Challenging human locomotion: stability and modular organisation in unsteady conditions

Abstract

The need to move over uneven terrain is a daily challenge. In order to face unexpected perturbations due to changes in the morphology of the terrain, the central nervous system must flexibly modify its control strategies. We analysed the local dynamic stability and the modular organisation of muscle activation (muscle synergies) during walking and running on an even- and an uneven-surface treadmill. We hypothesized a reduced stability during uneven-surface locomotion and a reorganisation of the modular control. We found a decreased stability when switching from even- to uneven-surface locomotion (p < 0.001 in walking, p = 0.001 in running). Moreover, we observed a substantial modification of the time-dependent muscle activation patterns (motor primitives) despite a general conservation of the time-independent coefficients (motor modules). The motor primitives were considerably wider in the uneven-surface condition. Specifically, the widening was significant in both the early (+40.5%, p < 0.001) and late swing (+7.7%, p = 0.040) phase in walking and in the weight acceptance (+13.6%, p = 0.006) and propulsion (+6.0%, p = 0.041) phase in running. This widening highlighted an increased motor output's robustness (i.e. ability to cope with errors) when dealing with the unexpected perturbations. Our results confirmed the hypothesis that humans adjust their motor control strategies' timing to deal with unsteady locomotion.

Figure 1

Sketch of the uneven-surface treadmill employed in this study.

Figure 2

Example of two fundamental synergies combined into one. The histograms (a and b) represent the two fundamental sets of motor modules for seven muscles. The curves (d and e) show the two respective primitives, with arbitrary x- and y-axis units. The combined motor modules and primitives are presented in panels (c and f), respectively.

Figure 3

Boxplots depicting the maximum Lyapunov exponent values for even and uneven surface in both walking and running with the black lines indicating individual changes between conditions (a). Averaged over all participants mean logarithmic divergences of the trajectories between even and uneven surface in walking and running. A faster divergence indicates worse dynamic stability (b).

Figure 4

The average spatiotemporal spinal motor outputs are presented for even and uneven surface walking and running, normalised in amplitude to the maximum of each segment. These curves have been obtained by mapping each of the 13 muscle activations onto the relevant spinal segment (lumbar from L2 to L5 and sacral from S1 and S3). Asterisks denote significant differences in the full width at half maximum of the mapped EMGs between even and uneven surface locomotion. The two level plots show the average alpha-motoneurons activity for each condition, giving additional information about the absolute activation level (normalisation to the maximum of each condition). The stance and swing phases have been temporally normalised to the same amount of data points (100 each). Values are the means across all subjects and all trials.

Figure 5

Average motor modules and motor primitives of the four fundamental synergies for walking and running on even and uneven surface. The motor modules are presented on a normalised y-axis base. For the motor primitives, the x-axis full scale represents one gait cycle (stance and swing normalised to the same amount of points and divided by a vertical line) and the y-axis the normalised amplitude. Asterisks denote significant differences between even and uneven surface locomotion. Daggers denote results of the post-hoc analysis.