Computer Research and Modeling
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Computer Research and Modeling:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Computer Research and Modeling, 2017, Volume 9, Issue 2, Pages 345–354
DOI: https://doi.org/10.20537/2076-7633-2017-9-2-345-354
(Mi crm68)
 

This article is cited in 8 scientific papers (total in 8 papers)

COMPUTER SCIENCE IN SPORT

Application of correlation adaptometry technique to sports and biomedical research

M. I. Shpitonkov

Dorodnicyn Computing Centre, Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, 44, b. 2, Vavilov st., Moscow, 119333, Russia
Full-text PDF (406 kB) Citations (8)
References:
Abstract: The paper outlines the approaches to mathematical modeling correlation adaptometry techniques widely used in biology and medicine. The analysis is based on models employed in descriptions of structured biological systems. It is assumed that the distribution density of the biological population numbers satisfies the equation of Kolmogorov-Fokker-Planck. Using this technique evaluated the effectiveness of treatment of patients with obesity. All patients depending on the obesity degree and the comorbidity nature were divided into three groups. Shows a decrease in weight of the correlation graph computed from the measured in the patients of the indicators that characterizes the effectiveness of the treatment for all studied groups. This technique was also used to assess the intensity of the training loads in academic rowing three age groups. It was shown that with the highest voltage worked with athletes for youth group. Also, using the technique of correlation adaptometry evaluated the effectiveness of the treatment of hormone replacement therapy in women. All the patients depending on the assigned drug were divided into four groups. In the standard analysis of the dynamics of mean values of indicators, it was shown that in the course of the treatment were observed normalization of the averages for all groups of patients. However, using the technique of correlation adaptometry it was found that during the first six months the weight of the correlation graph was decreasing and during the second six months the weight increased for all study groups. This indicates the excessive length of the annual course of hormone replacement therapy and the practicality of transition to a semiannual rate.
Keywords: correlation adaptometry, the weight of the correlation graph, patients with obesity, athletes-rowers, hormone replacement therapy.
Funding agency Grant number
Russian Foundation for Basic Research 15-07-06947
The work was supported by RFBR. Project code 15-07-06947.
Received: 19.11.2016
Revised: 27.01.2017
Accepted: 03.03.2017
Document Type: Article
UDC: 519.8
Language: Russian
Citation: M. I. Shpitonkov, “Application of correlation adaptometry technique to sports and biomedical research”, Computer Research and Modeling, 9:2 (2017), 345–354
Citation in format AMSBIB
\Bibitem{Shp17}
\by M.~I.~Shpitonkov
\paper Application of correlation adaptometry technique to sports and biomedical research
\jour Computer Research and Modeling
\yr 2017
\vol 9
\issue 2
\pages 345--354
\mathnet{http://mi.mathnet.ru/crm68}
\crossref{https://doi.org/10.20537/2076-7633-2017-9-2-345-354}
Linking options:
  • https://www.mathnet.ru/eng/crm68
  • https://www.mathnet.ru/eng/crm/v9/i2/p345
  • This publication is cited in the following 8 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Research and Modeling
    Statistics & downloads:
    Abstract page:277
    Full-text PDF :114
    References:52
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2025