Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings | Zendy

Cédric GouyPailler | Zendy; Reza Sameni | Zendy; Marco Congedo | Zendy; Christian Jutten | Zendy

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Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings

Author(s) -

Cédric GouyPailler,

Reza Sameni,

Marco Congedo,

Christian Jutten

Publication year - 2009

Publication title -

springer ebooks

Language(s) - English

Resource type - Book series

DOI - 10.1007/978-3-642-00599-2

Subject(s) - artifact (error) , subspace topology , electroencephalography , computer science , decomposition , artificial intelligence , pattern recognition (psychology) , computer vision , speech recognition , neuroscience , psychology , chemistry , organic chemistry

International audienceIn this study, we present a method to remove ocular artifacts from electroencephalographic (EEG) recordings. This method is based on the detection of the EOG activation periods from a reference EOG channel, definition of covariance matrices containing the nonstationary information of the EOG, and applying generalized eigenvalue decomposition (GEVD) onto these matrices to rank the components in order of resemblance with the EOG. An iterative procedure is further proposed to remove the EOG components in a deflation fashion

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