Research on Biomedical Engineering
http://www.rbejournal.periodikos.com.br/article/doi/10.1590/2446-4740.03615
Research on Biomedical Engineering
Original Article

Influence of subcutaneous fat on mechanomyographic signals at three levels of voluntary effort

Eduardo Mendonça Scheeren; Lindomar Mineiro; Eduardo Borba Neves; Eddy Krueger; Guilherme Nunes Nogueira Neto; Percy Nohama

http://dx.doi.org/10.1590/2446-4740.03615 Res. Biomed. Eng., vol.32, n4, p.307-317, 2017
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Abstract

Abstract: Introduction: This study aims to assess the influence of different skinfold thicknesses (ST) and their relation to the attenuation of the mechanomyographic (MMG) signal at different force levels (maximal voluntary contraction – MVC, 40% of MVC and 70% of MVC) of the rectus femoris muscle.

Methods: Fifteen volunteers were divided in two groups: ST lower than 10mm (G<10) (8 participants) and ST higher than 35mm (G>35) (7 participants). Student t tests were employed to investigate differences between G<10 and G>35 regarding MMG analysis parameters (acceleration root mean square – aRMS, zero crossing – ZC, and median frequency – MDF), for the X, Y and Z axes, as well as for the modulus of these three axes.

Results: We found that thicker layers of body fat act as attenuator filters for the MMG signal [MDFMVC: X (p = 0.005), Z (p = 0.003); MDF70%MVC: X (p = 0.034); ZCMVC: Z (p = 0.037), modulus (p = 0.005); ZC70%MVC: Z (p = 0.047)]. We found significant correlation between ST values and aRMS in three levels, in the Yaxis (p = 0.591), for the group G<10. For the modulus, the aRMS value showed correlation with ST values for group G>35 in 40%MVC (R2 = 0.610), and 70%MVC (R2 = 0.592). The MDF parameter showed correlation with ST values only in the Yaxis in 70%MVC (R2 = 0.700) for G>35.

Conclusions: We observed MMG signal attenuation in at least one of the parameters analyzed for each level of the rectus femoris muscle force, indicating that MMG signals are significantly attenuated with increasing thickness of the subcutaneous fat layer.

Keywords

Mechanomyography, Skinfold, Signal attenuation, Level of force

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