Identification of the Oculo-Motor System in the Form Volterra Model Based on Eye-Tracking Data

Pavlenko, Vitaliy; Shamanina, Tetiana; Chori, Vladislav

doi:10.1051/epjconf/202124801009

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Аналіз достовірності класифікації психофізіологічних станів в просторі запропонованих ознак полягає у формуванні всіх можливих комбінацій ознак та оцінці їх інформативності на основі результатів класифікації досліджуваної вибірки даних з використанням критерію імовірності правильного розпізнавання (ІПР) [27,28]. Таким чином, методом повного перебору були досліджені всі можливі пари ознак.…”

Section: а бunclassified

Using quadratic Volterra model of the oculo-motor system in diagnostic research of psychophysiological state of human

Pavlenko,

Shamanina,

Chori

2023

ИИМ

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It contains the results of the study of the effectiveness of the application of approximation Volterra models of the first and second order of the oculo-motor system in diagnostic studies of the psychophysiological state of a person based on eye-tracking data. Visual stimuli are used as test signals, which are displayed on the monitor screen at different distances from the initial position, which formally corresponds to the action of step signals with different amplitudes at the OMS input. Experimental studies of the "input-output" of the OMS were carried out using the Tobii Pro TX300 eyetracker, and the first-order transient functions and the second-order diagonal intersections of the second-order transient functions were determined based on the eye-tracking data. The resulting transient functions are used to form the spaces of diagnostic features. The diagnostic value of all possible combinations of features in pairs according to the indicator of the probability of correct recognition (PCR) was studied. The research results were obtained using Bayesian classifier training in different spaces of the proposed features. A study of the robustness of features according to the PCR indicator was carried out, the combinations of features with the maximum and most stable PCR indicator were selected. Figs.: 13. Tabl.: 5. Refs.: 28 titles.

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Section: а бunclassified

Using quadratic Volterra model of the oculo-motor system in diagnostic research of psychophysiological state of human

Pavlenko,

Shamanina,

Chori

2023

ИИМ

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“…In [24], based on experimental data obtained with the TOBII PRO TX300 eye tracker, a nonparametric OMS model was built in the form of transient functions of the first h1(m) and diagonal sections of the second h2(m,m) and third orders h3(m,m,m) orders. The resulting transition functions are used to construct the space of features that are used to classify two individuals [25].…”

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Building a classifier in the personality recognition system based on eye tracking data

Chori

Shamanina

Pavlenko

2021

ИИМ

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Identification systems that use biometric characteristics to solve the problem of access to information systems are becoming more common. The article proposes a new method of biometric identification of computer systems users, based on the determination of the integral Volterra model of the human oculo-motor system (OMS) according to experimental research "input-output" using innovative eye tracking technology. With the help of the Tobii Pro TX300 eye tracker, the data of OMC responses to test visual stimuli were obtained, displayed as bright dots on the computer screen at different distances from the start position in the "horizontal" direction. Based on the data obtained, the transition functions of the first, second and third orders of the OMS for two people were determined. To construct a personality classifier, the informativeness of the proposed heuristic features, determined on the basis of the transition functions in terms of the probability of correct recognition (PCR), is investigated. Pairs of features are established that are resistant to computational errors and have a high PCR value - in the range 0.92 - 0.97. Fig.: 8. Table: 5. Bibliography: 30 items. Key words: biometric identification, personality recognition, Volterra model, oculo-motor system, eye tracking technology, informativeness of features, classification.

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Nonlinear Dynamic Model of the Oculo-Motor System Human Based on the Volterra Series

Pavlenko,

Shamanina,

Chori

2024

Springer Proceedings in Mathematics &Amp; Statistics

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Identification of the Oculo-Motor System in the Form Volterra Model Based on Eye-Tracking Data

Cited by 3 publications

References 18 publications

Using quadratic Volterra model of the oculo-motor system in diagnostic research of psychophysiological state of human

Using quadratic Volterra model of the oculo-motor system in diagnostic research of psychophysiological state of human

Building a classifier in the personality recognition system based on eye tracking data

Nonlinear Dynamic Model of the Oculo-Motor System Human Based on the Volterra Series

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