Removing Electroencephalographic Artifacts : Comparison between Ica and Pca

  title={Removing Electroencephalographic Artifacts : Comparison between Ica and Pca},
  author={Tzyy-Ping Jung and Colin Humphries and Te-Won Lee and Scott Makeig and Martin J. McKeown and Vicente Iragui and Terrence J. Sejnowski},
Pervasive electroencephalographic (EEG) artifacts associated with blinks, eye-movements, muscle noise, cardiac signals , and line noise poses a major challenge for EEG interpretation and analysis. Here, we propose a generally applicable method for removing a wide variety of artifacts from EEG records based on an extended version of an Independent Component Analysis (ICA) algorithm 2, 12] for performing blind source separation on linear mixtures of independent source signals. Our results show… CONTINUE READING
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