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A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks

A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another,...

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Detalles Bibliográficos
Autores principales: Geng, Tao, Gan, John Q., Dyson, Matthew, Tsui, Chun SL, Sepulveda, Francisco
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2435224/
https://www.ncbi.nlm.nih.gov/pubmed/18584040
http://dx.doi.org/10.1155/2008/437306
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author Geng, Tao
Gan, John Q.
Dyson, Matthew
Tsui, Chun SL
Sepulveda, Francisco
author_facet Geng, Tao
Gan, John Q.
Dyson, Matthew
Tsui, Chun SL
Sepulveda, Francisco
author_sort Geng, Tao
collection PubMed
description A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms.
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spelling pubmed-24352242008-06-26 A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks Geng, Tao Gan, John Q. Dyson, Matthew Tsui, Chun SL Sepulveda, Francisco Comput Intell Neurosci Research Article A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms. Hindawi Publishing Corporation 2008 2008-06-22 /pmc/articles/PMC2435224/ /pubmed/18584040 http://dx.doi.org/10.1155/2008/437306 Text en Copyright © 2008 Tao Geng et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Geng, Tao
Gan, John Q.
Dyson, Matthew
Tsui, Chun SL
Sepulveda, Francisco
A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title_full A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title_fullStr A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title_full_unstemmed A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title_short A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks
title_sort novel design of 4-class bci using two binary classifiers and parallel mental tasks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2435224/
https://www.ncbi.nlm.nih.gov/pubmed/18584040
http://dx.doi.org/10.1155/2008/437306
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