Detection and classification of subject-generated artifacts in EEG signals using autoregressive models

We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can be tedious, time-consuming and infeasible for large datasets. We use autoregressive (AR) models for feature ex...

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Bibliografski detalji
Glavni autori: Vernon J. Lawhern, W. David Hairston, Kaleb McDowell, Marissa Westerfield, Kay A. Robbins
Format: Artigo
Jezik:engleski
Izdano: 2012
Online pristup:https://doi.org/10.1016/j.jneumeth.2012.05.017
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