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Updated: Aug 3, 2025
06:09
P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
620
How Visual Stimuli Evoked P300 is Transforming the Brain-Computer Interface Landscape: A PRISMA Compliant Systematic
Summary
This review analyzes 147 studies on non-invasive visual stimuli evoked-EEG-based P300 Brain-Computer Interfaces (BCIs). Research shows growing interest in P300 BCIs for assistive technology, driven by wireless EEG and AI advancements.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Computer Science
Background:
- Non-invasive visual stimuli evoked-EEG-based P300 Brain-Computer Interfaces (BCIs) are increasingly vital for assistive devices.
- P300 BCIs extend beyond medical applications into entertainment, robotics, and education.
Purpose of the Study:
- To systematically review and classify 147 articles on P300 BCIs published between 2006-2021.
- To analyze trends in article focus, participant demographics, tasks, databases, EEG devices, classification models, and application domains.
Main Methods:
- Systematic literature review of 147 articles (2006-2021).
- Classification of studies based on primary focus: orientation, participant age, tasks, databases, EEG devices, classification models, and application domain.
- Inclusion based on pre-defined criteria.
Main Results:
- Significant growth in research interest for P300 detection using visual stimuli.
- Increasing adoption of P300 BCIs for spelling applications.
- Expansion driven by wireless EEG devices and advancements in computational intelligence, machine learning, neural networks, and deep learning.
Conclusions:
- P300 detection via visual stimuli is a prominent and legitimate research area.
- The field of BCI spellers utilizing P300 shows significant growth.
- Technological advancements are key drivers for the expanding potential and applications of P300 BCIs.
