Literature DB >> 23466266

Gaze-independent BCI-spelling using rapid serial visual presentation (RSVP).

Laura Acqualagna1, Benjamin Blankertz.   

Abstract

OBJECTIVE: A Brain Computer Interface (BCI) speller is a communication device, which can be used by patients suffering from neurodegenerative diseases to select symbols in a computer application. For patients unable to overtly fixate the target symbol, it is crucial to develop a speller independent of gaze shifts. In the present online study, we investigated rapid serial visual presentation (RSVP) as a paradigm for mental typewriting.
METHODS: We investigated the RSVP speller in three conditions, regarding the Stimulus Onset Asynchrony (SOA) and the use of color features. A vocabulary of 30 symbols was presented one-by-one in a pseudo random sequence at the same location of display.
RESULTS: All twelve participants were able to successfully operate the RSVP speller. The results show a mean online spelling rate of 1.43 symb/min and a mean symbol selection accuracy of 94.8% in the best condition.
CONCLUSION: We conclude that the RSVP is a promising paradigm for BCI spelling and its performance is competitive with the fastest gaze-independent spellers in literature. SIGNIFICANCE: The RSVP speller does not require gaze shifts towards different target locations and can be operated by non-spatial visual attention, therefore it can be considered as a valid paradigm in applications with patients for impaired oculo-motor control.
Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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Mesh:

Year:  2013        PMID: 23466266     DOI: 10.1016/j.clinph.2012.12.050

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  32 in total

1.  An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling.

Authors:  Mohammad Moghadamfalahi; Murat Akcakaya; Hooman Nezamfar; Jamshid Sourati; Deniz Erdogmus
Journal:  IEEE Trans Signal Process       Date:  2017-07-17       Impact factor: 4.931

Review 2.  Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.

Authors:  Kevin M Pitt; Jonathan S Brumberg
Journal:  Am J Speech Lang Pathol       Date:  2018-08-06       Impact factor: 2.408

3.  Recursive Bayesian Coding for BCIs.

Authors:  Matt Higger; Fernando Quivira; Murat Akcakaya; Mohammad Moghadamfalahi; Hooman Nezamfar; Mujdat Cetin; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-07-13       Impact factor: 3.802

4.  An ERP-based BCI with peripheral stimuli: validation with ALS patients.

Authors:  Yangyang Miao; Erwei Yin; Brendan Z Allison; Yu Zhang; Yan Chen; Yi Dong; Xingyu Wang; Dewen Hu; Andrzej Chchocki; Jing Jin
Journal:  Cogn Neurodyn       Date:  2019-06-11       Impact factor: 5.082

Review 5.  Brain-Computer Interfaces for Augmentative and Alternative Communication: A Tutorial.

Authors:  Jonathan S Brumberg; Kevin M Pitt; Alana Mantie-Kozlowski; Jeremy D Burnison
Journal:  Am J Speech Lang Pathol       Date:  2018-02-06       Impact factor: 2.408

6.  Probabilistic Simulation Framework for EEG-Based BCI Design.

Authors:  Umut Orhan; Hooman Nezamfar; Murat Akcakaya; Deniz Erdogmus; Matt Higger; Mohammad Moghadamfalahi; Andrew Fowler; Brian Roark; Barry Oken; Melanie Fried-Oken
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2016-12-05

Review 7.  Integrating language models into classifiers for BCI communication: a review.

Authors:  W Speier; C Arnold; N Pouratian
Journal:  J Neural Eng       Date:  2016-05-06       Impact factor: 5.379

8.  Neural Point-and-Click Communication by a Person With Incomplete Locked-In Syndrome.

Authors:  Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; Sergey D Stavisky; John D Simeral; Katherine Newell; Erin M Oakley; Sydney S Cash; Gerhard Friehs; Leigh R Hochberg
Journal:  Neurorehabil Neural Repair       Date:  2014-11-10       Impact factor: 3.919

Review 9.  Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.

Authors:  Lichao Xu; Minpeng Xu; Tzyy-Ping Jung; Dong Ming
Journal:  Cogn Neurodyn       Date:  2021-04-10       Impact factor: 3.473

10.  Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state.

Authors:  Tobias Kaufmann; Elisa M Holz; Andrea Kübler
Journal:  Front Neurosci       Date:  2013-07-24       Impact factor: 4.677

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