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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
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Removal of ballistocardiogram artifacts using the cyclostationary source extraction method.

Foad Ghaderi, Kianoush Nazarpour, John G McWhirter

    IEEE Transactions on Bio-Medical Engineering
    |July 27, 2010
    PubMed
    Summary

    Cyclostationary source extraction (CSE) effectively removes ballistocardiogram (BCG) artifact from electroencephalogram (EEG) signals. This novel method preserves background EEG and eliminates the need for electrocardiogram (ECG) data.

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    Cortical Source Analysis of High-Density EEG Recordings in Children
    09:32

    Cortical Source Analysis of High-Density EEG Recordings in Children

    Published on: June 30, 2014

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Neuroscience

    Background:

    • Ballistocardiogram (BCG) artifact contaminates electroencephalogram (EEG) recordings, particularly in magnetic resonance (MR) environments.
    • Existing BCG artifact removal methods can degrade the quality of the background EEG signal.
    • The cyclostationary nature of BCG artifact presents a unique characteristic for signal processing.

    Purpose of the Study:

    • To introduce and validate a novel method, cyclostationary source extraction (CSE), for removing BCG artifact from EEG.
    • To demonstrate CSE's effectiveness in preserving background EEG signal quality compared to existing techniques.
    • To apply CSE for cleaning EEG data, specifically visual evoked potentials (VEPs), recorded during MR imaging.

    Main Methods:

    • Proposed cyclostationary source extraction (CSE) method to identify and remove BCG artifact components.
    • Applied CSE to electroencephalogram (EEG) data contaminated with ballistocardiogram (BCG) artifact, including visual evoked potential (VEP) recordings from within an MR scanner.
    • Compared CSE performance against benchmark BCG removal techniques using power spectral density analysis and VEP correlation.

    Main Results:

    • CSE effectively extracts cyclostationary BCG artifact components with minimal destructive impact on background EEG.
    • The proposed CSE method demonstrates superior performance in preserving the integrity of the background EEG signal.
    • Processed VEPs recorded inside the MR scanner using CSE show higher correlation with VEPs recorded outside the scanner.
    • CSE successfully removes BCG artifact frequency components from EEG data without requiring electrocardiogram (ECG) signals.

    Conclusions:

    • Cyclostationary source extraction (CSE) offers an effective and non-destructive approach for removing ballistocardiogram (BCG) artifact from electroencephalogram (EEG) signals.
    • CSE enhances the quality of EEG data, particularly VEPs recorded in challenging MR environments, by preserving background neural activity.
    • The method's ability to compute BCG cycle frequency directly from EEG simplifies the artifact removal process and eliminates reliance on auxiliary ECG data.