Abstract
A mathematical model and an algorithm for the statistical estimation of the frequencies of the main rhythms of human electroencephalograms (EEGs) are developed. Detailed description is presented by the example of three rhythms. A code for the computer-aided processing of EEGs, which implements this algorithm, is written. Using the statistical processing of the reliable experimental EEG sample, two criteria, which use processing of the O2-A2 signal of the patient’s EEG for making the decision about the level of health of the patient’s central nervous system (CNS), namely, to decide that the level of health of the patient’s CNS is normal or the patient suffers from the Parkinson’s disease, are formulated. After obtaining an additional information on the sample, it is possible to determine the probabilities of type one and type two errors in accepting the statistical hypotheses.
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Additional information
Original Russian Text © F.N. Grigor’ev, N.A. Kuznetsov, 2010, published in Informatsionnye Protsessy, 2010, Vol. 10, No. 4, pp. 325–333.
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Grigor’ev, F.N., Kuznetsov, N.A. Algorithms of estimation of the main rhythms of the electroencephalograms used for the diagnosing of the functioning of the human central nervous system and the initial ambulatory screening. J. Commun. Technol. Electron. 56, 1522–1526 (2011). https://doi.org/10.1134/S1064226911120047
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DOI: https://doi.org/10.1134/S1064226911120047