Lower-limb Nonparametric Functional Muscle Network: Test-retest Reliability Analysis

Area of Science:

• Biomechanics
• Neuroscience
• Rehabilitation Engineering

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 primarily focused on healthy subjects, with recent extensions to neurological conditions.

Approach:

• Investigated the test-retest reliability of non-parametric lower-limb functional muscle networks.
• Included controlled (sit-to-stand) and lightly controlled (over-the-ground walking) tasks in healthy subjects.
• Quantified reliability using intraclass correlation coefficient (ICC) for network metrics and compared with surface electromyography (sEMG) root mean square (RMS) and median frequency (MDF).

Key Points:

• Muscle network analysis demonstrated superior between-session reliability compared to classical sEMG measures (RMS, MDF).
• Topographical metrics from functional muscle networks reliably quantify synergistic intermuscular synchronicity in lower limb tasks.
• Network metrics achieved reliable measurements with fewer sessions, suggesting potential as rehabilitation biomarkers.

Conclusions:

• Functional muscle network analysis provides a reliable method for multi-session observations of intermuscular synchronicity.
• The findings support the use of these network metrics as sensitive biomarkers in rehabilitation settings.
• This study establishes a foundation for utilizing functional muscle networks in clinical and research applications.