A Decade of Rapid Serial Visual Presentation Paradigm in Brain-Computer Interface for Target Detection: Current Status and Trends

Objective: Electroencephalography (EEG)-based Rapid Serial Visual Presentation (RSVP) has steadily gained attention since 2015 as a paradigm to enhance image target detection in brain-computer interfaces (BCIs) used with healthy individuals. Methods: We reviewed the literature using Scopus and Web o...

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Veröffentlicht in:IEEE transactions on biomedical engineering Jg. PP; S. 1 - 15
Hauptverfasser: Xu, Meng, Zhang, Baiwen, Zhang, Lijian, Wang, Dan, Chen, Yuanfang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 29.08.2025
Schlagworte:
algorithm decoding
Artificial intelligence
Brain-computer interfaces
Decoding
Electroencephalography
Encoding
Image coding
Media
modality combinations
Object detection
Physiology
public datasets
Rapid serial visual presentation
target detection
Visualization
ISSN:0018-9294, 1558-2531, 1558-2531
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Zusammenfassung:Objective: Electroencephalography (EEG)-based Rapid Serial Visual Presentation (RSVP) has steadily gained attention since 2015 as a paradigm to enhance image target detection in brain-computer interfaces (BCIs) used with healthy individuals. Methods: We reviewed the literature using Scopus and Web of Science as primary databases, covering publications from 2015 to 2024. After literature screening and filtering, a total of 86 papers on RSVP-BCI studies were analyzed over this decadelong period. The research categorizes RSVP into three dimensions: public datasets, paradigm encoding, and decoding methods, while exploring eight mode combinations involving target types, subject groups, and different modalities. Results: Our literature search revealed a scarcity of studies addressing diverse target types across different subject groups or modality combinations, indicating a promising direction for future RSVP-BCI development. Future efforts should prioritize inclusivity across all age groups, the design of user-friendly stimulus interfaces, and the development of advanced algorithms, with the goal of creating a more widely accessible RSVP-BCI system. Conclusion: We have provided a comprehensive review of advances over the past decade in RSVP-based target detection, including datasets, encoding design, and decoding methods and potential applications. Significance: The present work aims to articulate prospective trajectories for the continued advancement of the RSVP community.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0018-9294
1558-2531
1558-2531
DOI:10.1109/TBME.2025.3603945