Orthogonal Extreme Learning Machine Based P300 Visual Event-Related BCI

Brain Computer Interface (BCI) is a type of human-computer relationship research that directly translates electrical activity of brain into commands that can rule equipment and create novel communication channel for muscular disabled patients. In this study, in order to overcome shortcoming of Singu...

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Bibliographic Details
Published inNeural Information Processing Vol. 9490; pp. 284 - 291
Main Authors Kutlu, Yakup, Yayik, Apdullah, Yildirim, Esen, Yildirim, Serdar
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 01.01.2015
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Brain computer interface
Iteratively optimized neuron number
MoDP method
P300
Pattern recognition
QR decomposition
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Summary:Brain Computer Interface (BCI) is a type of human-computer relationship research that directly translates electrical activity of brain into commands that can rule equipment and create novel communication channel for muscular disabled patients. In this study, in order to overcome shortcoming of Singular Value Decomposition in Extreme Learning Machine, iteratively optimized neuron numbered QR Decomposition technique with different approaches are proposed. QR Decomposition Extreme Learning Machine technique based P300 event-related potential BCI application that achieves almost % 100 classification accuracy with milliseconds is presented. QR decomposition based ELM and novel feature extraction method named Multi Order Difference Plot (MoDP) techniques are milestones of proposed BCI system.
ISBN:9783319265346
3319265342
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-26535-3_33