A student at St. Petersburg State University of Aerospace Instrumentation has created an innovative program that allows detecting signs of insomnia based on the analysis of electroencephalogram (EEG) signals
The relevance of the development is due to the growing number of people suffering from sleep disorders caused by stress and negative environmental influences. The program analyzes EEG monitoring data by recording the bioelectric activity of the brain during sleep. The key factor in the algorithm is the identification of high-amplitude components in the occipital EEG channels (P4_O2 and P3_O1). The presence of such flashes is characteristic of the deep sleep phase and indicates that a person is asleep. The absence of these signs indicates a possible state of wakefulness and, as a result, the presence of insomnia.
The high work efficiency is due to the fact that the results obtained in the analysis of the program data coincided with the diagnoses of each entry from the physio database.
The development of SUAI student makes it possible to objectively assess the quality of sleep, which is necessary to select the right therapy. Unlike subjective assessments, the proposed method is based on the analysis of physiological parameters. This is especially important given that polysomnography, the traditional method of diagnosing sleep disorders, can cause discomfort and distort the results due to the large number of sensors. The program developed by the student can become a minimally invasive tool for detecting insomnia.
