  In this work we develop a new method of diagnosing the nervous system
diseases and a new approach in studying human gait dynamics with the help of
the theory of discrete non-Markov random processes. The stratification of the
phase clouds and the statistical non-Markov effects in the time series of the
dynamics of human gait are considered. We carried out the comparative analysis
of the data of four age groups of healthy people: children (from 3 to 10 year
olds), teenagers (from 11 to 14 year oulds), young people (from 21 up to 29
year oulds), elderly persons (from 71 to 77 year olds) and Parkinson patients.
The full data set are analyzed with the help of the phase portraits of the four
dynamic variables, the power spectra of the initial time correlation function
and the memory functions of junior orders, the three first points in the
spectra of the statistical non-Markov parameter. The received results allow to
define the predisposition of the probationers to deflections in the central
nervous system caused by Parkinson's disease. We have found out distinct
differencies between the five submitted groups. On this basis we offer a new
method of diagnostics and forecasting Parkinson's disease.
