The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
SSVEP-based Bremen–BCI interface—boosting information transfer rates
Open accessAbstract
In recent years, there has been increased interest in using steady-state visual evoked potentials (SSVEP) in brain-computer interface (BCI) systems; the SSVEP approach currently provides the fastest and most reliable communication paradigm for the implementation of a non-invasive BCI. This paper presents recent developments in the signal processing of the SSVEP-based Bremen BCI system, which allowed one of the subjects in an online experiment to reach a peak information transfer rate (ITR) of 124 bit min(-1). It is worth mentioning that this ITR value is higher than all values previously published in the literature for any kind of BCI paradigm.
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Cites
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
Steady-state visually evoked potentials: Focus on essential paradigms and future perspectives
Vialatte, F.-B., Maurice, M., Dauwels, J., & Cichocki, A. (2010) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2009.11.005 · Cited by 1,066
An efficient P300-based brain–computer interface for disabled subjects
Hoffmann, U., Vesin, J.-M., Ebrahimi, T., & Diserens, K. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.03.005 · Cited by 859
Brain-Computer Interfaces Based on Visual Evoked Potentials
Wang, Y., Gao, X., Hong, B., Jia, C., & Gao, S. (2008) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2008.923958 · Cited by 423
BCI demographics: how many (and what kinds of) people can use an SSVEP BCI?
Allison, B., Luth, T., Valbuena, D., Teymourian, A., Volosyak, I., & Graser, A. (2010) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2039495 · Cited by 344
Self-citation
Cited by
Brain–Computer Interface Spellers: A Review
Rezeika, A., Benda, M., Stawicki, P., Gembler, F., Saboor, A., & Volosyak, I. (2018) · Brain Sciences · doi:10.3390/brainsci8040057 · Cited by 391
Self-citationEEG-Based Brain-Computer Interfaces: A Thorough Literature Survey
Hwang, H.-J., Kim, S., Choi, S., & Im, C.-H. (2013) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2013.780869 · Cited by 257
A Dynamically Optimized SSVEP Brain–Computer Interface (BCI) Speller
Yin, E., Zhou, Z., Jiang, J., Yu, Y., & Hu, D. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2320948 · Cited by 254
Mahmood, M., Mzurikwao, D., Kim, Y.-S., Lee, Y., Mishra, S., Herbert, R., Duarte, A., Ang, C. S., & Yeo, W.-H. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0091-7 · Cited by 181
Systems Neuroengineering: Understanding and Interacting with the Brain
Edelman, B. J., Johnson, N., Sohrabpour, A., Tong, S., Thakor, N., & He, B. (2015) · Engineering · doi:10.15302/j-eng-2015078 · Cited by 45
Metadata
- Authors
- Volosyak, I.
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2011-05-10
- Volume
- 8
- Issue
- 3
- Pages
- 036020
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- OpenAlex
- W2038052881
- Cited by
- 232
- References
- 5
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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