Humans exploit the biomechanics of bipedal gait during visually guided walking over complex terrain

Abstract

How do humans achieve such remarkable energetic efficiency when walking over complex terrain such as a rocky trail? Recent research in biomechanics suggests that the efficiency of human walking over flat, obstacle-free terrain derives from the ability to exploit the physical dynamics of our bodies. In this study, we investigated whether this principle also applies to visually guided walking over complex terrain. We found that when humans can see the immediate foreground as little as two step lengths ahead, they are able to choose footholds that allow them to exploit their biomechanical structure as efficiently as they can with unlimited visual information. We conclude that when humans walk over complex terrain, they use visual information from two step lengths ahead to choose footholds that allow them to approximate the energetic efficiency of walking in flat, obstacle-free environments.

Keywords: dynamic walking; human locomotion; inverted pendulum; visual control.

Figure 1.

A conceptual diagram summarizing the dynamic walking perspective. The walker's COM follows a ballistic, passive trajectory during the single-support phase governed by the dynamics of an inverted pendulum. During the double-support phase, or step-to-step transition, the positive work of the trailing leg and the negative work of the leading leg (upward pointing arrows) redirect the COM's trajectory from a downward arc to the upward arc necessary for the next step. The energetic cost of this redirection of the COM is proportional to α.

Figure 2.

(a) Experimental set-up. An LCD projector displayed obstacles on the ground. The projector system was synchronized with a motion capture system so that subjects’ collisions with the virtual obstacles could be registered and recorded. (b) In the full vision control condition, the entire field of obstacles was visible throughout the trial. (c) In the limited vision condition, obstacles were only displayed when they fell within a certain visibility window centred on the subject. In this study, nine different window sizes were tested, with radii ranging from one step length (0.7 × leg length) to five step lengths. The edge of the visibility window shown here (dashed circle in (c)) was not visible to the subject.

Figure 3.

Mean Euclidean distance between COM at the end of each step and the predicted endpoint if the COM had followed the trajectory of an unactuated inverted pendulum with equivalent initial conditions. Values normalized by scores in an obstacle-free condition (mean: 77.3 mm, s.d.: 11.3). Asterisks denote significant deviations from the full vision control condition (p < 0.05). Bars indicate ± 1 s.e.m.

Figure 4.

Mean energy recovery for all subjects in each visibility condition. Asterisks denote significant deviations from the full vision control condition (p < 0.05). Bars indicate ± 1 s.e.m.

Figure 5.

Mean change in COM height as a function of time during steps for a single representative subject during (a) obstacle-free walking and (b–i) a selection of the various visibility conditions. Grey regions represent ± s.d.

Figure 6.

(a) Mean number of collisions per trial for each visibility condition. (b) Mean walking speed for each visibility condition were normalized to their scores in an obstacle-free condition (mean: 1.0 m s⁻¹, s.d.: 0.1). Asterisks denote significant deviations from the full vision control condition (p < 0.05). Bars indicate ± 1 s.e.m.

Figure 7.

Consideration of the point at which the determinants of the passive trajectory of the COM for a given step are defined yields a prediction of how walking behaviour over complex terrain will be affected by the limited visibility conditions.