Independent Components Analysis “Artifact Correction” Distorts EEG Phase in Artifact Free Segments
نویسندگان
چکیده
منابع مشابه
Semi-automatic identification of independent components representing EEG artifact.
OBJECTIVE Independent component analysis (ICA) can disentangle multi-channel electroencephalogram (EEG) signals into a number of artifacts and brain-related signals. However, the identification and interpretation of independent components is time-consuming and involves subjective decision making. We developed and evaluated a semi-automatic tool designed for clustering independent components fro...
متن کاملClassification of independent components of EEG into multiple artifact classes.
In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification pe...
متن کاملArtifact removal procedure distorts multifocal electroretinogram.
PURPOSE To study whether the Artifact Removal procedure available for eliminating artifacts in multifocal electroretinograms (mERG) works correctly or not. METHODS A test response was made using a photo-diode circuit. mERGs were recorded from 3 well-trained normal subjects using the Veris III system, and were then analyzed by the procedure that is included in the Veris Science (Artifact Remov...
متن کاملReal-time EEG artifact correction during fMRI using ICA
BACKGROUND Simultaneous acquisition of EEG and fMRI data results in EEG signal contamination by imaging (MR) and ballistocardiogram (BCG) artifacts. Artifact correction of EEG data for real-time applications, such as neurofeedback studies, is the subject of ongoing research. To date, average artifact subtraction (AAS) is the most widespread real-time method used to partially remove BCG and imag...
متن کاملArtifact Removal from EEG Signals
Electroencephalographic (EEG) recordings are often contaminated with several artifacts.Powerline interference and baseline noise is always present in EEG response of every patient. A number of strategies are available to deal with noise effectively both at the time of EEG recording as well as during preprocessing of recorded data. The aim of the paper is to give an overview of the most common s...
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ژورنال
عنوان ژورنال: Journal of Neurology and Neurobiology
سال: 2020
ISSN: 2379-7150
DOI: 10.16966/2379-7150.172