International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The study of sleep is crucial for understanding various physiological and neurological processes, yet research on different sleep phases often comes with high costs and requires specialized equipment. To address these challenges, we developed a portable and relatively inexpensive oculograph, which enables more accessible sleep studies. A critical technical aspect of using the device is the necessity for mathematical transformations to interpret the signals generated by eye movements, which are often complex and prone to noise. We implemented several mathematical procedures for noise reduction, signal filtering, and the extraction of key signal features. To assess the accuracy of the oculograph, we conducted 10 daytime experiments with predefined protocols involving specific eye movements. The results indicate that the oculograph successfully measures eye movements with high precision, which was further validated through comparison with graphical signal representations. Moreover, we performed tests for nighttime use of the device, and validation of REM sleep signals is planned using a camera to record the subject during sleep. These promising outcomes suggest significant potential for the oculograph to help sleep research by offering a more affordable and mobile solution, suitable for both laboratory and home environments. The mathematical procedures and signal processing techniques presented here are tailored to the needs of psychological and medical sleep studies. Additionally, practical applications of the oculograph for targeted sleep research, including tracking eye movements during various sleep stages, are proposed.

Sleep is not just a rest; it is a necessary part of the functioning of the cognitive system of people. Studying the role of sleep for effective functioning of the immune system, temperature regulation, memory, emotional regulation, learning and many other physiological and psychological processes is gaining more and more relevance. It attracts the attention of many leading researchers from around the world. The study of sleep by electrooculography (using three electrodes – two on the temples and one on the forehead) to track eye movements has a significant advantage over the more commonly used EEG methods due to its lower cost and the ability to quickly and efficiently collect large databases. A software-implemented algorithm for automatic recognition of the REM sleep phase during sleep is presented. This algorithm is a step of a larger project to create a system for external control of the content of dreams during REM sleep by providing scents and sounds, pre-associated with various stimuli and symbols. This system will allow in the future applying an automatic external influence on the sleeper during the REM phase. The development will have applications at research on the induction of selected elements during dreaming. This can help to people with post-traumatic stress disorder and phobias, as well for a more effective learning.