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Experimental Psychology (Russia)
2021. Vol. 14, no. 1, 204–222
https://doi.org/10.17759/exppsy.2021140110
ISSN: 2072-7593 / 2311-7036 (online)

Assessing the Aircraft Crew Activity Basing on Video Oculography Data

 
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Abstract

Mathematical models and methods for crew training level assessing based on video oculography data are presented. The results obtained are based on comparing the studied fragments of oculomotor activity of pilots with comparable patterns of video oculography data of various types and performance quality contained in a pre-formed specialized database. To obtain estimates, a complex combination of random process analysis and multivariate statistical analysis is used. The “intelligence” of diagnostic tools is contained in empirical data and can flexibly change as they accumulate. The considered example of determining the flight mode and pilot qualification based on video oculography data allows us to talk about the possibility of significant discrimination of the gaze movement trajectories of pilots at different flight phases and significant discrimination of the gaze movement trajectories of experienced and inexperienced pilots at certain phases of flight. An important new component of the presented results is a discriminant analysis for solving the problem of flight exercises classification, based on the principles of quantum computing. The scope of the considered approach is not limited to aviation applications and can be extended to tasks that are similar in content.

General Information

Keywords: crew training level assessing, video oculography, Discriminant Analysis, Multidimensional Scaling, Cluster Analysis, oculomotor activity indexes.

Journal rubric: Psychology of Labor and Engineering Psychology

OpenAlex citations: 5

OpenAlex topics: Technology and Human Factors in Education and Health, Advanced Control and Stabilization in Aerospace Systems, Cognitive Science and Mapping

Information about the work in OpenAlex

Number of citations: 5

Topics

Technology and Human Factors in Education and Health

This cluster of papers explores the future of personalized medicine in healthcare, focusing on topics such as artificial intelligence, healthcare technology, medical innovation, ergonomics, biomedical signal analysis, digital health, cyber-physical systems, healthcare automation, and clinical decision support. The papers cover a wide range of interdisciplinary research related to advancing personalized medical treatments and technologies.

Number of works: 27101  |  Total number of citations: 82403

Topic detailsв OpenAlex

Advanced Control and Stabilization in Aerospace Systems

This cluster of papers focuses on the concepts, principles, and applications of inertially stabilized platform technology. It covers topics such as control systems for stabilization, gimbal systems, line-of-sight stabilization, disturbance rejection, MEMS sensors, robust control, navigation aids, UAV operation, and signal processing in the context of airborne imaging and remote sensing systems.

Number of works: 8399  |  Total number of citations: 23472

Topic detailsв OpenAlex

Cognitive Science and Mapping

This cluster of papers focuses on the application of Fuzzy Cognitive Maps (FCMs) in modeling complex systems, decision support, and knowledge representation. It explores various learning algorithms for FCMs, their use in scenario development for social-ecological systems, prediction in healthcare decision making, and their role in multi-criteria analysis.

Number of works: 38697  |  Total number of citations: 753469

Topic detailsв OpenAlex

Work details in OpenAlex

DOI: https://doi.org/10.17759/exppsy.2021140110

Funding. This work was performed as part of the “SAFEMODE” project (grant # 814961) with the financial support of the Ministry of Science and Higher Education of the Russian Federation (UID RFMEFI62819X0014 project)

Published

For citation: Kuravsky, L.S., Yuryev, G.A., Zlatomrezhev, V.I., Greshnikov, I.I., Polyakov, B.Y. (2021). Assessing the Aircraft Crew Activity Basing on Video Oculography Data. Experimental Psychology (Russia), 14(1), 204–222. https://doi.org/10.17759/exppsy.2021140110

© Kuravsky L.S., Yuryev G.A., Zlatomrezhev V.I., Greshnikov I.I., Polyakov B.Y., 2021

License: CC BY-NC 4.0

References

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Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, Dean of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-3375-8446, e-mail: l.s.kuravsky@gmail.com

Grigory A. Yuryev, Candidate of Science (Physics and Matematics), Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

Valentin I. Zlatomrezhev, Head of Laboratory, State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0003-1776-6881, e-mail: vizlatomr@2100.gosniias.ru

Ivan I. Greshnikov, Candidate of Science (Engineering), Head of laboratory, State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-5474-3094, e-mail: vvanes@mail.ru

Borislav Y. Polyakov, Junior Researcher, Research Assistant, Laboratory of Mathematical Psychology and Applied Software of the Center for Information Technologies for Psychological Research, Moscow State University of Psychology and Education, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-6457-9520, e-mail: deslion@yandex.ru

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