Interpreting Changes in Surface EMG Amplitude During High-Level Fatiguing Contractions of the Brachioradialis

Abstract

The amplitude of the surface EMG signal may provide a more accurate reflection of motor unit activity during sustained fatiguing contractions than spectral parameters which are more commonly used to estimate muscle fatigue. In this paper, theoretical relationships between surface EMG amplitude measures and mean motor unit firing rates and muscle fiber conduction velocity (MFCV) are established. It is proposed that using these relationships, under conditions where motor unit recruitment and synchronization can be assumed to be negligible, such as at high force levels or in smaller muscles, it may be possible to obtain au estimate of relative changes in motor unit firing rates during a sustained isometric contraction. Using EMG amplitude and MFCV data gathered from the brachioradialis muscle during 8O % maximum voluntary contraction, relative changes iii mean motor unit firing rates were estimated iii this manner. MFCV and the estimated firing rate changes were then incorporated into a model of the surface EMG signal. Simulated EMG data was generated individually for each subject and EMG amplitude and spectral parameters calculated from the simulated and experimental data were found to compare well. velocity, motor ullit firiug rates.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409624

Entities

People

  • M. J. O'malley
  • M. Lowery
  • M. Rybansky

Organizations

  • Shirley Ryan AbilityLab

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Amplitude
  • Data Analysis
  • Electrical Engineering
  • Electrodes
  • Engineering
  • Experimental Data
  • Firing Rate
  • Frequency
  • Information Science
  • Load Cells
  • Muscle Fibers
  • Musculoskeletal Physiology
  • Physical Properties
  • Power Spectra
  • Simulations
  • Spectra
  • Standards

Readers

  • Acoustics.
  • Computational Modeling and Simulation
  • Exercise and Sports Science.