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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-436dc055-83b9-44ad-a324-7fa1237da294

Czasopismo

Biocybernetics and Biomedical Engineering

Tytuł artykułu

Multi-objective binary DE algorithm for optimizing the performance of Devanagari script-based P300 speller

Autorzy Chaurasiya, R. K.  Londhe, N. D.  Ghosh, S. 
Treść / Zawartość http://www.ibib.waw.pl/pl/wydawnictwa/biocybernetics-and-biomedical-enginering-bbe/bbe-tomy http://www.journals.elsevier.com/biocybernetics-and-biomedical-engineering/
Warianty tytułu
Języki publikacji EN
Abstrakty
EN P300 speller-based brain-computer interface (BCI) allows a person to communicate with a computer using only brain signals. In order to achieve better reliability and user continence, it is desirable to have a system capable of providing accurate classification with as few EEG channels as possible. This article proposes an approach based on multi-objective binary differential evolution (MOBDE) algorithm to optimize the system accuracy and number of EEG channels used for classification. The algorithm on convergence provides a set of pareto-optimal solutions by solving the trade-off between the classification accuracy and the number of channels for Devanagari script (DS)-based P300 speller system. The proposed method is evaluated on EEG data acquired from 9 subjects using a 64 channel EEG acquisition device. The statistical analysis carried out in the article, suggests that the proposed method not only increases the classification accuracy but also increases the over-all system reliabil-ity in terms of improved user-convenience and information transfer rate (ITR) by reducing the EEG channels. It was also revealed that the proposed system with only 16 channels was able to achieve higher classification accuracy than a system which uses all 64 channel's data for feature extraction and classification.
Słowa kluczowe
PL interfejs mózg-komputer   optymalizacja wielokryterialna   P300   maszyna wektorów wspierających  
EN brain computer interface   Devanagari script   multiobjective optimization   binary DE   P300 speller   support vector machine  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Elsevier
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 422--431
Opis fizyczny Bibliogr. 38 poz., rys., tab., wykr.
Twórcy
autor Chaurasiya, R. K.
  • Department of Electronics and Telecommunication Engineering, National Institute of Technology, Raipur, Raipur-C.G, PIN-492010, India, rkchaurasiya@nitrr.ac.in
autor Londhe, N. D.
autor Ghosh, S.
Bibliografia
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Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-436dc055-83b9-44ad-a324-7fa1237da294
Identyfikatory
DOI 10.1016/j.bbe.2017.04.006