Estimation of the interplay between groups of fast and slow muscle fibers of the tibialis anterior and gastrocnemius muscle while running

Comparison of human gastrocnemius forces predicted by Hill-type muscle models and estimated from ultrasound images

“…The total intensity is a close approximation to the power of the signal and was calculated across a 10-450 Hz frequency band using an EMG-specific wavelet analysis (von Tscharner, 2000). Optimized wavelets were derived, for each muscle, using principal component analysis to identify the major features of the intensity spectra from the 16 subjects (Wakeling and Rozitis, 2004;Von Tscharner and Goepfert, 2006;Hodson-Tole and Wakeling, 2007;Wakeling and Horn, 2009;Lee et al, 2011) (Fig. 2).…”

Counterpoint: Spectral properties of the surface emg do not provide information about motor unit recruitment and muscle fiber type

“…The limitations discussed in the preceding paragraph are sometimes considered to be negligible (26). A study often cited to support this assertion is the observation by Solomonow et al (23) that orderly stimulation of motor units in the cat gastrocnemius muscle via nerve electrodes gave rise to linearly increasing median frequency of the intramuscular EMG signal.…”

“…In addition to these applications, the spectral characteristics of the surface EMG have been used to infer motor unit recruitment strategies and the fiber-type composition of a muscle. Higher characteristic spectral frequencies are associated with a greater proportion of type II fibers (20, 21) and changes in EMG spectral variables are used to infer the recruitment of faster or slower motor units (3,26).The capacity of surface EMG spectral properties to provide information about motor unit recruitment or the proportion of fiber types is based on the rationale that higher threshold (and type II) motor units produce surface action potentials with larger relative energy at higher frequencies than lower threshold (and type I) motor units.Because in these applications the main determinant of the frequency content of an action potential is assumed to be its conduction velocity (28), the crucial issue in this debate is the validity of two assumptions: 1) average conduction velocity of the active motor units is related to fiber-type proportions, and 2) changes in the spectral properties of the surface EMG are associated with changes in average conduction velocity.Fiber-type composition and average muscle fiber conduction velocity. There are several physiological details that confound this association.…”

“…In addition to these applications, the spectral characteristics of the surface EMG have been used to infer motor unit recruitment strategies and the fiber-type composition of a muscle. Higher characteristic spectral frequencies are associated with a greater proportion of type II fibers (20, 21) and changes in EMG spectral variables are used to infer the recruitment of faster or slower motor units (3,26).…”

Análise espectral do sinal EMG de exercício incremental em ciclistas e não ciclistas usando as transformadas de Fourier e Wavelet

“…Vontscharner and Goepfert 12 have shown that the WT analysis is highly effective in identifying the muscle recruitment pattern of different types of muscle fiber in a specific phase of movement during running. The FFT analysis would hardly be able to identify this pattern with the same accuracy as the WT analysis, as suggested by the study of Karlsson et al 13 .…”