(untitled) (Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, 2021)
Mathematical, algorithmic and software have been developed as a part of a computer electroencephalographic system. It is based on a 24 hours processing of an EEG signal in a form of a piecewise random sequence of white noises and an additive mixture of harmonic functions with different frequencies for hidden epilepsy time zones detection. The method of epilepsy detecting is based on a procedure of covariance treatment using covariators with basic harmonic functions of frequencies in the range from f1 to f2 within the sliding window, which moves along a sample of values of the EEG signal lasting 24 hours. Based on the mathematical model and processing method, an algorithm and software have been developed for computer electroencephalographic systems using the MATLAB application package. According to the results of the EEG signal lasting 24 hours experimental data processing, it was found that at the time moments of epilepsy there is covariation average power increasing compared to time moments without epilepsy. Therefore, estimates of covariators EEG signal within 24 hours respond quantitatively to the manifestations of epilepsy. To verify the developed mathematical, algorithmic support and software there was generated a test signal in the form of the harmonic components sum in given time zones, (characteristic of the EEG signal) at the time of epilepsy, and white noise - in time zones without epilepsy. The results of the generated test signal processing confirmed the correctness of the detection of the areas of harmonic components appearance that induce the manifestation of epilepsy.