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PresentationsTools of intelligent information technology for building Volterra model of the oculo-motor apparatusOdessa National Polytechnic University, Ukraine, 65044, Odessa, Avenue Shevchenko, 1. Tel: +3 (0063) 461-74-72, pavlenko_vitalij@mail.ru We are currently developing an innovative technology of Eye tracking – is the process of determining the point to which the directed gaze or movement of the eye relative to the head. This high tech innovation has been further developed and effectively used to construct a mathematical model of the process of continuous monitoring eye movements for the detection of anomalies in tracking data for quantifying motor symptoms of Parkinson's disease [1]. It uses nonlinear dynamic of Wiener and Volterra-Laguerre models and their identification based on the use of test random effects, which requires the use of correlation analysis methods and receive a large amount of experimental data (long-term experimental studies). To build Volterra model of the oculo-motor system (OMS) of the person propose to use deterministic test sygnals, i.e. signals of type step (the most adequate to study the dynamics OMS), which allows to simplify the computational algorithm identification and significantly reduce the time of processing of data experimental. Method is developed and computing algorithms of deterministic identification of nonlinear dynamic systems in the form of Volterra models using multi-step test signals. On the basis of experimental data using the developed tools of information processing is constructed of non-parametric dynamic of Volterra model of the OMS in the form of a 1th and 2th orders transition functions. Verification of the constructed model showed its adequacy to the studied object – the practical coincidence (within acceptable error) of the responses object and model at one and the same test exposure.
Referenses 1. Jansson, D., Medvedev A., Axelson H., Nyholm D. Stochastic anomaly detection in eye-tracking data for quantification of motor symptoms in Parkinson's disease // Advances in Experimental Medicine and Biology, No.823, 2015. P. 63-82. DOI: 10.1007/978-3-319-10984-8_4 2. Pavlenko V.D., Fomin O.O., Fedorova A.N., Dombrovskyi M.M. Identification of Human Eye-Motor System Base on Volterra Model // Herald of the National Technical University «KhPI». Subject issue: Information Science and Modelling, Kharkov, NTU «KhPI», No. 21 (1193), 2016. P. 74 – 85.
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