Literature DB >> 22244309

Online use of error-related potentials in healthy users and people with severe motor impairment increases performance of a P300-BCI.

Martin Spüler1, Michael Bensch, Sonja Kleih, Wolfgang Rosenstiel, Martin Bogdan, Andrea Kübler.   

Abstract

OBJECTIVE: To investigate whether error-related potentials can be used to increase information transfer rate of a P3 brain-computer interface (BCI) in healthy and motor-impaired individuals.
METHODS: Extraction and classification of the error-related potential was performed offline on data recorded from six amyotrophic lateral sclerosis (ALS) patients. An online study with 17 healthy and six motor impaired participants followed, using a modified P3 speller to provide explicit feedback of spelled letters. On recognition of error-related potentials, the interface informed users that the incorrect letter was automatically deleted.
RESULTS: The offline cross-validation estimate of P3 speller data of six ALS patients increased bit rate by 0.44 bit/trial. During online copy spelling, the participants increased their bit rate by 0.52 bit/trial with the error correction system (ECS). Some participants performed free spelling and were able to increase their bit rate. Finally, we demonstrated that healthy participants could increase their bit rate by using a classifier pre-trained on other users' data.
CONCLUSIONS: Error-related potentials as a secondary source of information can be used to increase overall bit rate in a P3 BCI. SIGNIFICANCE: The method should be made available to any patient using the P3 BCI for communication.
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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Mesh:

Year:  2012        PMID: 22244309     DOI: 10.1016/j.clinph.2011.11.082

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


  25 in total

1.  A P300-based brain-computer interface aimed at operating electronic devices at home for severely disabled people.

Authors:  Rebeca Corralejo; Luis F Nicolás-Alonso; Daniel Alvarez; Roberto Hornero
Journal:  Med Biol Eng Comput       Date:  2014-08-28       Impact factor: 2.602

2.  Increasing BCI communication rates with dynamic stopping towards more practical use: an ALS study.

Authors:  B O Mainsah; L M Collins; K A Colwell; E W Sellers; D B Ryan; K Caves; C S Throckmorton
Journal:  J Neural Eng       Date:  2015-01-14       Impact factor: 5.379

3.  Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers.

Authors:  Boyla O Mainsah; Kenneth D Morton; Leslie M Collins; Eric W Sellers; Chandra S Throckmorton
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2014-11-25       Impact factor: 3.802

4.  P300-based brain-computer interface (BCI) event-related potentials (ERPs): People with amyotrophic lateral sclerosis (ALS) vs. age-matched controls.

Authors:  Lynn M McCane; Susan M Heckman; Dennis J McFarland; George Townsend; Joseph N Mak; Eric W Sellers; Debra Zeitlin; Laura M Tenteromano; Jonathan R Wolpaw; Theresa M Vaughan
Journal:  Clin Neurophysiol       Date:  2015-02-07       Impact factor: 3.708

5.  Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Authors:  Jane E Huggins; Christoph Guger; Brendan Allison; Charles W Anderson; Aaron Batista; Anne-Marie A-M Brouwer; Clemens Brunner; Ricardo Chavarriaga; Melanie Fried-Oken; Aysegul Gunduz; Disha Gupta; Andrea Kübler; Robert Leeb; Fabien Lotte; Lee E Miller; Gernot Müller-Putz; Tomasz Rutkowski; Michael Tangermann; David Edward Thompson
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2014-01

6.  A multimenu system based on the P300 component as a time saving procedure for communication with a brain-computer interface.

Authors:  Joanna Jarmolowska; Marcello M Turconi; Pierpaolo Busan; Jie Mei; Piero P Battaglini
Journal:  Front Neurosci       Date:  2013-03-25       Impact factor: 4.677

7.  Prediction of auditory and visual p300 brain-computer interface aptitude.

Authors:  Sebastian Halder; Eva Maria Hammer; Sonja Claudia Kleih; Martin Bogdan; Wolfgang Rosenstiel; Niels Birbaumer; Andrea Kübler
Journal:  PLoS One       Date:  2013-02-14       Impact factor: 3.240

8.  Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

Authors:  Martin Spüler; Wolfgang Rosenstiel; Martin Bogdan
Journal:  PLoS One       Date:  2012-12-07       Impact factor: 3.240

9.  Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity.

Authors:  Martin Spüler; Christian Niethammer
Journal:  Front Hum Neurosci       Date:  2015-03-26       Impact factor: 3.169

10.  Augmenting intracortical brain-machine interface with neurally driven error detectors.

Authors:  Nir Even-Chen; Sergey D Stavisky; Jonathan C Kao; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neural Eng       Date:  2017-12       Impact factor: 5.379

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