Parametric and Nonparametric Analysis of Eye-Tracking Data by Anomaly Detection

Jansson, Daniel; Rosen, Olov; Medvedev, Alexander

doi:10.1109/tcst.2014.2364958

Cited by 16 publications

(4 citation statements)

References 24 publications

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“…Внаслідок бойових дій, стихійних лих, що відбуваються сьогодні, значна кількість людей отримують психологічні травми різного ступеня, які часто призводять до посттравматичного стресового розладу (ПТСР) і потребують постійної психологічної підтримки та допомоги [2]. Оскільки ПТСР є комплексним розладом, який проявляється одночасно на психологічному, біологічному та соціальному рівнях, лікування, залежить від його глибини, включає психотерапію, а іноді й використання психофармакологічних препаратів [3]. Запропонована в [4] модель окуломоторної системи (ОМС) дозволяє визначити наявність синдрому ПТСР, а також отримати кількісну оцінку глибини ПТСР і на основі цих досліджень обрати найбільш ефективну тактику лікування.…”

Section: використання квадратичної моделі вольтерри окуло-моторної си...unclassified

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: використання квадратичної моделі вольтерри окуло-моторної си...unclassified

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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“…The developed software enables support of the following tasks: − The relationship study of mental states and cognitive processes in educational activities, a post-traumatic stress disorder, the diagnosis of the Parkinson's and Alzheimer's disease stage, checking the psychophysiological state of pilots and drivers, the professional suitability, the fatigue syndrome [10][11][12][13][14][15][16].…”

Section: The Scope Of Applicationmentioning

confidence: 99%

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

2021

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Instrumental computing and software tools have been developed for constructing a nonlinear dynamic model of the human oculo-motor system (OMS) based on the data of input-output experiments using test visual stimulus and innovative technology. Volterra model in the form of multidimensional transition functions of the 1st, 2nd and 3rd orders, taking into account the inertial and nonlinear properties of the OMS was used as the identification tool. Eye-tracking data developed in the Matlab environment are tested on real datasets from an experimental study of OMS.

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“…Typically, the anomalous items correspond to some significant information in many diverse research areas, such as biomedical imaging, hyperspectral remote sensing, cybersecurity and industrial applications. Jansson et al [10] applied stochastic anomaly detection methods to analyze eye-tracking data of Parkinson patients. Veracini et al [11] presented an anomaly detection strategy for hyperspectral imagery based on a fully unsupervised Gaussian mixture learning.…”

Section: Anomaly Detectionmentioning

confidence: 99%

A New Anomaly Detection System for School Electricity Consumption Data

Cui

Wang

2017

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Anomaly detection has been widely used in a variety of research and application domains, such as network intrusion detection, insurance/credit card fraud detection, health-care informatics, industrial damage detection, image processing and novel topic detection in text mining. In this paper, we focus on remote facilities management that identifies anomalous events in buildings by detecting anomalies in building electricity consumption data. We investigated five models within electricity consumption data from different schools to detect anomalies in the data. Furthermore, we proposed a hybrid model that combines polynomial regression and Gaussian distribution, which detects anomalies in the data with 0 false negative and an average precision higher than 91%. Based on the proposed model, we developed a data detection and visualization system for a facilities management company to detect and visualize anomalies in school electricity consumption data. The system is tested and evaluated by facilities managers. According to the evaluation, our system has improved the efficiency of facilities managers to identify anomalies in the data.

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Parametric and Nonparametric Analysis of Eye-Tracking Data by Anomaly Detection

Cited by 16 publications

References 24 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

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

A New Anomaly Detection System for School Electricity Consumption Data

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