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Related Experiment Video

Updated: Dec 6, 2025

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
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Reliability of Electroencephalogram-Based Individual Markers - Case Study.

Tuuli Uudeberg, Laura Paeske, Hiie Hinrikus

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    |October 6, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Electroencephalogram (EEG) markers show stable individual variability, suggesting potential for diagnosing brain disorders. This stability is lower than differences observed between healthy and depressed individuals.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Electroencephalogram (EEG) is a key tool for studying brain activity.
    • Assessing individual variability in EEG markers is crucial for clinical applications.
    • Previous studies highlighted differences in EEG markers between healthy and depressed groups.

    Purpose of the Study:

    • To evaluate the natural intra-individual variability of selected EEG-based markers.
    • To determine the reliability of EEG markers for individual-level brain activity assessment.
    • To explore the potential of EEG markers in diagnosing mental disorders.

    Main Methods:

    • Selected linear EEG markers: alpha power variability, spectral asymmetry index, relative gamma power.
    • Selected nonlinear EEG markers: Higuchi's fractal dimension, detrended fluctuation analysis, Lempel-Ziv complexity.
    • Evaluated markers across 15 sessions spanning 14 months for individual variability assessment.

    Main Results:

    • Five out of six selected EEG markers exhibited low individual natural variability.
    • The observed intra-individual variability was less than inter-group differences (healthy vs. depressed).
    • This indicates a high degree of stability for these markers at the individual level.

    Conclusions:

    • Stable EEG markers at the individual level show promise for clinical use.
    • EEG-based markers can potentially be used to evaluate disturbances in brain activity.
    • This supports the application of EEG as a novel diagnostic method for mental disorders.