A comparison study of two P300 speller paradigms for brain–computer interface
Open accessAbstract
In this paper, a comparison of two existing P300 spellers is conducted. In the first speller, the visual stimuli of characters are presented in a single character (SC) paradigm and each button corresponding to a character flashes individually in a random order. The second speller is based on a region-based (RB) paradigm. In the first level, all characters are grouped and each button corresponding to a group flashes individually in a random order. Once a group is selected, the characters in it will appear on the flashing buttons of the second level for the selection of desired character. In a spelling experiment involving 12 subjects, higher online accuracy was obtained on the RB paradigm-based P300 speller than the SC paradigm-based P300 speller. Furthermore, we analyzed P300 detection performance, the P300 waveforms and Fisher ratios using the data collected by the two spellers. It was found that the stimuli display paradigm of the RB speller enhances P300 potential and is more suitable for P300 detection.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
SVM classifier was widely used in the EEG-based brain computer interface in practice.
“It should be noted that SVM classifier was widely used in the EEG-based brain computer interface in practice [26–29].”
From Fusion of Facial Expressions and EEG for Multimodal Emotion Recognition (2017) · cites this paper as [28]
The Data collection and processing section uses an SVM classifier on EEG features, and the Region-based speller section says an SVM model was applied in an online BCI test. These passages support SVM use in an EEG-based BCI, but do not establish that SVM classifiers were widely used across such systems in practice. Page numbers are unavailable in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918 · see citing works
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927 · see citing works
Farwell, L. A., & Donchin, E. (1988) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(88)90149-6 · Cited by 3,228 · see citing works
The mental prosthesis: assessing the speed of a P300-based brain-computer interface
Donchin, E., Spencer, K., & Wijesinghe, R. S. (2000) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.847808 · Cited by 1,217 · see citing works
Blankertz, B., Muller, K.-R., Curio, G., Vaughan, T. M., Schalk, G., Wolpaw, J. R., Schlogl, A., Neuper, C., Pfurtscheller, G., Hinterberger, T., et al. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.826692 · Cited by 670 · see citing works
How many people are able to control a P300-based brain-computer interface (BCI)?
Guger, C., Daban, S., Sellers, E., Holzner, C., Krausz, G., Carabalona, R., Gramatica, F., & Edlinger, G. (2009) · Neuroscience Letters · doi:10.1016/j.neulet.2009.06.045 · Cited by 652 · see citing works
A method to standardize a reference of scalp EEG recordings to a point at infinity
Yao, D. (2001) · Physiological Measurement · doi:10.1088/0967-3334/22/4/305 · Cited by 585 · see citing works
Townsend, G., LaPallo, B. K., Boulay, C. B., Krusienski, D. J., Frye, G. E., Hauser, C. K., Schwartz, N. E., Vaughan, T. M., Wolpaw, J. R., & Sellers, E. W. (2010) · Clinical Neurophysiology · doi:10.1016/j.clinph.2010.01.030 · Cited by 570 · see citing works
Sellers, E. W., Krusienski, D. J., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2006) · Biological Psychology · doi:10.1016/j.biopsycho.2006.04.007 · Cited by 504 · see citing works
Fabiani, M., Gratton, G., Karis, D., & Donchin, E. (1987) · Digital Commons - University of South Florida (University of South Florida) · Cited by 376 · see citing works
The wadsworth BCI research and development program: at home with BCI
Vaughan, T. M., McFarland, D. J., Schalk, G., Sarnacki, W. A., Krusienski, D. J., Sellers, E. W., & Wolpaw, J. R. (2006) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2006.875577 · Cited by 335 · see citing works
P300 amplitude is determined by target‐to‐target interval
Gonsalvez, C. J., & Polich, J. M. (2002) · Psychophysiology · doi:10.1017/s0048577201393137 · Cited by 284 · see citing works
ERPs evoked by different matrix sizes: implications for a brain computer interface (BCI) system
Allison, B. Z., & Pineda, J. A. (2003) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2003.814448 · Cited by 226 · see citing works
Unfocussed spatial attention underlies the crowding effect in indirect form vision
Strasburger, H. (2005) · Journal of Vision · doi:10.1167/5.11.8 · Cited by 219 · see citing works
Qin, Y. F., Xu, P., & Yao, D. (2010) · Clinical Neurophysiology · doi:10.1016/j.clinph.2010.03.056 · Cited by 209 · see citing works
Visual modifications on the P300 speller BCI paradigm
Salvaris, M., & Sepulveda, F. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/4/046011 · Cited by 197 · see citing works
High performance p300 speller for brain-computer interface
Guan, C., Thulasidas, M., & Wu, J. (2005) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2004.1454155 · Cited by 165 · see citing works
Takano, K., Komatsu, T., Hata, N., Nakajima, Y., & Kansaku, K. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2009.06.002 · Cited by 148 · see citing works
The P300-based brain–computer interface (BCI): Effects of stimulus rate
McFarland, D. J., Sarnacki, W. A., Townsend, G., Vaughan, T. M., & Wolpaw, J. R. (2010) · Clinical Neurophysiology · doi:10.1016/j.clinph.2010.10.029 · Cited by 122 · see citing works
Allison, B. Z., & Pineda, J. A. (2005) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2005.02.007 · Cited by 119 · see citing works
Subliminal visual oddball stimuli evoke a P300 component.
