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Related Experiment Video

Updated: Jul 24, 2025

Standing Neurophysiological Assessment of Lower Extremity Muscles Post-Stroke
08:23

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Lower-Limb Non-Parametric Functional Muscle Network: Test-Retest Reliability Analysis.

Rory O'Keeffe, Jinghui Yang, Sarmad Mehrdad

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |July 3, 2023
    PubMed
    Summary
    This summary is machine-generated.

    Functional muscle network analysis shows high test-retest reliability for lower-limb tasks. These network metrics offer reliable biomarkers for rehabilitation, outperforming traditional surface electromyography (sEMG) measures.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Rehabilitation Science

    Background:

    • Functional muscle network analysis shows promise for detecting intermuscular synchronicity changes.
    • Reliability of these network measures, particularly between and within sessions, remains largely unestablished.
    • Previous studies focused mainly on healthy subjects and neurological conditions.

    Purpose of the Study:

    • To evaluate the test-retest reliability of non-parametric lower-limb functional muscle networks.
    • To compare the reliability of network metrics with traditional surface electromyography (sEMG) measures.
    • To assess reliability for both controlled (sit-to-stand) and lightly controlled (walking) tasks in healthy individuals.

    Main Methods:

    • Fifteen healthy subjects participated in two test sessions on separate days.
    • Muscle activity was recorded using 14 surface electromyography (sEMG) sensors.
    • Intraclass correlation coefficient (ICC) was calculated for network metrics (degree, clustering coefficient) and sEMG measures (RMS, MDF).

    Main Results:

    • Functional muscle networks demonstrated superior between-session reliability compared to traditional sEMG measures (RMS, MDF).
    • Statistically significant differences in reliability were observed between network metrics and classical measures.
    • Topographical metrics from functional muscle networks achieved reliable measurements with a low number of sessions.

    Conclusions:

    • Topographical metrics from functional muscle networks can be reliably used for multi-session observations.
    • These metrics reliably quantify synergistic intermuscular synchronicity in lower limb tasks.
    • Functional muscle network metrics show potential as reliable biomarkers for rehabilitation monitoring.