Identification of the oculo-motor system based on the Volterra model using eye tracking technology

Abstract

Instrumental algorithmic and software tools for constructing a nonparametric dynamic model of the human oculo-motor system (OMS) based on its inertial and nonlinear properties are developed in the paper on the basis of the experimental studies data of «inputoutput» in the form of the Volterra model. Taking into account the specificity of the object investigated, test multistage signals (visual stimulus) were used for identification. Based on the experimental data obtained using the developed computational algorithms and data processing software, a nonparametric dynamic model of OMS in the form of a transition function and transition functions of the 2nd and 3rd orders is constructed. Verification of the constructed model showed its adequacy to the object investigated – a practical coincidence (within the acceptable error) of the object and model feedback for the same test effect.