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Improving test-retest reliability of quantitative electroencephalography using different preprocessing approaches.

Jazmin Suarez-Revelo, John Ochoa-Gomez, Jon Duque-Grajales

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed
    Summary

    Preprocessing methods significantly impact electroencephalography (EEG) reliability. Optimal approaches, including robust referencing and independent component analysis, enhance test-retest reliability for quantitative EEG in longitudinal studies.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Quantitative electroencephalography (qEEG) is a valuable tool for studying brain activity.
    • Assessing the test-retest reliability of qEEG measurements is crucial for longitudinal research.
    • Preprocessing steps can influence the reliability of neurophysiological data.

    Purpose of the Study:

    • To evaluate how different preprocessing techniques affect the test-retest reliability of qEEG.
    • To identify optimal preprocessing strategies for enhancing the stability of qEEG measures.
    • To determine the suitability of qEEG for longitudinal studies based on reliability.

    Main Methods:

    • Two resting-state electroencephalography (EEG) sessions were conducted with a 4-6 week interval in 15 healthy young adults.
    • Various common preprocessing approaches were applied to obtain clean EEG recordings.
    • Power spectrum density was calculated for six frequency bands (delta, theta, alpha1, alpha2, beta, gamma).
    • Intraclass correlation coefficient (ICC) was used to assess test-retest reliability for each preprocessing method and frequency band.

    Main Results:

    • Test-retest reliability of qEEG varied significantly across different frequency bands and preprocessing methods.
    • Higher reliability was observed in the theta, alpha1, and alpha2 frequency bands.
    • Preprocessing incorporating robust average referencing and independent component analysis improved reliability in beta and gamma bands.

    Conclusions:

    • Quantitative electroencephalography measurements demonstrate good test-retest reliability.
    • Specific preprocessing strategies, such as robust average referencing and ICA, can optimize qEEG reliability.
    • The findings support the use of qEEG in longitudinal research designs for tracking brain changes over time.