A Muscle’s Force Depends on the Recruitment Patterns of Its Fibers

Abstract

Biomechanical models of whole muscles commonly used in simulations of musculoskeletal function and movement typically assume that the muscle generates force as a scaled-up muscle fiber. However, muscles are comprised of motor units that have different intrinsic properties and that can be activated at different times. This study tested whether a muscle model comprised of motor units that could be independently activated resulted in more accurate predictions of force than traditional Hill-type models. Forces predicted by the models were evaluated by direct comparison with the muscle forces measured in situ from the gastrocnemii in goats. The muscle was stimulated tetanically at a range of frequencies, muscle fiber strains were measured using sonomicrometry, and the activation patterns of the different types of motor unit were calculated from electromyographic recordings. Activation patterns were input into five different muscle models. Four models were traditional Hill-type models with different intrinsic speeds and fiber-type properties. The fifth model incorporated differential groups of fast and slow motor units. For all goats, muscles and stimulation frequencies the differential model resulted in the best predictions of muscle force. The in situ muscle output was shown to depend on the recruitment of different motor units within the muscle.

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

“…We hypothesized that the twoelement model would better reproduce the ultrasound-based estimates of gastrocnemius force at the higher cadences, where preferential recruitment of fast fibres has been reported (Citterio and Agostoni, 1984;Wakeling et al, 2006). This is an extension of our previous studies on the gastrocnemius muscles in goats, where we showed that a two-element model, driven by the independent activation of slow and fast muscle fibres, provided better predictions of time-varying muscle forces than traditional one-element models for some in situ (Wakeling et al, 2012) and in vivo conditions.…”

“…However, at low motor unit firing rates, differences in the predicted and measured forces were greater than 50% (Perreault et al, 2003). Our own efforts to predict in situ and in vivo forces generated by the gastrocnemius muscles of goats (Wakeling et al, 2012;Lee et al, 2013) confirmed that Hill-type models are sensitive to assumptions about activation state and the force-velocity properties of the model's contractile element. For example, we have shown that Hill-type models reproduce the timevarying in vivo forces with an average r 2 of 0.40, and errors in force greater than 15% and 28% of maximum isometric force for the medial (MG) and lateral (LG) gastrocnemii of goats, respectively, when averaged across the gait cycle and different locomotor speeds.…”

Recruitment of faster motor units is associated with greater rates of fascicle strain and rapid changes in muscle force during locomotion

“…These results support hypotheses posed in previous studies, suggesting that motor units form task groups that are selectively recruited for rapid tasks (Hodson-Tole and Wakeling, 2008b;Wakeling, 2004;Loeb, 1985). The results also may have important and practical implications for muscle modeling, as new models that incorporate separate slow and fast contractile elements may yield better predictions of time-varying muscle force than existing, oneelement models that do not consider differential recruitment (Wakeling et al, 2012). To our knowledge, this is only the third report that has identified significant associations between EMG frequency content and EMG intensity, strain rate and force on motor unit recruitment and investigated whether there is a mechanical basis for preferential recruitment of different motor unit types.…”

“…The cut-off frequency was chosen to accommodate a complementary study, in which we tested muscle models against in situ experiments involving 40Hz tetanic stimulations (Wakeling et al, 2012). Force rise and relaxation rates were calculated by taking the first derivative of tendon force with respect to time.…”

The detection of long-range correlations of operation force and sEMG with multifractal detrended fluctuation analysis

“…The former group's factors include the level of muscle activity, activity synchronization of motor units, muscle fibers recruitment, and muscle fiber conduction velocity [9,10].The latter group is affected by factors such as detecting electrode positions, skin temperature, muscle length, and muscle contraction mode [11][12][13]. sEMG are the result of a number of electrical signals of motor units in time and space in the muscle, and they have been proved by researchers as 1 Shanguang Chen contributes as equal as the first author and is the co-first author. * shown in Figures 1b and 1d that these signals are not in a strictly linear steady-state.…”