Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors

Abstract

We investigated muscle activity, ground reaction forces, and center of mass (CoM) acceleration in two different postural behaviors for standing balance control in humans to determine whether common neural mechanisms are used in different postural tasks. We compared nonstepping responses, where the base of support is stationary and balance is recovered by returning CoM back to its initial position, with stepping responses, where the base of support is enlarged and balance is recovered by pushing the CoM away from the initial position. In response to perturbations of the same direction, these two postural behaviors resulted in different muscle activity and ground reaction forces. We hypothesized that a common pool of muscle synergies producing consistent task-level biomechanical functions is used to generate different postural behaviors. Two sets of support-surface translations in 12 horizontal-plane directions were presented, first to evoke stepping responses and then to evoke nonstepping responses. Electromyographs in 16 lower back and leg muscles of the stance leg were measured. Initially (∼100-ms latency), electromyographs, CoM acceleration, and forces were similar in nonstepping and stepping responses, but these diverged in later time periods (∼200 ms), when stepping occurred. We identified muscle synergies using non-negative matrix factorization and functional muscle synergies that quantified correlations between muscle synergy recruitment levels and biomechanical outputs. Functional muscle synergies that produce forces to restore CoM position in nonstepping responses were also used to displace the CoM during stepping responses. These results suggest that muscle synergies represent common neural mechanisms for CoM movement control under different dynamic conditions: stepping and nonstepping postural responses.

Individuals with transtibial limb loss use interlimb force asymmetries to maintain multi-directional reactive balance control

“…Here we examined whole-body kinematics and endpoint forces to describe differences in reactive postural balance control between individuals with unilateral TTLL and unimpaired adults. An analysis of the muscle coordination patterns that underlie the differences in control strategies used to stabilize the same CoM displacement [36,51,52], may provide additional insight into their production and the design of interventions to improve balance control among individuals with LLL.…”

Contribution of vision to postural behaviors during continuous support-surface translations

“…Postural difficulty has also been shown to increase due to disruption of vestibular or somatosensory information (Horak et al 1990), distance from CoM position-velocity stability limits (Pai and Patton 1997), and changes in stance width (Winter et al 1998; Gatev et al 1999; Bingham et al 2011). Here we focused on a shift from ankle to hip strategy, although increasing difficulty could also involve knee flexion (Dokka et al 2009; Allum et al 2008), arm raising (Allum et al 2008), as well as stepping responses (McIlroy and Maki 1993; Ting et al 2009; Chvatal et al 2011). The ankle strategy may be a preferred strategy for less difficult perturbations despite its limited biomechanical efficacy in restoring balance (Kuo and Zajac 1993).…”

Review and perspective: neuromechanical considerations for predicting muscle activation patterns for movement

“…A consistent relationship between muscle synergy recruitment and endpoint force production was found in cats during balance control [60]; this direction of force production with respect to the limb axis was preserved across multiple postural configurations [61]. In humans, muscle synergy structure was consistent across postural configurations including narrow, wide, crouched, and single limb stance [62], as well as in a variety of postural responses such as hip, ankle, stepping, and feet in place [63]. Similarly, simulations in which muscle synergies constrain muscle activation patterns have reliably produced motor functions across variations in the motor task [64,65,66].…”