Trial reportPloS one2017
A comparison of stimulus types in online classification of the P300 speller using language models.
Trial report in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 29 citations in OpenAlex.
- An Immersive P300 Brain-Computer Interface Based on 3D Morphological Stimuli and Self-Adaptive Bayesian Linear Discriminant Analysis.Biomimetics (Basel, Switzerland) · 2026Article
- Article
- Extending Brain-Computer Interface Access with a Multilingual Language Model in the P300 Speller.Brain computer interfaces (Abingdon, England) · 2022Article
- Evaluation of color modulation in visual P300-speller using new stimulus patterns.Cognitive neurodynamics · 2021Article
- Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions.Frontiers in human neuroscience · 2021Review
- Influence of the Number of Channels and Classification Algorithm on the Performance Robustness to Electrode Shift in Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces.Frontiers in neuroinformatics · 2021Article
- Evaluation of a P300-Based Brain-Machine Interface for a Robotic Hand-Orthosis Control.Frontiers in neuroscience · 2020Article
- Optimising non-invasive brain-computer interface systems for free communication between naïve human participants.Scientific reports · 2019Article
- Neural Activities Classification of Human Inhibitory Control Using Hierarchical Model.Sensors (Basel, Switzerland) · 2019Article
- Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.Brain computer interfaces (Abingdon, England) · 2019Article
- The Self-Face Paradigm Improves the Performance of the P300-Speller System.Frontiers in computational neuroscience · 2019Article
- Robust detection of event-related potentials in a user-voluntary short-term imagery task.PloS one · 2019Article
- Brain-Computer Interface Spellers: A Review.Brain sciences · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
The P300 Speller is a common brain-computer interface communication system. There are many parallel lines of research underway to overcome the system's low signal to noise ratio and thereby improve performance, including using famous face stimuli and integrating language information into the classifier. While both have been shown separately to provide significant improvements, the two methods have not yet been implemented together to demonstrate that the improvements are complimentary. The goal of this study is therefore twofold. First, we aim to compare the famous faces stimulus paradigm with an existing alternative stimulus paradigm currently used in commercial systems (i.e., character inversion). Second, we test these methods with language model integration to assess whether different optimization approaches can be combined to further improve BCI communication. In offline analysis using a previously published particle filter method, famous faces stimuli yielded superior results to both standard and inverting stimuli. In online trials using the particle filter method, all 10 subjects achieved a higher selection rate when using the famous faces flashing paradigm than when using inverting flashes. The improvements achieved by these methods are therefore complementary and a combination yields superior results to either method implemented individually when tested in healthy subjects.
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What OpenQuestion holds
Registered trials
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.