ArticleFrontiers in neuroscience2011
Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).
Article in Frontiers in neuroscience, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals.Journal of neurophysiology · 2018Trial
- High performance communication by people with paralysis using an intracortical brain-computer interface.eLife · 2017Trial
- Signal acquisition of brain-computer interfaces: A medical-engineering crossover perspective review.Fundamental research · 2025Review
- A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome.Cognitive neurodynamics · 2024Review
- Considerations and discussions on the clear definition and definite scope of brain-computer interfaces.Frontiers in neuroscience · 2024Review
- Towards clinical application of implantable brain-computer interfaces for people with late-stage ALS: medical and ethical considerations.Journal of neurology · 2023Review
- Brain-computer interface paradigms and neural coding.Frontiers in neuroscience · 2023Review
- Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.Frontiers in neuroscience · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Practical real-time MEG-based neural interfacing with optically pumped magnetometers.BMC biology · 2021Article
- P300-Based Brain-Computer Interface Speller: Usability Evaluation of Three Speller Sizes by Severely Motor-Disabled Patients.Frontiers in human neuroscience · 2020Article
- Biomarkers and neuromodulation techniques in substance use disorders.Bioelectronic medicine · 2020Review
- A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.Journal of neural engineering · 2019Article
- Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects.Frontiers in human neuroscience · 2019Review
- Discrimination of Movement-Related Cortical Potentials Exploiting Unsupervised Learned Representations From ECoGs.Frontiers in neuroscience · 2019Article
- Decoding Movement From Electrocorticographic Activity: A Review.Frontiers in neuroinformatics · 2019Review
- Accurate Decoding of Short, Phase-Encoded SSVEPs.Sensors (Basel, Switzerland) · 2018Article
- Decoding Steady-State Visual Evoked Potentials From Electrocorticography.Frontiers in neuroinformatics · 2018Article
- Enhancing Performance of a Hybrid EEG-fNIRS System Using Channel Selection and Early Temporal Features.Frontiers in human neuroscience · 2017Article
- Integrating language models into classifiers for BCI communication: a review.Journal of neural engineering · 2016Review
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Authors and funding
5 authors.
Funding
Abstract
A brain-computer interface (BCI) can provide a non-muscular communication channel to severely disabled people. One particular realization of a BCI is the P300 matrix speller that was originally described by Farwell and Donchin (1988). This speller uses event-related potentials (ERPs) that include the P300 ERP. All previous online studies of the P300 matrix speller used scalp-recorded electroencephalography (EEG) and were limited in their communication performance to only a few characters per minute. In our study, we investigated the feasibility of using electrocorticographic (ECoG) signals for online operation of the matrix speller, and determined associated spelling rates. We used the matrix speller that is implemented in the BCI2000 system. This speller used ECoG signals that were recorded from frontal, parietal, and occipital areas in one subject. This subject spelled a total of 444 characters in online experiments. The results showed that the subject sustained a rate of 17 characters/min (i.e., 69 bits/min), and achieved a peak rate of 22 characters/min (i.e., 113 bits/min). Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller BCI system. Our results also point to potential reasons for the apparent advantages in spelling performance of ECoG compared to EEG. Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.
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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.