Introduction: The study is devoted to the development of new analytical procedures that would be fit for further study of the cerebral bioelectric activity (EEG) and may become reliable tools for diagnosing schizophrenia by using EEG. Objective of the study: The study was aimed at detecting new “neuromarkers” suitable for diagnosing schizophrenia by using EEG. Materials and methods: The subjects of the study were healthy individuals and patients with schizophrenia, both groups having been examined while either in the state of the undisturbed wakefulness or under mental exertion (backward counting in memory). Fractal characteristics of EEG traces has been determined by applying the Multifractal Detrended Fluctuation Analysis (MDFA). Results: The dimensionality values of the dominant monofractal (the localization of the multifractal spectral function maxima) in patients with schizophrenia while in the state of undisturbed wakefulness could be increased in comparison with the healthy subjects. Have introduced a “decision-making rule” that allows to rate the status of tested subjects with special reference to the risk factors (suspected signs of schizophrenia) by employing the sets of data obtained by applying the procedures of multifractal analysis towards the EEG traces. A diagnostic method allowing the detection of EEG signals pathologically deviating from normal ranges of values based on the use of multifractal characteristics has been suggested.

B Verkin Institute for Low Temperature Physics and Engineering of the National Academy of Sciences Kharkiv Ukraine

Institute for Medical Informatics and Telemedicine Kharkіv Ukraine

Kharkiv Medical Academy of Postgraduate Education of the Ministry of Health Ukraine

Research Institute for Children and Adolescents Health Protection of the National Academy of Medical Sciences Kharkiv Ukraine

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