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Muscle Synergies Extracted Using Principal Activations: Improvement of Robustness and Interpretability

Marco Ghislieri, Valentina Agostini, Marco Knaflitz

2020IEEE Transactions on Neural Systems and Rehabilitation Engineering45 citationsDOIOpen Access PDF

Abstract

The muscle synergy theory has been widely used to assess the modular organization of the central nervous system (CNS) during human locomotion. The pre-processing approach applied to the surface electromyographic (sEMG) signals influences the extraction of muscle synergies. The aim of this contribution is to assess the improvements in muscle synergy extraction obtained by using an innovative pre-processing approach. We evaluate the improvement in terms of the possible variation in the number of muscle synergies, of the intra-subject consistency, of the robustness, and of the interpretability of the results. The pre-processing approach presented in this paper is based on the extraction of the muscle principal activations (muscle activations strictly necessary to accomplish a specific biomechanical task) from the original sEMG signals, to then obtain muscle synergies using principal activations only. The results herein presented show that the application of this novel approach for the extraction of the muscle synergies provides a more robust and easily interpretable description of the modular organization of the CNS with respect to the standard pre-processing approach.

Topics & Concepts

InterpretabilityRobustness (evolution)Computer scienceModular designArtificial intelligenceElectromyographyPattern recognition (psychology)Machine learningNeuroscienceBiologyOperating systemBiochemistryGeneMuscle activation and electromyography studiesMotor Control and AdaptationEEG and Brain-Computer Interfaces
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