A noninvasive, log-transform method for fiber type discrimination using mechanomyography

Trent J. Herda, Terry J. Housh, Andrew C. Fry, Joseph P. Weir, Brian K. Schilling, Eric D. Ryan, Joel T. Cramer

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

This study examined the log-transformed mechanomyographic (MMGRMS) and electromyographic (EMGRMS) amplitude vs. force relationships for aerobically-trained (AT), resistance-trained (RT), and sedentary (SED) individuals. Subjects performed isometric ramp contractions from 5% to 90% maximal voluntary contraction. Muscle biopsies were collected and thigh skinfolds, MMG and EMG were recorded from the vastus lateralis muscle. Linear regression models were fit to the log-transformed EMGRMS and MMGRMS vs. force relationships. The slope (b coefficient) and the antilog of the y-intercept (a coefficient) were calculated. The AT group had the highest percentage of type I fiber area, the RT group had the highest percentage of type IIa fiber area, and the SED group had the highest percentage of type IIx fiber area. The a coefficients were higher for the AT group than the RT and SED groups in both the MMGRMS and EMGRMS vs. force relationships, whereas the b coefficients were lower for the AT group than the RT and SED groups only in the MMGRMS vs. force relationship. The group differences among the a coefficients may have reflected subcutaneous fat acting as a filter thereby reducing EMGRMS and MMGRMS. The lower b coefficients for the AT group in the MMGRMS patterns may have reflected fiber area-related differences in motor unit activation strategies.

Original languageEnglish (US)
Pages (from-to)787-794
Number of pages8
JournalJournal of Electromyography and Kinesiology
Volume20
Issue number5
DOIs
StatePublished - Oct 1 2010

Keywords

  • EMG
  • Electromyography
  • MMG
  • Motor unit activation strategies

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biophysics
  • Clinical Neurology

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