ArticleScientific data2022
EEG Dataset for RSVP and P300 Speller Brain-Computer Interfaces.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Dataset Fragmentation, Cognitive Variability, and Reproducibility Challenges in EEG-Based Brain-Computer Interfaces: A PRISMA-Based Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Brain-computer interfaces: innovations and challenges in the field of cerebral palsy rehabilitation.Italian journal of pediatrics · 2026Review
- An EEG dataset for handwriting imagery decoding of Chinese character strokes and Pinyin single vowels.Scientific data · 2026Article
- A multi-subject and multi-session EEG dataset for modelling human visual object recognition.Scientific data · 2025Article
- A novel scrolling text reading paradigm for improving the performance of multiclass and hybrid brain computer interface systems.PloS one · 2025Article
- Evaluation of consumer-grade wireless EEG systems for brain-computer interface applications.Biomedical engineering letters · 2024Article
- Ten quick tips for clinical electroencephalographic (EEG) data acquisition and signal processing.PeerJ. Computer science · 2024Article
- [Research progress of brain-computer interface application paradigms based on rapid serial visual presentation].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- EEG-Based Target Detection Using an RSVP Paradigm under Five Levels of Weak Hidden Conditions.Brain sciences · 2023Article
- A magnetoencephalography dataset during three-dimensional reaching movements for brain-computer interfaces.Scientific data · 2023Article
- A Novel Automatic Audiometric System Design Based on Machine Learning Methods Using the Brain's Electrical Activity Signals.Diagnostics (Basel, Switzerland) · 2023Article
- AMBER: advancing multimodal brain-computer interfaces for enhanced robustness-A dataset for naturalistic settings.Frontiers in neuroergonomics · 2023Article
- Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance.Frontiers in human neuroscience · 2023Review
- EEG Dataset for RSVP and P300 Speller Brain-Computer Interfaces.Scientific data · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As attention to deep learning techniques has grown, many researchers have attempted to develop ready-to-go brain-computer interfaces (BCIs) that include automatic processing pipelines. However, to do so, a large and clear dataset is essential to increase the model's reliability and performance. Accordingly, our electroencephalogram (EEG) dataset for rapid serial visual representation (RSVP) and P300 speller may contribute to increasing such BCI research. We validated our dataset with respect to features and accuracy. For the RSVP, the participants (N = 50) achieved about 92% mean target detection accuracy. At the feature level, we observed notable ERPs (at 315 ms in the RSVP; at 262 ms in the P300 speller) during target events compared to non-target events. Regarding P300 speller performance, the participants (N = 55) achieved about 92% mean accuracy. In addition, P300 speller performance over trial repetitions up to 15 was explored. The presented dataset could potentially improve P300 speller applications. Further, it may be used to evaluate feature extraction and classification algorithm effectively, such as for cross-subjects/cross-datasets, and even for the cross-paradigm BCI model.
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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.