The article reviews algorithms of bispectral analysis of the electroencephalogram (EEG) signal of a patient to determine the level of brain activity during sedative-assisted treatment. The proposed algorithms are based on construction of multiple convolutions of complex amplitudes of the EEG signal, combined into so-called bispectra. Artificial neural networks (ANNs) are used to perform bispectral analysis and form a conclusion on the degree of patient brain activity. The article also shows individual results of functioning of the algorithms on real EEG signals and compares these results with expert judgments of doctors (anesthesiologists and neurophysiologists).
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References
Kelly, Scott J., Monitoring the State of Consciousness during Anesthesia and Sedation [Guide for Doctors on the Use of Bispectral Index (BIS®) Technology].
Rangayyan R.M., Biomedical Signal Analysis: A Case-Study Approach [translated to Russian], FIZMATLIT, Moscow (2010).
Osovskii C., Neural Networks for Information Processing [in Russian], Finansy i Statistika, Moscow (2002).
Kruglov V.V., Borisov V.V, Artificial Neural Networks: Theory and Practice [in Russian], Goryachaya Liniya - Telekom, Moscow (2001).
Methods of Robust, Neuro-Fuzzy and Adaptive Control [in Russian; N.D. Egupov (Ed.); 2nd ed., reprinted], Bauman MSTU Press, Moscow (2002).
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Translated from Meditsinskaya Tekhnika, Vol. 49, No. 6, Nov.-Dec., 2015, pp. 41-44.
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Lavrov, N.G., Bulaev, V.V., Solouhin, E.N. et al. Bispectral Analysis of Electroencephalogram Using Neural Networks to Assess the Depth of Anesthesia. Biomed Eng 49, 380–384 (2016). https://doi.org/10.1007/s10527-016-9571-9
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DOI: https://doi.org/10.1007/s10527-016-9571-9