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The assessment and physiological register of muscular tissue can be done through mechanomyography (MMG). The oscillation of muscular displacement is acquired on the skin surface, insomuch that the skinfold thickness can influence in MMG response. The aim of this study is verify the influence of different skinfold thickness on MMG features responses. Triaxial MMG was used over the rectus femoris muscle belly of ten volunteers during maximal voluntary contraction. MMG spectral and temporal analyses were made and specific features (root mean square (RMS), Integral (Int), mean frequency (MF), zero-crossing (ZC), and μ3) were correlated with skinfold thickness. Moderate and high negative correlation occurred to MMG mean frequency in axes X (ρ = - 0.57) and Y (ρ = -0.75), respectively. As the fat tissue behaves like a low-pass filter, i.e. the thicker his skinfold the shorter its bandwidth; therefore, the skinfold thicknesses result in lower frequency responses. So, hereafter these results may be applied to calibrate MMG responses as biofeedback systems in, for instance, neuroprostheses.

Functional electrical stimulation (FES) improves paraplegic subjects rehabilitation and may be used in neuroprosthesis systems. Superficial mechanomyography (MMG) monitors the contracting muscles oscillations. The goal of this paper is to compare the relationships between MMG features and knee angles during open chain movements artificially evoked by different FES off times (5s; 10s and 15s) in a spinal cord injured volunteer. FES waveform consisted of a monophasic square wave, 1kHz pulse frequency, 300μs active pulse period and 3ms active burst period with burst frequency of 70Hz. Sixteen artificial contractions were generated by FES applied to the quadriceps femoral muscle pre- and pos-interval of 15min, totalizing thirty two contractions. Temporal (RMS value) and spectral (median frequency) MMG features were analyzed for rectus femoris and vastus lateralis muscles. MMGRMS and MMGMF variations were inversely related, with correlation coefficients values from -0.30 until -0.79. These results may help create new FES closed-loop control strategies by MMG features.

The goal of this study is to investigate the time versus frequency relationship of mechanomyographic signals during dynamic knee movements and FES fatigue protocol. Ten healthy volunteer’s (HV) were submitted to four functional electrical stimulation (FES) profiles (pulse frequency: 1kHz; active pulse duration: 200μs; burst frequency: 50Hz; active burst duration: 3ms) applied to the rectus femoris and vastus lateralis muscles. Each contraction was repeated four times randomly. RMS and MF MMG features were plotted using linear regression so as to find the relation between them during fatigue protocol. The results showed that the linear regression had a negative slope in all contractions. The best fit linear regression values (for both RF and VL muscles) were obtained in the fourth contraction, and the best correlation was found in the VL muscle.