Is slow walking more stable?

Several efforts have been made to study gait stability using measures derived from nonlinear time-series analysis. The maximum finite time Lyapunov exponent (λmax) quantifies how a system responds to an infinitesimally small perturbation. Recent studies suggested that slow walking leads to lower λmax values, and thus is more stable than fast walking, but these studies suffer from methodological limitations. We studied the effects of walking speed on the amount of kinematic variability and stability in human walking. Trunk motions of 15 healthy volunteers were recorded in 3D during 2 min of treadmill walking at different speeds. From those time series, maximum Lyapunov exponents, indicating short-term and long-term divergence (λS-stride and λL-stride), and mean standard deviation (MeanSD) were calculated. λS-stride showed a linear decrease with increasing speed for forward–backward (AP) movements and quadratic effects (inverted U-shaped) for medio-lateral (ML) and up–down (VT) movements. λL-stride showed a quadratic effect (inverted U-shaped) of walking speed for AP movements, a linear decrease for ML movements, and a linear increase for VT movements. Moreover, positive correlations between λS and MeanSD were found for all directions, while λL-stride and MeanSD were correlated negatively in the AP direction. The different effects of walking speed on λS-stride and λL-stride for the different planes suggest that slow walking is not necessarily more stable than fast walking. The absence of a consistent pattern of correlations between λL-stride and MeanSD over the three directions suggests that variability and stability reflect, at least to a degree, different properties of the dynamics of walking.