Your browser doesn't support javascript.
loading
Correlation between spectral and temporal mechanomyography features during functional electrical stimulation
Krueger, Eddy; Scheeren, Eduardo Mendonça; Nogueira-Neto, Guilherme Nunes; Button, Vera Lúcia da Silveira Nantes; Nohama, Percy.
  • Krueger, Eddy; Universidade Tecnológica Federal do Paraná. Graduate Program in Electrical and Computer Engineering. Curitiba. BR
  • Scheeren, Eduardo Mendonça; Universidade Tecnológica Federal do Paraná. Graduate Program in Electrical and Computer Engineering. Curitiba. BR
  • Nogueira-Neto, Guilherme Nunes; Universidade Tecnológica Federal do Paraná. Graduate Program in Electrical and Computer Engineering. Curitiba. BR
  • Button, Vera Lúcia da Silveira Nantes; Universidade Tecnológica Federal do Paraná. Graduate Program in Electrical and Computer Engineering. Curitiba. BR
  • Nohama, Percy; Universidade Tecnológica Federal do Paraná. Graduate Program in Electrical and Computer Engineering. Curitiba. BR
Res. Biomed. Eng. (Online) ; 32(1): 85-91, Jan.-Mar. 2016. tab, graf
Article in English | LILACS | ID: biblio-829461
ABSTRACT
Abstract Introduction: Signal analysis involves time and/or frequency domains, and correlations are described in the literature for voluntary contractions. However, there are few studies about those correlations using mechanomyography (MMG) response during functional electrical stimulation (FES) elicited contractions in spinal cord injured subjects. This study aimed to determine the correlation between spectral and temporal MMG features during FES application to healthy (HV) and spinal cord injured volunteers (SCIV). Methods: Twenty volunteers participated in the research divided in two groups: HV (N=10) and SCIV (N=10). The protocol consisted of four FES profiles transcutaneously applied to quadriceps femoris muscle via femoral nerve. Each application produced a sustained knee extension greater than 65º up to 2 min without adjusting FES intensity. The investigation involved the correlation between MMG signal root mean square (RMS) and mean frequency (MF). Results: HV and SCIV indicated that MMGRMS and MMGMF variations were inversely related with -0.12 ≥ r ≥ -0.82. The dispersion between MMGMF and MMGRMS reached 0.50 ≤ r2 ≤ 0.64. Conclusion The increase in MMGRMS and the decrease in MMGMF may be explained by the motor units coherence during fatigue state or by motor neuron adaptation (habituation) along FES application (without modification on parameters).


Full text: Available Index: LILACS (Americas) Language: English Journal: Res. Biomed. Eng. (Online) Journal subject: Engenharia Biom‚dica Year: 2016 Type: Article Affiliation country: Brazil Institution/Affiliation country: Universidade Tecnológica Federal do Paraná/BR

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Index: LILACS (Americas) Language: English Journal: Res. Biomed. Eng. (Online) Journal subject: Engenharia Biom‚dica Year: 2016 Type: Article Affiliation country: Brazil Institution/Affiliation country: Universidade Tecnológica Federal do Paraná/BR