• DocumentCode
    139820
  • Title

    Evaluation of HD-sEMG Probability Density Function deformations in ramp exercise

  • Author

    Al Harrach, M. ; Boudaoud, S. ; Gamet, D. ; Grosset, J.F. ; Marin, Frederic

  • Author_Institution
    BMBI, Univ. de Technol. de Compiegne, Compiègne, France
  • fYear
    2014
  • fDate
    26-30 Aug. 2014
  • Firstpage
    2209
  • Lastpage
    2212
  • Abstract
    The aim of the present study is to propose a subject-specific screening approach of High Density surface EMG (HD-sEMG) Probability Density Function (PDF) shape evolution in experimental conditions following a ramp exercise from 0% to 50% of the Maximum Voluntary Contraction (MVC) during 25 seconds of isometric contractions of the Biceps Brachii from six healthy subjects. This method uses High Order Statistics (HOS), namely the kurtosis and the skewness for PDF shape screening examined on selectively positioned Laplacian sEMG channels obtained on an 8×8 HD-sEMG grid. For each subject, the position of the Laplacian channels was chosen based on the level of muscle activation obtained from the Signal to Noise Ratio (SNR) matrix computed for the 64 sEMG signals of the grid in order to obtain independent Laplacian configurations localized in areas with high SNRs indicating high muscle activation. Afterwards, we used the Principal Component Analysis (PCA) to obtain the principal trend of the kurtosis and the skewness computed from the selected Laplacian signals according to force level variation. The obtained results show a globally common increasing HOS trend according to force increase from 0% to 50% MVC for all the subjects regardless of the anatomical, instrumental and physiological variability that usually strongly influences these trends.
  • Keywords
    biomechanics; electromyography; higher order statistics; medical signal processing; principal component analysis; probability; HD-sEMG probability density function deformation; HOS; Laplacian configurations; Laplacian signals; PCA; PDF shape screening; SNR; anatomical variability; biceps brachii; force level variation; high density surface EMG probability density function shape evolution; high order statistics; instrumental variability; isometric contractions; kurtosis; maximum voluntary contraction; muscle activation; physiological variability; principal component analysis; ramp exercise; sEMG signals; selectively positioned Laplacian sEMG channels; signal-to-noise ratio; skewness; subject-specific screening approach; surface electromyography; Force; Laplace equations; Market research; Muscles; Principal component analysis; Shape; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2014.6944057
  • Filename
    6944057