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PRINCIPLES OF DEVELOPING A SYSTEM FOR DETERMINING EYE MOVEMENT ACTIVITY BASED ON DATA FROM A MOBILE PORTABLE ELECTROENCEPHALOGRAPH
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Romanyuk Vladimir Ruslanovich
postgraduate student, Junior Researcher at the Laboratory of Integrated Automation Systems
SPYIRAN, line 14, 39, St. Petersburg, Russia.
Research interests: machine learning, human condition detection, neural interfaces.
UDC 004.8
DOI 10.24412/2413-7383-123-133
Language: Russian
Annotation:
Eye movements play an important role in human cognitive processes, making them a subject of interest across a wide range of scientific and applied fields. Traditional eye-tracking methods offer high accuracy but have limitations related to the use of cameras or their equivalents. This paper proposes principles for developing a system to detect eye movement activity based on data from mobile, portable electro- encephalograph (EEG), which allows overcome these limitations. The system design is based on machine learning methods such as Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN). Key aspects of development include signal preprocessing, filtering, data normalization, and feature extraction. The proposed principles lay the foundation for developing eye movement detection systems applicable in natural environments.
Keywords: EEG, eye movement activity, machine learning
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Release: 1(36)'2025
Chapter: METHODS AND SYSTEMS OF INFORMATION PROTECTION, INFORMATION SECURITY
How to quote:
V.R. Romaniuk. PRINCIPLES OF DEVELOPING A SYSTEM FOR DETERMINING EYE MOVEMENT ACTIVITY BASED ON DATA FROM A MOBILE PORTABLE ELECTROENCEPHALOGRAPH // Problems of artificial intelligence. 2025. №1.
