Evaluation of effectiveness of kinesotherapy according to stochastics and chaos

S. Sagadeeva; D. Sinenko; G. Garaeva; Valeriy V. Eskov; L. Shakirova

doi:doi:10.12737/10870

Evaluation of effectiveness of kinesotherapy according to stochastics and chaos

Published в Complexity. Mind. Postnonclassic · Volume 4, Issue 1, 2015 · Pages 89–95 · Rubrics: Section Synergetic aspects of the personified medicine and synergetrics and integrated medicine

DOI 10.12737/10870

Received: 23.04.2015 Accepted: 23.04.2015 Published: 23.04.2015 Language of publication: RUS

Authors

S. Sagadeeva · D. Sinenko · G. Garaeva · Valeriy V. Eskov ⁴ · L. Shakirova

4 Russian Federation

ABSTRACT

Evaluating the effectiveness of treatment of a disease (in this paper is kinesotherapy treatment of acute cerebrovascular accidents and physical therapy for hypertension in the North of the Russian Federation) is traditionally carried out by the results of the monitoring of relevant parameters of the disease in patient before treatment and after treatment measures. However, it is quite often that with multi-parameter monitoring of the patient is not all of the observed parameters xi may show substantial (in the framework of stochastic criteria) change of parameters of the entire state vector xi of the human body in the form x = x (t) = (x1, x2,..., xm)T where m is dimension of the phase space of states. In such cases there is an uncertainty of type 1 (sort) when the stochastics show low efficiency. Then it is supposed that there is a efficiency of treatment, otherwise there is a need to find other methods allowing more accurate measurement of real change of xi within the course of treatment. We show two ways of solving the problem of uncertainty of 1st type on the basis of the calculation of quasi-attractors of the state vector of the human body.

KEYWORDS

chaos quasi-attractors kinesotherapy.

Information Text References

Authors:

4. Russian Federation

Type:

Article

Pages:

from 89 to 95

Status:

Published

Language:

Russian

Keywords:

chaos, quasi-attractors, kinesotherapy.

Text

В рамках этих новых подходов неопределенность 1-го типа может быть устранена с использованием нейрокомпьютерных технологий (с помощью НЭВМ) или на основе расчета параметров квазиаттракторов (КА), внутри которых непрерывно и хаотически движется вектор состояния организма человека (ВСОЧ) – x(t). При работе с m-мерным фазовым пространством состояний возникает задача выделения наиболее важных диагностических признаков x_i из всего набора m. Фактически, при этом осуществляется переход к системам с меньшей размерностью k (k<<m), а это уже определяется как задача системного синтеза (минимизация размерности m фазового пространства состояний).

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