Comparison between the degree of motor unit short-term synchronization and recurrence quantification analysis of the surface EMG in two human muscles

J L Dideriksen, Deborah Falla, M Baekgaard, M L Mogensen, K L Steimle, D Farina

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

OBJECTIVE: To verify if non-linear recurrence analysis of the surface EMG is a suitable tool for assessing motor unit short-term synchronization.

METHODS: Surface and intramuscular EMG signals were recorded from the abductor digiti minimi and vastus medialis muscles of 12 and 10 healthy men, respectively, during isometric contractions. In the abductor digiti minimi, EMG signals were additionally recorded after a contraction sustained for 1min at 50% of the maximal force. In both muscles, percent of determinism (%DET) was estimated from the surface EMG and common input strength (CIS) index was computed from motor unit recordings.

RESULTS: For both muscles, CIS did not correlate with %DET (abductor digiti minimi: R(2)=0.11, P=0.12; vastus medialis: R(2)=0.04, P=0.56). Although the values of CIS for the vastus medialis were lower than those of the abductor digiti minimi (P<0.001), the %DET values did not differ between the two muscles (71.6+/-5.5% vs 66.9+/-8.7%; P=0.12).

CONCLUSION: The variable %DET extracted from the surface EMG is a poor indicator of the degree of motor unit short-term synchronization.

SIGNIFICANCE: The study provides a systematic evaluation of a technique previously proposed for the estimation of a clinically relevant characteristic of motor unit behavior.

Original languageEnglish
Pages (from-to)2086-92
Number of pages7
JournalClinical Neurophysiology
Volume120
Issue number12
DOIs
Publication statusPublished - Dec 2009

Keywords

  • Action Potentials
  • Adult
  • Electromyography
  • Humans
  • Isometric Contraction
  • Male
  • Muscle, Skeletal
  • Recruitment, Neurophysiological
  • Young Adult
  • Comparative Study
  • Journal Article
  • Research Support, Non-U.S. Gov't

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