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Development of a Method for Identifying the Functional State of a Person When Solving Cognitive Tasks According to the Data of the Brain Microwave Radiation

The article described a technique for conducting experimental studies using passive non-invasive thermography in radio bands to study the effect of changes in the psychophysiological state on a person's radio-brightness temperature. The registration of the radio-brightness temperature signals was carried by contact microwave radiometer, which ensures the reception of brain microwave radiation in the frequency range (3.4-4.2) GHz. A data processing algorithm for detecting stable characteristics of patterns in changes in brightness temperature fluctuations, based on continuous wavelet transform, was proposed. A total of 18 parameters were used to estimate the brightness temperature fluctuations. In this study, two machine learning methods were tested that allow the selection of the most significant features: logistic regression using L1regularization and the decision tree method. The accuracy of determining the functional state on the training data reached 90%. It was shown that the parameter of microwave radiation fluctuations – the median value of the amplitude of fluctuations with fluctuation periods from 40 to 80 s, makes it possible to divide the initial data sample into two subgroups in which the response to cognitive load is significantly different.