Comparison of the fast Fourier transform and continuous wavelet transform for examining mechanomyographic frequency versus eccentric torque relationships

Travis W. Beck, Terry J. Housh, Glen O. Johnson, Joel T. Cramer, Joseph P. Weir, Jared W. Coburn, Moh H. Malek

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The purpose of this study was to compare the eccentric torque-related patterns for mechanomyographic (MMG) center frequencies (mean power frequency (MPF), median frequency (MDF), and average instantaneous mean power frequency (AIMPF)) determined by the fast Fourier transform (FFT) and continuous wavelet transform (CWT). Eight adults (mean ± S.D. age = 22.5 ± 2.4 years) performed submaximal to maximal, eccentric isokinetic muscle actions of the biceps brachii on a Cybex 6000 dynamometer. The mean MMG MPF, MDF, and AIMPF values for both the absolute and normalized data from 10 to 100% eccentric peak torque (PT) were highly intercorrelated at r = 0.908-0.985. Linear models provided the best fit for the absolute MMG MPF (r = 0.873), MDF (r = 0.831), and AIMPF (r = 0.924), as well as normalized MMG MPF (r = 0.869), MDF (r = 0.816), and AIMPF (r = 0.920) versus percentage eccentric PT relationships. There were no significant differences (p > 0.05) among the linear slope coefficients for the MMG MPF, MDF, and AIMPF versus percentage eccentric PT relationships for either the absolute or normalized data. These results suggested that Fourier or wavelet transform procedures can be used to examine the patterns of MMG responses during eccentric muscle actions of the biceps brachii.

Original languageEnglish (US)
Pages (from-to)59-66
Number of pages8
JournalJournal of Neuroscience Methods
Volume150
Issue number1
DOIs
StatePublished - Jan 15 2006

Keywords

  • Eccentric isokinetic torque
  • Fourier transform
  • Mechanomyography
  • Wavelet transform

ASJC Scopus subject areas

  • Neuroscience(all)

Fingerprint Dive into the research topics of 'Comparison of the fast Fourier transform and continuous wavelet transform for examining mechanomyographic frequency versus eccentric torque relationships'. Together they form a unique fingerprint.

  • Cite this