Optimal Identification of Muscle Synergies From Typical Sit-to-Stand Clinical Tests

Area of Science:

• Biomechanics
• Neuroscience
• Motor Control

Background:

• Muscle synergies represent fundamental neural control strategies for movement.
• The sit-to-stand (STS) movement is a common functional task used in clinical assessments.
• Extracting reliable muscle synergy information from clinical tests is crucial for understanding motor control.

Purpose of the Study:

• To determine optimal methods for extracting muscle synergies from STS test data.
• To evaluate the impact of signal duration on the identification of modular motor structures.
• To assess the consistency of muscle synergy extraction across different phases of the STS cycle.

Main Methods:

• Surface electromyography (sEMG) signals were recorded during instrumented STS trials.
• Muscle synergies were extracted from sEMG signals of varying durations (5x STS and 30s STS).
• A modified Akaike Information Criterion was used to determine the optimal number of synergies.

Main Results:

• Accurate identification of muscle synergies is possible even with relatively short sEMG signal durations.
• Motor control structure identification showed higher consistency when analyzing only the sit-to-stand phase.
• Cross-validation procedures confirmed the reliability of the extraction methods.

Conclusions:

• Optimal methods for muscle synergy extraction from the STS test enhance clinical applicability.
• Synergy-related analysis can be reliably performed in clinical practice without deep signal processing expertise.
• Standardized methods for synergy extraction from functional tests are essential for clinical translation.