The autoregressive time series modelling of stabilograms.

Power spectral density analysis of frontal and sagittal stabilograms in young male subjects with a normal vestibular function indicates the fitting of parametric time series models to stabilograms. Subjects were standing on a force platform under three different standing conditions. Stabilograms lasting for 2 minutes were processed by means of a TPAi computer with the CAMAC system. Following digital high-pass filtering, correlation functions and power spectral density distributions were estimated. Linear autoregressive models of increasing order up to 30 were fitted to stabilograms on the basis of the autocorrelation functions by means of a recursive scheme. The goodness of fit of the autoregressive models was significantly different in the standing conditions, planes and subjects. The orders of models for frontal stabilograms were higher than for sagittal ones, whereas the residual variances were lower than for sagittal stabilograms. We arrived at the conclusion that autoregressive modelling is a suitable approach for obtaining reliable spectral estimates and for characterizing the control system of body sway.