Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 548208, 5 pages
Research Article

Locomotor Development Prediction Based on Statistical Model Parameters Identification

1The Center of Mathematical Modelling of Medicosocial Systems and Processes, The State National Research Politechnical University of Perm, Perm 614990, Russia
2The Department of Physical Culture and Health, The Perm State Medical Academy, Perm 614000, Russia

Received 2 July 2012; Revised 8 October 2012; Accepted 23 October 2012

Academic Editor: Alejandro Rodríguez-González

Copyright © 2012 A. V. Wildemann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper introduces an approach for parameters identification of a statistical predicting model with the use of the available individual data. Unknown parameters are separated into two groups: the ones specifying the average trend over large set of individuals and the ones describing the details of a concrete person. In order to calculate the vector of unknown parameters, a multidimensional constrained optimization problem is solved minimizing the discrepancy between real data and the model prediction over the set of feasible solutions. Both the individual retrospective data and factors influencing the individual dynamics are taken into account. The application of the method for predicting the movement of a patient with congenital motility disorders is considered.