Interaction between step-to-step variability and metabolic cost of transport during human walking

Abstract

Minimizing the metabolic cost of transport can affect selection of the preferred walking speed. While many factors can affect metabolic cost of transport during human walking, its interaction with step-to-step variability is unclear. Here, we aimed to determine the interaction between metabolic cost of transport and step length variability during human walking at different speeds. In particular, two aspects of step length variability were analyzed: the amount of variations ('variations') and the organization of the step-to-step fluctuations ('fluctuations'). Ten healthy, young participants walked on a treadmill at five speeds, ranging from 0.75 to 1.75 m s^-1 Metabolic cost of transport, step length variations (coefficient of variation) and step length fluctuations (quantified via detrended fluctuation analysis) were calculated. A mixed-model ANOVA revealed that variations and walking speed were strong predictors of metabolic cost of transport (R²=0.917, P<0.001), whereas fluctuations were not. Preferred walking speed (1.05±0.20 m s^-1) was not significantly different from the speed at which metabolic cost of transport was minimized (1.04±0.05 m s^-1; P=0.792), nor from the speed at which fluctuations were most persistent (1.00±0.41 m s^-1; P=0.698). The minimization of variations occurred at a faster speed (1.56±0.17 m s^-1) than the preferred walking speed (P<0.001). Step length variations likely affect metabolic cost of transport because greater variations are indicative of suboptimal, mechanically inefficient steps. Fluctuations have little or no effect on metabolic cost of transport, but still may relate to preferred walking speed.

Keywords: Energy; Fractal; Locomotion; Persistence; Step length.

Fig. 1.

Effect of speed on net metabolic cost of transport (MCOT), variations (step length coefficient of variation) and fluctuations (step length DFA-α). Mean values for each speed condition were calculated (circles, error bars=±1 s.d.) and fitted with a second order polynomial. Significant effects of speed were observed on net MCOT (P<0.001) and on variations (P=0.002). No effect of speed was observed on fluctuations (P=0.342). The average preferred walking speed (PWS) across participants (dashed vertical line) was 1.05±0.20 m s⁻¹. Subject-specific figures are shown in Fig. S2. CV, coefficient of variation; DFA, detrended fluctuation analysis.

Fig. 2.

Estimated net MCOT values as a function of variations (step length CV) and walking speed according to the model. Circles represent the measured mean net MCOT for each speed condition. A strong relationship was observed between the observed net MCOT values and the values estimated by the model (R²=0.917). CV, coefficient of variation.

Fig. 3.

Speeds at which net MCOT and variations (step length CV) were estimated to be minimized, and at which fluctuations (step length DFA-α) were estimated to be maximized. The minimum of net MCOT was not significantly different (P=0.792) from the mean PWS (solid horizontal line; dashed lines=95% confidence interval), nor was the maximum of fluctuations (P=0.698). However, the minimum of variations was significantly different from the PWS (P<0.001). Bars represent mean values with error bars indicating 95% confidence intervals. Least significant difference was used for post hoc comparisons. CV, coefficient of variation.