Estimation of the multidimensional dynamical characteristic eye-motor system

A new method of constructing nonparametric dynamic model of the human oculomotor system on the basis of experimental data “input-output” is developed, considering nonlinear and inertial properties of the rectus muscles of the eye. A technology for tracking eye movement is based on the videos. It is possible to determine the dynamic characteristics of the oculomotor system functions as a transition of the first and second order - integral transforms Volterra kernels.

I. Introduction

The innovative technology of Eye tracking which is rapidly being developed nowadays - is the process of determining the point where the eye looks or eye movements relatively to the head [1]–[3]. This high-tech innovation is being developed further and is effectively used in the construction of a mathematical model of a process of tracking eye movement to detect anomalies in data tracking to quantify the motor symptoms of Parkinson's disease [4]–[5]. The use of nonlinear dynamic model of Wiener and Volterra-Laguerre [6] and their identification is based on a random effects test [7], which requires the application of methods of correlation analysis and generation of a large amount of experimental data (long-term experimental studies).