ArticleFrontiers in human neuroscience2019
P300 Speller Performance Predictor Based on RSVP Multi-feature.
Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Evaluation of Different Types of Stimuli in an Event-Related Potential-Based Brain-Computer Interface Speller under Rapid Serial Visual Presentation.Sensors (Basel, Switzerland) · 2024Article
- Article
- Optimization of transfer learning based on source sample selection in Euclidean space for P300-based brain-computer interfaces.Frontiers in neuroscience · 2024Article
- BCI-Utility Metric for Asynchronous P300 Brain-Computer Interface Systems.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2023Article
- EEG Dataset for RSVP and P300 Speller Brain-Computer Interfaces.Scientific data · 2022Article
- P300 Brain-Computer Interface-Based Drone Control in Virtual and Augmented Reality.Sensors (Basel, Switzerland) · 2021Article
- See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions.Frontiers in human neuroscience · 2021Article
- Target Detection Using Ternary Classification During a Rapid Serial Visual Presentation Task Using Magnetoencephalography Data.Frontiers in computational neuroscience · 2021Article
- A Survey on Deep Learning-Based Short/Zero-Calibration Approaches for EEG-Based Brain-Computer Interfaces.Frontiers in human neuroscience · 2021Review
- An Open Source-Based BCI Application for Virtual World Tour and Its Usability Evaluation.Frontiers in human neuroscience · 2021Article
- Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder.Frontiers in psychiatry · 2021Article
- Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions.Sensors (Basel, Switzerland) · 2020Article
- Improving the Cross-Subject Performance of the ERP-Based Brain-Computer Interface Using Rapid Serial Visual Presentation and Correlation Analysis Rank.Frontiers in human neuroscience · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interface (BCI) systems were developed so that people can control computers or machines through their brain activity without moving their limbs. The P300 speller is one of the BCI applications used most commonly, as is very simple and reliable and can achieve satisfactory performance. However, like other BCIs, the P300 speller still has room for improvements in terms of its practical use, for example, selecting the best compromise between spelling accuracy and information transfer rate (ITR; speed) so that the P300 speller can maintain high accuracy while increasing spelling speed. Therefore, seeking correlates of, and predicting, the P300 speller's performance is necessary to understand and improve the technique. In this work, we investigated the correlations between rapid serial visual presentation (RSVP) task features and the P300 speller's performance. Fifty-five subjects participated in the RSVP and conventional matrix P300 speller tasks and RSVP behavioral and electroencephalography (EEG) features were compared in the P300's speller performance. We found that several of the RSVP's event-related potential (ERP) and behavioral features were correlated with the P300 speller's offline binary classification accuracy. Using these features, we propose a simple multi-feature performance predictor (
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