Examining Human Unipedal Quiet Stance: Characterizing Control through Jerk

Figure 10

Typical fluctuation profiles generated by performing a detrended fluctuation analysis on our data. Temporal scaling regions common to all data are shown. (a and c) Results for M-L and A-P jerk data, respectively, indicating these realizations are characteristics of (stationary) fractional Gaussian noise. The 95% confidence bounds included on the plot yet are barely visible. Moreover, for the analysis seen in (a), one can argue that a crossover from persistent to antipersistent behavior is made at the time scale of 1.00 s. This is true for other jerk data (Table 1) for both the time scales, 0.20 s and 1.00 s. (b, c) The results of the DFA for the force corresponding to the jerk. These plots correspond to a character of (nonstationary) fractional Brownian motion for the shorter time scales. (a) Example of DFA for M-L jerk data. (b) DFA for M-L force corresponding to the jerk analyzed in (a). (c) Example of DFA for A-P jerk data. (d) DFA for A-P force data corresponding to the jerk analyzed in (c).

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