Muscle Synergy Assessment During Single-Leg Stance

Area of Science:

• Biomechanics
• Motor Control
• Neuroscience

Background:

• Muscle synergies are fundamental to motor control, but their extraction requires careful signal processing.
• Distinguishing between balanced and unbalanced states in single-leg stance is crucial for accurate muscle synergy analysis.

Purpose of the Study:

• To develop and validate a robust procedure for differentiating "well-balanced" and "unbalanced" single-leg stance epochs from surface electromyography (sEMG) data.
• To ensure this procedure serves as a reliable input for muscle synergy extraction algorithms.

Main Methods:

• The study proposes a method to segment sEMG signals based on balance quality during single-leg stance.
• The robustness of this segmentation was tested against variations in segmentation thresholds.

Main Results:

• The proposed method demonstrated high consistency in the number of muscle synergies identified.
• Weight vectors showed high similarity (0.75–0.97 correlation) between balance conditions.
• Differences in recruitment levels and control strategies suggest distinct modular organizations for balanced vs. unbalanced stance.

Conclusions:

• The developed procedure is a robust pre-processing step for muscle synergy extraction.
• This method enhances the assessment of motor control strategies during single-leg balance tasks.