Five basic muscle activation patterns account for muscle activity during human locomotion

Abstract

An electromyographic (EMG) activity pattern for individual muscles in the gait cycle exhibits a great deal of intersubject, intermuscle and context-dependent variability. Here we examined the issue of common underlying patterns by applying factor analysis to the set of EMG records obtained at different walking speeds and gravitational loads. To this end healthy subjects were asked to walk on a treadmill at speeds of 1, 2, 3 and 5 km h −1 as well as when 35-95% of the body weightwassupportedusingaharness.Werecordedfrom12-16ipsilaterallegandtrunkmuscles using both surface and intramuscular recording and determined the average, normalized EMG of each record for 10-15 consecutive step cycles. We identified five basic underlying factors or component waveforms that can account for about 90% of the total waveform variance across different muscles during normal gait. Furthermore, while activation patterns of individual muscles could vary dramatically with speed and gravitational load, both the limb kinematics and the basic EMG components displayed only limited changes. Thus, we found a systematic phase shift of all five factors with speed in the same direction as the shift in the onset of the swing phase. This tendency for the factors to be timed according to the lift-off event supports the idea that the origin of the gait cycle generation is the propulsion rather than heel strike event. The basic invariance of the factors with walking speed and with body weight unloading implies that a few oscillating circuits drive the active muscles to produce the locomotion kinematics. A flexible and dynamic distribution of these basic components to the muscles may result from various descending and proprioceptive signals that depend on the kinematic and kinetic demands of the movements.

Learning effects on muscle modes and multi-mode postural synergies

“…We would like to emphasize a major difference of our approach from those of a number of research groups who have also used matrix factorization techniques to identify muscle groups, within which levels of muscle activation scaled in parallel (d'Avella et al 2003;Ivanenko et al 2004;Weiss and Flanders 2004;Ting and Macpherson 2005;Tresch et al 2006). Both lines of research follow the general idea that a smaller number of variables (M-modes in our study or "synergies" in most other studies) can be used to construct behaviors with different characteristics (Loeb et al 2000;Saltiel et al 2001;d'Avella and Bizzi 2005;Ting and Macpherson 2005).…”

“…The coordination of the many muscles involved in standing has been viewed as an example of muscle synergies, large groups of muscles united by a common motor goal (Bernstein 1967;Ivanenko et al 2004Ivanenko et al , 2005Ting and Macpherson 2005).…”

“…M-modes were defined in those studies using principal component analysis with factor extraction. Other matrix factorization techniques have been used to identify such muscle groups (d'Avella et al 2003;Ivanenko et al 2004;Weiss and Flanders 2004;Ting and Macpherson 2005;Tresch et al 2006), but the authors of those studies addressed such groups as "synergies", while we view them as elemental variables forming a space, within which synergies are organized.…”

Analysis of muscle synergies and activation–deactivation patterns in subjects with anterior cruciate ligament deficiency during walking

“…It is believed that the number of synergies used by a human being when walking is between 4 and 6 (Allen and Neptune, 2012;Clark et al, 2010;De Groote et al, 2014;Ivanenko et al, 2005Ivanenko et al, , 2004Oliveira et al, 2014). The Variance Accounted For (VAF) between the reconstructed and the original signals is evaluated to select the proper number of modules to be used when factorizing the signals.…”

“…It is reported that there are similarities in the muscle synergies when performing the same movement across subjects. Several authors reported muscle synergies when walking (Clark et al, 2010;Dominici et al, 2011;Ivanenko et al, 2004;Neptune et al, 2009;Oliveira et al, 2014), walking with perturbations (Ivanenko et al, 2005) or performing other tasks (Rugy et al, 2013). Clark et al (2010) applied the muscle synergy analysis in post-stroke injured subjects.…”