Multidiagnostics system for patients with postural deficits and algorithm for recognizing stabilographic signals
Abstract
Multidiagnostics system for patients with postural deficits and algorithm for recognizing stabilographic signals
Work is connected with the synthesis of information behavior of groups of autonomous intelligent agents of biomedical research, and machine learning methods to ensure the reliability of the forecast increase in their behavior using multi-agent systems based on the use of bionic principles, methods and models of swarm intelligence. Developed multi-agent system simulates the behavior of groups of autonomous intelligent agents developed methods to meet the proposed criteria of reliability, differing form the structure of the system and developed a set of specialized agents that provides the capability to model a group of biomedical robotics using autonomous intelligent agents. Classifier of stabilographic signals on the basis of Parzen method was developed. These data indicate that the auxiliary symptoms resulting from multidimensional scaling much more informative initial attributes.
Keywords: Intelligent agent, multidiagnostics, Parzen classifier