The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.

How to Improve Robustness in Muscle Synergy Extraction

Ghislieri, M.;
2019-01-01

Abstract

The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.
2019
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Berlin, Germany
July 23-27, 2019
Titolo del volume non avvalorato
IEEE
1525
1528
978-1-5386-1311-5
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8856438
Muscle synergies; EMG; electromyography; signal processing; algorithms; CIMAP
Ghislieri, M.; Agostini, V.; Knaflitz, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1718129
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