Nonlinear Dynamics Identification of the Oculo-Motor System based on Eye Tracking Data-Reference-Cited by-同舟云学术

Nonlinear Dynamics Identification of the Oculo-Motor System based on Eye Tracking Data

Published:2021-07-05 Issue: Volume:15 Page:569-577
ISSN:1998-4464
Container-title:International Journal of Circuits, Systems and Signal Processing
language:en
Short-container-title:

Author:

Pavlenko Vitaliy¹,Shamanina Tetiana¹,Chori Vladislav¹

Affiliation:

1. Odessa National Polytechnic University Shevchenko av. 1, Odessa, 65044 Ukraine

Abstract

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 stimuli and innovative technology eye tracking. For identification the Volterra model is used in the form of multidimensional transient functions of the 1st, 2nd and 3rd orders, taking into account the inertial and nonlinear properties of the OMS. Software tools for processing eye tracking data developed in the Matlab environment are tested on real data from an experimental study of OMS.

Publisher

North Atlantic University Union (NAUN)

Subject

Electrical and Electronic Engineering,Signal Processing

Reference30 articles.

1. Y. Wamain, X. Corveleyn, L. Ott, Y. Coello, “Does the motor system contribute to the perception of changes in objects visual attributes? The neural dynamics of sensory binding by action,” Neuropsychologia, 132, 2019. 107121.doi.org/10.1016/j.neuropsychologia.2019.107121

2. M. Daoudi, M. Coello, P. Desrosiers, L. Ott, “A New Computational Approach to Identify Human Social Intention in Action,” In the 13th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2018, Xi'an, China on May 15-19. (2018).

3. F. Quesque, A. Mignon, Y. Coello, “Cooperative and competitive contexts do not modify the effect of social intention on motor action. Consciousness and Cognition. doi: 10.1016/j.concog,” 2017, 06.011.

4. L. Lanata, Sebastian, F. Di Gruttola, S. Di Modica, E.P. Scilingo and A. Greco1 “Nonlinear Analysis of Eye-Tracking Information for Motor Imagery Assessments. Frontiers in Neuroscience”, 2020, 13:1431. DOI: 10.3389/fnins.2019.01431.

5. N. Gueugneau, L.Crognier, and C. Papaxanthis, “The influence of eye movements on the temporal features of executed and imagined arm movements,” Brain Research, 1187, 2008, pp. 95–102.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Eye-Tracking Technology and its Application in Neuroscience;2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS);2023-09-07

2. EYE-TRACKING TECHNOLOGY IN THE STUDY OF COGNITIVE PROCESSES;Sworld-Us Conference proceedings;2019-10-30