrodegrid stimulusindustrial-like setting

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Brain Science Advances
Volume 9 Issue 4,
December 2023
Pages 297-309
DOI: 10.26599/BSA.2023.9050020
Cite this article:
Dong Y, Tian S. A large database towards user-friendly SSVEP-based BCI. Brain Science Advances, 2023, 9(4): 297-309. https://doi.org/10.26599/BSA.2023.9050020

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Received: 31 May 2023
Revised: 27 July 2023
Accepted: 15 August 2023
Published: 05 December 2023
© The authors 2023.

This article is published with open access at journals.sagepub.com/home/BSA

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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