Application of Adaptive Classification of Tensotremorograms for Revealing the Pathological States of Human Motor Control System

Abstract

In this paper the adaptive binary classifier is applied for the classification of the tensotremorogramm (TTG) time series. The idea is to reveal pathological states of human motor control system. Adaptive binary classifier being a new type of trained classifiers can be trained on the data for healthy subjects. Then the trained classifier can be used for the examinees division into healthy and sick patients. It is shown, that the trained adaptive binary classifier is able to classify the patients with acceptable accuracy. Other method of classification—Neural Clouds—has also been used. The comparison both methods has been done.