An Experimental and Model Based Investigation of the Potential and Limitations of Surface EMG Spectral Analysis for Assessment of Motor Unit Recruitment Strategy

Abstract

Characteristic frequencies of surface EMG power spectrum have been used in the past as indicative of motor unit (MU) recruitment, since they are rather insensitive to changes of MU firing rates and this they should remain constant when only rate coding is used to modulate muscle force. However, this speculation has not been yet validated by simulated and experimental data. In this paper, a model of surface EMG signal generation and detection is used to simulate EMG signals detected during linearly increasing force contractions. Different MU control strategies (corresponding to different ways for force generation by recruitment mid rate coding) are simulated. A number of simulations are performed to study the effect of random distribution of MUs in the muscles cross-section upon the surface EMG. The results are compared with those obtained analyzing the EMG signals detected experimentally during linearly increasing force contractions of the biceps brachii muscle in 10 subjects. Results show that the volume conductor properties may act as confounding factors which may mask ally relationship between characteristic spectral frequencies mid conduction velocity as a size principle parameter. It is concluded that more advanced signal processing techniques which aim at the analysis of single MU activity are required for the surface EMG based assessment of central nervous system control strategy.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409741

Entities

People

  • D. Farina
  • R. Merletti

Organizations

  • Polytechnic University of Turin

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Central Nervous System
  • Computer Programming
  • Electrodes
  • Electromyography
  • Engineering
  • Experimental Data
  • Firing Rate
  • Frequency
  • Intervals
  • Muscles
  • Nervous System
  • Neurology
  • Power Spectra
  • Signal Processing
  • Simulations
  • Spectra
  • Standards

Fields of Study

  • Engineering

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Neuroscience