  Scaling concepts and renormalization group (RG) methods are applied to a
simple linear model of human posture control consisting of a trembling or
quivering string subject to damping and restoring forces. The string is driven
by uncorrelated white Gaussian noise intended to model the corrections of the
physiological control system. We find that adding a weak quadratic nonlinearity
to the posture control model opens up a rich and complicated phase space
(representing the dynamics) with various non-trivial fixed points and basins of
attraction. The transition from diffusive to saturated regimes of the linear
model is understood as a crossover phenomenon, and the robustness of the linear
model with respect to weak non-linearities is confirmed. Correlations in
posture fluctuations are obtained in both the time and space domain. There is
an attractive fixed point identified with falling. The scaling of the
correlations in the front-back displacement, which can be measured in the
laboratory, is predicted for both the large-separation (along the string) and
long-time regimes of posture control.
