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Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and(More)
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(More)
Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, and muscle, heart and line noise presents a serious problem for EEG interpretation and analysis. Rejecting contaminated EEG segments results in a considerable loss of data and may be impractical for clinical data. Many methods have been proposed to remove eye movement(More)
Despite genetic, morphological and experimental in vivo, data implying fixed abnormalities in patients with absence seizures, attempts to find highly consistent features in the 3-Hz spike-and-wave pattern recorded during sequential seizures from the same subject have been largely unsuccessful. We used a new data decomposition technique called Independent(More)
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