The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Toward a high-throughput auditory P300-based brain–computer interface
Open accessAbstract
Objective Brain-computer interface (BCI) technology can provide severely disabled people with non-muscular communication. For those most severely disabled, limitations in eye mobility or visual acuity may necessitate auditory BCI systems. The present study investigates the efficacy of the use of six environmental sounds to operate a 6×6 P300 Speller. Methods A two-group design was used to ascertain whether participants benefited from visual cues early in training. Group A (N=5) received only auditory stimuli during all 11 sessions, whereas Group AV (N=5) received simultaneous auditory and visual stimuli in initial sessions after which the visual stimuli were systematically removed. Stepwise linear discriminant analysis determined the matrix item that elicited the largest P300 response and thereby identified the desired choice. Results Online results and offline analyses showed that the two groups achieved equivalent accuracy. In the last session, eight of ten participants achieved 50% or more, and four of these achieved 75% or more, online accuracy (2.8% accuracy expected by chance). Mean bit rates averaged about 2 bits/min, and maximum bit rates reached 5.6 bits/min. Conclusions This study indicates that an auditory P300 BCI is feasible, that reasonable classification accuracy and rate of communication are achievable, and that the paradigm should be further evaluated with a group of severely disabled participants who have limited visual mobility. Significance With further development, this auditory P300 BCI could be of substantial value to severely disabled people who cannot use a visual BCI.
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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
Self-citationJohnson, R. (1986) · Psychophysiology · doi:10.1111/j.1469-8986.1986.tb00649.x · Cited by 960
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
Toward enhanced p300 speller performance
Krusienski, D. J., Sellers, E. W., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.07.017 · Cited by 749 · cited 6×
“This process was repeated until no additional features met the entry/removal criteria, or until a pre-defined number of features were entered into the model (Draper and Smith, 1981; Krusienski et al., 2006, 2008).”
BackgroundMethodResultInfluentialA P300-based brain–computer interface for people with amyotrophic lateral sclerosis
Nijboer, F., Sellers, E. W., Mellinger, J., Jordan, M. A., Matuz, T., Furdea, A., Halder, S., Mochty, U., Krusienski, D. J., Vaughan, T. M., et al. (2008) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.03.034 · Cited by 633
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Brain Computer Interfaces, a Review
Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012) · Sensors · doi:10.3390/s120201211 · Cited by 2,143
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
“Two, offline analyses only estimate potential online performance; while they may show that a paradigm is likely to work, only online testing can establish that for certain (Klobassa et al., 2009).”
BackgroundSelf-citationVisual and Auditory Brain–Computer Interfaces
Gao, S., Wang, Y., Gao, X., & Hong, B. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2300164 · Cited by 449
A brain-computer interface for long-term independent home use
Sellers, E. W., Vaughan, T. M., & Wolpaw, J. R. (2010) · Amyotrophic Lateral Sclerosis · doi:10.3109/17482961003777470 · Cited by 400
Self-citationEEG-based brain–computer interfaces
McFarland, D. J., & Wolpaw, J. R. (2017) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2017.11.004 · Cited by 283
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Metadata
- Authors
- Klobassa, D. S., Vaughan, T. M., Brunner, P., Schwartz, N. E., Wolpaw, J. R., Neuper, C., & Sellers, E. W.
- Venue
- Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 120
- Issue
- 7
- Pages
- 1252-1261
- ISSN
- 1388-2457 (ISSN-L)
- OpenAlex
- W2070913574
- Cited by
- 165
- References
- 5
- FWCI
- 8.22
- Type
- journal article
- Language
- en
- Open access
- green
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