A student from St. Petersburg State University of Aerospace Instrumentation has developed an innovative program. It analyzes electroencephalogram signals and identifies signs of insomnia in people. The program helps to objectively assess sleep quality, which is important for selecting the right treatment.
The algorithm and program are developed based on information from the physio.net database. The uniqueness of the project lies in the use of two methods of mathematical processing: spectral and correlational.
With their help, signals are analyzed according to certain characteristics, which makes it possible to identify the likelihood of developing insomnia. Such a program can become a valuable tool for doctors in making decisions. In the process, the program analyzes data obtained using electroencephalography. It records the electrical activity of the brain during sleep.
The key element of the algorithm is the detection of high-amplitude signals in the occipital channels of the EEG. If such signals are present, it means that the person is in a deep sleep phase. The absence of these signals may indicate that the person is not sleeping, but is awake, which may be a sign of insomnia.
This development makes it possible to obtain an objective assessment of sleep quality. Unlike subjective assessments, the proposed method relies on the analysis of physiological indicators. This is especially valuable, since the traditional method of diagnosing sleep disorders — polysomnography — can cause discomfort and distort results due to the large number of sensors.
The program created by the student can become an innovative tool for detecting insomnia, without requiring significant intervention in the body.
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