Comparisons of stimulus paradigms for SSVEP-based brain–computer interfaces
<i>Objective.</i>With the recent development of visual evoked potential (VEP) based brain-computer interfaces (BCIs), the stimulus paradigm has been continuously innovated, in which the pursuit of higher BCI performance and better user experience has become indispensable.<i>Approach.</i>To optimize the stimulus paradigm, a 12-target online BCI system was designed in this study by adopting flicker for steady-state VEPs, Newton's ring for steady-state motion VEP, and frame rate based video stimulus, respectively. The signal characteristics of VEP, classification accuracy, and user experience of the three stimulus paradigms were quantitatively evaluated and compared.<i>Main results.</i>The online information transfer rates for the three stimulus paradigms were 53.77 bits min<sup>-1</sup>, 51.41 ± 3.55 bits min<sup>-1</sup>, and 52.07 ± 3.09 bits min<sup>-1</sup>, respectively. The video stimulus had a significantly better user experience, while the flicker stimulus showed the worst.<i>Significance.</i>These results demonstrate the advantage of the proposed video stimulus paradigm and have significant theoretical and applied implications for developing VEP-based BCI systems.
Authors
- Xiaorong Gao (ORCID: https://orcid.org/0000-0003-0499-2740)
- Weihua Pei (ORCID: https://orcid.org/0000-0002-1631-0199)
- Guoya Dong
- Yijun Wang (ORCID: https://orcid.org/0000-0002-8161-2150)
- Deyu Zhao
Institutions
- Hebei University of Technology (CN)
- Chinese Academy of Sciences (CN)
- State Key Laboratory on Integrated Optoelectronics (CN)
- Chinese Academy of Surveying and Mapping (CN)
- Chinese Institute for Brain Research (CN)
- Institute of Semiconductors (CN)
- University of Chinese Academy of Sciences (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Journal of Neural Engineering
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1088/1741-2552/adce32
- Citations
- 2
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Natural Science Foundation of China