Bernat, E. M., Shevrin, H., & Snodgrass, M. (2001) · Clinical Neurophysiology · doi:10.1016/s1388-2457(00)00445-4 · Cited by 106 · see citing works
Farwell, L. A. (2012) · Cognitive Neurodynamics · doi:10.1007/s11571-012-9192-2 · Cited by 103 · see citing works
A region-based P300 speller for brain-computer interface
Fazel-Rezai, R., & Abhari, K. (2009) · Canadian Journal of Electrical and Computer Engineering · doi:10.1109/cjece.2009.5443854 · Cited by 97 · see citing works
Human Error in P300 Speller Paradigm for Brain-Computer Interface
Fazel-Rezai, R. (2007) · Conference proceedings · doi:10.1109/iembs.2007.4352840 · Cited by 94 · see citing works
P300, stimulus intensity, and modality
Covington, J. W., & Polich, J. M. (1996) · Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section · doi:10.1016/s0168-5597(96)96013-x · Cited by 75 · see citing works
A new interpretation of P300 responses upon analysis of coherences
Güntekin, B., & Başar, E. (2010) · Cognitive Neurodynamics · doi:10.1007/s11571-010-9106-0 · Cited by 66 · see citing works
Fazel-Rezai, R., & Abhari, K. (2008) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2008.4649364 · Cited by 48 · see citing works
P300-based Brain-Computer Interface Paradigm Design
Fazel-Rezai, R., & Ahm, W. (2011) · InTech eBooks · doi:10.5772/14858 · Cited by 37 · see citing works
Semi-supervised joint spatio-temporal feature selection for P300-based BCI speller
Long, J., Gu, Z., Li, Y., Yu, T., Li, F., & Fu, M. (2011) · Cognitive Neurodynamics · doi:10.1007/s11571-011-9167-8 · Cited by 26 · see citing works
Self-citationInvestigation of changes in EEG complexity during memory retrieval: the effect of midazolam
Talebi, N., Nasrabadi, A. M., & Curran, T. (2012) · Cognitive Neurodynamics · doi:10.1007/s11571-012-9214-0 · Cited by 24 · see citing works
Yao, D. (2002) · Physics in Medicine and Biology · doi:10.1088/0031-9155/47/12/312 · Cited by 17 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Duda RO, Hart PE (1973) Pattern classification and scene analysis, vol 1. Wiley, New York
Cited by
Sorted by citations
Fusion of Facial Expressions and EEG for Multimodal Emotion Recognition
Huang, Y., Yang, J., Liao, P., & Pan, J. (2017) · Computational Intelligence and Neuroscience · doi:10.1155/2017/2107451 · Cited by 115 · see citing works
Self-citation
- Authors
- Pan, J., Li, Y., Gu, Z., & Yu, Z.
- Affiliations
- South China Normal University (CN)
- South China University of Technology (CN)
- Corresponding author
- Li, Yuanqing
- Venue
- Cognitive Neurodynamics
- Published
- 2013-04-16
- Volume
- 7
- Issue
- 6
- Pages
- 523-529
- ISSN
- 1871-4080 (ISSN-L)
- 1871-4099
- PMC
- PMC3825150
- OpenAlex
- W2072662136
- Cited by
- 46
- References
- 31
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 7 · 2020: 6 · 2019: 5 · 2018: 1 · 2017: 8 · 2016: 5 · 2015: 2
- FWCI
- 1.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Cognitive Neurodynamics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (91120305, 863 Program, 2012AA011601, 61105121, 61175114)
- National High-tech Research and Development Program
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Keywords
- P300 speller, P300 event-related potential, brain-computer interface, character selection, P300 detection, Fisher ratio, visual stimulus presentation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
