The conducted theoretical studies provide a basic thesis regarding the creation of a generalized concept of diagnosis of the signs of multiple sclerosis, which should determine the parameters of the distortion of the idealized model of the body system by the real nature of the disease and the state of the object. The work presents an analytical model for determining the onset of the disease using the TONTOR step model. The proposed method provides the doctor with information, excluding the subjective factor, while the results of such information technology significantly increase the accuracy of determining the early stage of the disease. Purpose of work consists in modeling the diagnostic signs of appearance of multiple sclerosis at an early stage of development, and appearance of moment of action's onset of this pathology by analysis methods. With this method of modeling, we have the opportunity to use affine and conformal transformations, which were considered earlier. In this case, the chord should be perceived as a directional vector with location accuracy. A circle is a consequence of an affine transformation. Thus, we have the opportunity to set the coordinates of the points of the trajectory and the circle in an unambiguous correspondence. In addition, since the real motion along the trajectory is characterized by oscillatory processes, the affine transformation of the model can be imagined as an exponential curve. The proposed physical and mathematical information processing models will help determine the main points of creating the principles of operation of technical integrated diagnostic tools. The basis is a vector model for determining the state of biological objects, which will allow information signals to be determined with help of integrated TONTOR sensors and TONTOR step model. As a result, the study of the nature of this functional dependence will provide analytical dependences in digital form, will allow the creation of a computer-integrated hardware solution that will eliminate subjectivity in diagnostics according to the "bad - good" principle.