Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?
Figure 5
(A) Example GEM data from a typical subject. Individual dots represent individual strides. The diagonal line represents the GEM (see Fig. 2). (B) Time series of δT and δP deviations for the data set shown in (A). Qualitatively, the δT deviations exhibit larger amplitudes and also appear to show greater statistical persistence than the δP deviations. (C) Standard deviations for all δT and δP time series at all 5 walking speeds. Error bars represent between-subject ±95% confidence intervals. Subjects exhibited significantly greater variability along the GEM (δT) than perpendicular to the GEM (δP): F(1,16) = 139.93; p = 2.53×10−9. (D) DFA α exponents for all δT and δP time series at all 5 walking speeds. Error bars represent between-subject ±95% confidence intervals. Subjects exhibited significantly greater statistical persistence along the GEM (δT) than perpendicular to the GEM (δP): F(1,16) = 368.21; p = 1.81×10−12. Additionally, all subjects exhibited significant anti-persistence (95% confidence interval upper bounds all <½) for the goal-relevant δP deviations at all 5 walking speeds.