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Automatic artifact suppression in simultaneous tDCS-EEG using adaptive filtering.

Matteo Mancini, Maria Concetta Pellicciari, Debora Brignani

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed
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    This study introduces an automated method to remove artifacts from electroencephalography (EEG) signals during transcranial direct current stimulation (tDCS). The adaptive filtering approach successfully cleans neural data, enabling clearer insights into tDCS mechanisms.

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Transcranial direct current stimulation (tDCS) is a non-invasive brain modulation technique.
    • Understanding tDCS's neural mechanisms requires simultaneous electroencephalography (EEG) recordings.
    • tDCS-EEG recordings are hindered by significant signal artifacts.

    Purpose of the Study:

    • To develop an automated method for canceling tDCS-induced artifacts in EEG signals.
    • To enable clearer neural recordings during tDCS for mechanism investigation.
    • To validate the artifact cancellation method in both phantom and human studies.

    Main Methods:

    • An automated artifact cancellation technique utilizing adaptive filtering.
    • Independent Component Analysis (ICA) was employed to characterize tDCS artifacts.

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  • The method was tested using data from a phantom setup and healthy human subjects.

    • Main Results:

    • The proposed adaptive filtering method effectively identified and characterized tDCS artifacts.
    • Successful removal of artifacts was demonstrated for both anodal and cathodal tDCS.
    • The developed filter significantly improves the quality of simultaneous tDCS-EEG recordings.

    Conclusions:

    • The automated artifact cancellation method provides a robust solution for tDCS-EEG studies.
    • This technique facilitates a deeper understanding of the neural mechanisms underlying tDCS.
    • The findings pave the way for more reliable neuroscientific research using combined tDCS-EEG.