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Toward a high-throughput auditory P300-based brain–computer interface

Open access
Klobassa, D.S., Vaughan, T.M., Brunner, P., Schwartz, N.E., Wolpaw, J.R., Neuper, C., Sellers, E.W.·2009·Clinical Neurophysiology

Abstract

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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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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CoChat. (2026). Citation check: Toward a high-throughput auditory P300-based brain–computer interface. https://app.cochat.ai/papers/10.1016/j.clinph.2009.04.019
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Klobassa, D. S., Vaughan, T. M., Brunner, P., Schwartz, N. E., Wolpaw, J. R., Neuper, C., & Sellers, E. W. (2009). Toward a high-throughput auditory P300-based brain–computer interface. Clinical Neurophysiology. https://doi.org/10.1016/j.clinph.2009.04.019

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