Dynamical Properties of Postural Control in Obese Community-Dwelling Older Adults

Figure 1. (a) Median over all the center of pressure (COP) AP time series; (b) The lowest curve is obtained for m = 3 as it shows a minimum that is lower than 0.05. This minimum is reached for r = 0.25 for both AP and ML directions.

Figure 2. Linear measures of postural stability (a) Mean Velocity; (b) Mean Radius; (c) Circular area; (d) Elliptical area; (e) COP Path length.

Figure 3. Forceplate signal based non-linear analysis showing (a) approximate entropy; the graph highlights (dashed red line) obese fallers have significantly lower complexity in anterior posterior direction with eyes open condition; (b) scaling exponent α and; the graph highlights (dashed red line) that obese fallers have significantly higher scaling exponents in anterior posterior direction during eyes open condition (c) sample entropy is significantly lower for AP time series derived from forceplate for fallers with obesity in eyes open condition (red dashed lines).

Figure 4. Inertial measurement units (IMU) based nonlinear analysis showing (a) approximate entropy; The graph highlights (dashed red-line) approximate entropy is significantly lower in obese fallers in anterior posterior direction during eyes open double limb stance; (b) scaling exponent α and; The graph highlights (dashed red-line) that the scaling exponent is significantly higher for obese fallers in anterior posterior direction during eyes open double limb stance; (c) sample entropy; The graph highlights (red dashed line) that fallers who were non-obese showed significantly lower complexity (measured by sample entropy)for AP time series derived from IMU.

Figure 5. Ensemble patterns of postural stability of fallers and non-fallers exhibiting fallers with larger area of sway with lower sample entropy.

Figure 6. Radar plot of significant discriminative parameters.