Literature DB >> 21436523

P300 audio-visual speller.

A Belitski1, J Farquhar, P Desain.   

Abstract

The Farwell and Donchin matrix speller is well known as one of the highest performing brain-computer interfaces (BCIs) currently available. However, its use of visual stimulation limits its applicability to users with normal eyesight. Alternative BCI spelling systems which rely on non-visual stimulation, e.g. auditory or tactile, tend to perform much more poorly and/or can be very difficult to use. In this paper we present a novel extension of the matrix speller, based on flipping the letter matrix, which allows us to use the same interface for visual, auditory or simultaneous visual and auditory stimuli. In this way we aim to allow users to utilize the best available input modality for their situation, that is use visual + auditory for best performance and move smoothly to purely auditory when necessary, e.g. when disease causes the user's eyesight to deteriorate. Our results on seven healthy subjects demonstrate the effectiveness of this approach, with our modified visual + auditory stimulation slightly out-performing the classic matrix speller. The purely auditory system performance was lower than for visual stimulation, but comparable to other auditory BCI systems.

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Mesh:

Year:  2011        PMID: 21436523     DOI: 10.1088/1741-2560/8/2/025022

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  23 in total

1.  An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps.

Authors:  Minqiang Huang; Ian Daly; Jing Jin; Yu Zhang; Xingyu Wang; Andrzej Cichocki
Journal:  Cogn Neurodyn       Date:  2016-01-23       Impact factor: 5.082

2.  Identifying the Attended Speaker Using Electrocorticographic (ECoG) Signals.

Authors:  K Dijkstra; P Brunner; A Gunduz; W Coon; A L Ritaccio; J Farquhar; G Schalk
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2015-08-26

3.  An online brain-computer interface based on shifting attention to concurrent streams of auditory stimuli.

Authors:  N J Hill; B Schölkopf
Journal:  J Neural Eng       Date:  2012-02-15       Impact factor: 5.379

4.  Communication and control by listening: toward optimal design of a two-class auditory streaming brain-computer interface.

Authors:  N Jeremy Hill; Aisha Moinuddin; Ann-Katrin Häuser; Stephan Kienzle; Gerwin Schalk
Journal:  Front Neurosci       Date:  2012-12-19       Impact factor: 4.677

5.  Listen, You are Writing! Speeding up Online Spelling with a Dynamic Auditory BCI.

Authors:  Martijn Schreuder; Thomas Rost; Michael Tangermann
Journal:  Front Neurosci       Date:  2011-10-14       Impact factor: 4.677

6.  A Novel Audiovisual Brain-Computer Interface and Its Application in Awareness Detection.

Authors:  Fei Wang; Yanbin He; Jiahui Pan; Qiuyou Xie; Ronghao Yu; Rui Zhang; Yuanqing Li
Journal:  Sci Rep       Date:  2015-06-30       Impact factor: 4.379

7.  Decoding of single-trial auditory mismatch responses for online perceptual monitoring and neurofeedback.

Authors:  Alex Brandmeyer; Makiko Sadakata; Loukianos Spyrou; James M McQueen; Peter Desain
Journal:  Front Neurosci       Date:  2013-12-30       Impact factor: 4.677

8.  Exploring combinations of auditory and visual stimuli for gaze-independent brain-computer interfaces.

Authors:  Xingwei An; Johannes Höhne; Dong Ming; Benjamin Blankertz
Journal:  PLoS One       Date:  2014-10-28       Impact factor: 3.240

9.  Decoding speech perception by native and non-native speakers using single-trial electrophysiological data.

Authors:  Alex Brandmeyer; Jason D R Farquhar; James M McQueen; Peter W M Desain
Journal:  PLoS One       Date:  2013-07-11       Impact factor: 3.240

10.  Towards a communication brain computer interface based on semantic relations.

Authors:  Jeroen Geuze; Jason Farquhar; Peter Desain
Journal:  PLoS One       Date:  2014-02-07       Impact factor: 3.240

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