Detection of intermuscular coordination based on the causality of empirical mode decomposition

Carlos Cruz-Montecinos, Xavier García-Massó, Huub Maas, Mauricio Cerda, Javier Ruiz-del-Solar, Claudio Tapia*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

Considering the stochastic nature of electromyographic (EMG) signals, nonlinear methods may be a more accurate approach to study intermuscular coordination than the linear approach. The aims of this study were to assess the coordination between two ankle plantar flexors using EMG by applying the causal decomposition approach and assessing whether the intermuscular coordination is affected by the slope of the treadmill. The medial gastrocnemius (MG) and soleus muscles (SOL) were analyzed during the treadmill walking at inclinations of 0°, 5°, and 10°. The coordination was evaluated using ensemble empirical mode decomposition, and the causal interaction was encoded by the instantaneous phase dependence of time series bi-directional causality. To estimate the mutual predictability between MG and SOL, the cross-approximate entropy (XApEn) was assessed. The maximal causal interaction was observed between 40 and 75 Hz independent of inclination. XApEn showed a significant decrease between 0° and 5° (p = 0.028), between 5° and 10° (p = 0.038), and between 0° and 10° (p = 0.014), indicating an increase in coordination. Thus, causal decomposition is an appropriate methodology to study intermuscular coordination. These results indicate that the variation of loading through the change in treadmill inclination increases the interaction of the shared input between MG and SOL, suggesting increased intermuscular coordination. Graphical abstract: [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)497-509
Number of pages13
JournalMedical and Biological Engineering and Computing
Volume61
Issue number2
Early online date17 Dec 2022
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Funding Information:
MC is partially supported by Iniciativa Cientifica Milenio ICM P09-015F, FONDECYT 1211988, FONDEF ID20I10371, PIA ACT192015, and DAAD 57220037 and 57168868.

Publisher Copyright:
© 2022, International Federation for Medical and Biological Engineering.

Funding

MC is partially supported by Iniciativa Cientifica Milenio ICM P09-015F, FONDECYT 1211988, FONDEF ID20I10371, PIA ACT192015, and DAAD 57220037 and 57168868.

FundersFunder number
Iniciativa Cientifica MilenioICM P09-015F
Fondo Nacional de Desarrollo Científico y Tecnológico1211988
Fondo Nacional de Desarrollo Científico y Tecnológico
Fondo de Fomento al Desarrollo Científico y TecnológicoID20I10371, PIA ACT192015, 57168868, DAAD 57220037
Fondo de Fomento al Desarrollo Científico y Tecnológico

    Keywords

    • Causality analysis
    • EMG
    • Empirical mode decomposition
    • Gait
    • Muscle synergy

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