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Muscle Synergy Assessment During Single-Leg Stance

Marco Ghislieri, Marco Knaflitz, Luciana Labanca, Giuseppe Barone, Laura Bragonzoni, Maria Grazia Benedetti, Valentina Agostini

2020IEEE Transactions on Neural Systems and Rehabilitation Engineering25 citationsDOIOpen Access PDF

Abstract

In the study of muscle synergies during the maintenance of single-leg stance there are several methodological issues that must be taken into account before muscle synergy extraction. In particular, it is important to distinguish between epochs of surface electromyography (sEMG) signals corresponding to "well-balanced" and "unbalanced" single-leg stance, since different motor control strategies could be used to maintain balance. The aim of this work is to present and define a robust procedure to distinguish between "well-balanced" and "unbalanced" single-leg stance to be chosen as input for the algorithm used to extract muscle synergies. Our results demonstrate that the proposed approach for the selection of sEMG epochs relative to "well-balanced" and "unbalanced" single-leg stance is robust with respect to the selection of the segmentation threshold, revealing a high consistency in the number of muscle synergies and high similarity among the weight vectors (correlation values range from 0.75 to 0.97). Moreover, differences in terms of average recruitment levels and balance control strategies were detected, suggesting a slightly different modular organization between "well-balanced" and "unbalanced" single-leg stance. In conclusion, this approach can be successfully used as a pre-processing step before muscle synergy extraction, allowing for a better assessment of motor control strategies during the single-leg stance task.

Topics & Concepts

SegmentationBalance (ability)Consistency (knowledge bases)ElectromyographyComputer scienceLeg musclePhysical medicine and rehabilitationTask (project management)Selection (genetic algorithm)Motor controlWork (physics)Artificial intelligencePsychologyMedicineEngineeringNeuroscienceSystems engineeringMechanical engineeringMuscle activation and electromyography studiesMotor Control and AdaptationBalance, Gait, and Falls Prevention
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