  In this chapter we present a new approach to the study of manifestations of
chaos in real complex system. Recently we have achieved the following result.
In real complex systems the informational measure of chaotic chatacter (IMC)
can serve as a reliable quantitative estimation of the state of a complex
system and help to estimate the deviation of this state from its normal
condition. As the IMC we suggest the statistical spectrum of the non-Markovity
parameter (NMP) and its frequency behavior. Our preliminary studies of real
complex systems in cardiology, neurophysiology and seismology have shown that
the NMP has diverse frequency dependence. It testifies to the competition
between Markovian and non-Markovian, random and regular processes and makes a
crossover from one relaxation scenario to the other possible. On this basis we
can formulate the new concept in the study of the manifestation of chaoticity.
We suggest the statistical theory of discrete non-Markov stochastic processes
to calculate the NMP and the quantitative evaluation of the IMC in real complex
systems. With the help of the IMC we have found out the evident manifestation
of chaosity in a normal (healthy) state of the studied system, its sharp
reduction in the period of crises, catastrophes and various human diseases. It
means that one can appreciably improve the state of a patient (of any system)
by increasing the IMC of the studied live system. The given observation creates
a reliable basis for predicting crises and catastrophes, as well as for
diagnosing and treating various human diseases, Parkinson's disease in
particular.
