Inventory reference ISSN 1812-7231 Klin.inform.telemed. Volume 13, Issue 14, 2018, Pages 37–46
Author(s) O. Yu. Mayorov 1, 2, 4, V. N. Fenchenko 1, 2, 3
1Kharkiv Medical Academy of Postgraduate Education, Ministry of Healthcare of Ukraine, 2Institute for Medical Informatics and Telemedicine LTD(Kharkiv), 3Physico-Technical Institute of Low Temperatures NAS of Ukraine named after B. I. Verkin (Kharkiv), 4Institute of Children and Adolescents Health protection NAMS of Ukraine (Kharkiv)
Article title Method of detection of schizophrenic row disorders at early stages in patients from groups with "functional psychoses" basing on EEG scaling indicators
Introduction. The use of various hardware methods — PET, fMRI, qEEG has deepened the understanding of the schizophrenic state, however, still, no valid "neuromarkers" of schizophrenia were identified that reliably distinguished schizophrenia patients from groups of patients with other "functional psychoses". There are no standard criteria for diagnosing schizophrenia based on EEG. Significant differences in the EEG of patients with schizophrenia and healthy individuals are detected only when comparing the averaged data for large groups of patients and healthy ones. In this paper, it was proposed to use reliable mathematical indicators to compare individual EEG parameters with reference groups for classifying patients (identifying schizophrenia and other "functional" psychosis).
Methods. Three reference groups of male subjects, 20–26 years old, were studied: healthy (35), patients with depression (34), untreated schizophrenic patients (28), whose diagnosis was clinically confirmed. Studies were conducted in a state of calm wakefulness and during mental load (counting in the mind). EEG was recorded monopolarly on a 24-channels electroencephalograph ("DX-systems", Ukraine) with an averaged reference electrode, with an arrangement of electrodes in the 10–20 system, with a discretisation frequency of 400 Hz. Frontal (F3, F4), parietal (P3, P4), and temporal (T3, T4) leads were studied.
Results. A study of scaling EEG indicators was performed. Multifractal Detrended Fluctuation Analysis (МDFA) was used. Its application is most effective given the heterogeneity and nonstationarity of the signal and has a number of features due to the complex structure and specific nature of the EEG. A new method for the early diagnosis of mental disorders of the schizophrenic series according to scaling EEG indicators registered in the state of rest and mental load with subsequent patient classification has been proposed.
Keywords EEG, Scaling EEG indicators, "Neuromarkers", Schizophrenia, Depression.
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