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A Time-Frequency Approach for the Assessment of Dynamic Muscle Co-contractions

  • Annachiara Strazza
  • Federica Verdini
  • Alessandro Mengarelli
  • Stefano Cardarelli
  • Laura Burattini
  • Sandro Fioretti
  • Francesco Di Nardo
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 68/2)

Abstract

Co-contraction is defined as the activity of agonist and antagonist muscles around a joint, enhancing stability and balance. The quantitative assessment of muscle co-contractions would be meaningful for deepening the comprehension of this physiological mechanism. Thus, the purpose of this work is to quantify muscle co-contraction using energy localization in time-frequency domain of sEMG signal during straight walking. To this purpose, sEMG from tibialis anterior (TA) and gastrocnemius lateralis (GL) and basographic signals were acquired in five healthy subjects during walking. Basographic signals were analyzed to quantify foot-floor contact. sEMG signals were processed using Wavelet Transform (WT) to identify muscular co-contractions, according to the following steps. Daubechies (order 4 with 6 levels of decomposition) was chosen as mother wavelet. A denoising algorithm based on Daubechies mother wavelet was applied for removing noise from raw signals. Denoised signals were decomposed into WT coefficients with different frequency content, and then recombined to achieve the co-scalogram function, a localized statistical assessment of cross-energy density between signals. The localization of regions with maximum cross-energy density provided the assessment of co-contractions in time-frequency domain. This methodology applied to TA and GL signals was able to detect GL/TA co-contractions during mid-stance (30–34% of GC) phase, matching with literature. Moreover, WT approach was able to provide also the frequency band of information content for muscle co-contractions: 65–164 Hz. In conclusion, this study proposed WT cross-energy density as a reliable estimation of muscle co-contraction in time-frequency domain.

Keywords

sEMG Time-frequency analysis Muscle co-contraction 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Annachiara Strazza
    • 1
  • Federica Verdini
    • 1
  • Alessandro Mengarelli
    • 1
  • Stefano Cardarelli
    • 1
  • Laura Burattini
    • 1
  • Sandro Fioretti
    • 1
  • Francesco Di Nardo
    • 1
  1. 1.Department of Information EngineeringUniversità Politecnica delle MarcheAnconaItaly

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