Abstract
The available presentations and models for outcome of the basic types of rhythmic biosignals are considered. For the choice of informative parameters of the signals under investigation, the typological analysis of these signals, and the differential diagnosis, a complex of algorithms are developed, which are based on the methods of the classified analysis of data and pattern recognition. The development and modeling of these algorithms were performed on the basis of analysis of an extensive experimental material for the study of the rhythmic structure of a pulse signal of the radial artery.
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Teoreticheskie i prikladnye aspekty analiza vremennoi organizatsii biosistem (Theoretical and Applied Aspects of Analysis of the Time Organization of Biosystems), Moscow: Nauka, 1976.
Vasilik, P.V., Features of the Structure of Biological Rhythms of an Organism, in Meditsinskaya i biologicheskaya informatika (Medical and Biological Information Science), Kiev: Naukova Dumka, 1987, pp. 65–67.
Vashchenko, A.M. and Kirguev, P.D., Diagnostika po pul’su. Kratkoe prakticheskoe posobie (Pulse-Based Diagnosis. Short Practical Manual), Rostov-on-Don: Feniks, 2006.
Desova, A.A., Legovich, Yu.S., and Razin, O.S., The Computer System of Diagnosis on the Basis of Analysis of the Rhythmic Structure of a Pulse Signal of the Radial Artery, Meditsin. Tekh., 1999, no. 2, pp. 3–5.
Bauman, E.V. and Dorofeyuk, A.A., Classified Analysis of Data, Proc. Intern. Conf. of Control Problems, Moscow: SINTEG, 1999, vol. 1, pp. 62–77.
Nesterov, V.P., Khirmanov, V.N., Nesterov, S.V., et al., Pulsometric Study of State Functions of the Cardiovascular System, Byul. Eksper. Biolog. Medits., 2001, no. 9, pp. 310–313.
Tzydypov, Ch.Ts., Pul’sovaya diagnostika tibetskoi meditsiny (Pulse Diagnosis of Nature Cures), Novosibirsk: Nauka, 1988.
Baevskii, R.M. and Ivanov, G.G., Variabel’nost’ serdechnogo ritma: teoreticheskie aspekty i vozmozhnosti klinicheskogo primeneniya (Variability of the Cardiac Rhythm: Theoretical Aspects and Possibilities of Clinical Application), Moscow: Meditsina, 2000.
Dorofeyuk, Yu.A., The Complex Algorithm of Automatic Classification and Its Application to Analysis and Decision-Making in Large Control Systems, Proc. Intern. Scientific-Practical Conf. “Theory of Active Systems,” Moscow: Inst. Probl. Upravlen., 2007, pp. 39–42.
Dorofeyuk, A.A., Algorithms of Automatic Classification, Avtom. Telemekh., 1971, no. 12, pp. 78–113.
Dorofeyuk, A.A., Algorithms of Machine Learning for Pattern Recognition without the Teacher, which are Based on the Method of Potential Functions, Avtom. Telemekh., 1966, no. 10, pp. 78–87.
Aizerman, M.A., Braverman, E.M., and Rozonoer, L.I., Metod potentsial’nykh funktsii v teorii obucheniya mashin (The Method of Potential Functions in the Theory of Machine Learning), Moscow: Nauka, 1970.
Braverman, E.M. and Muchnik, I.B., Strukturnye metody obrabotki empiricheskikh dannykh (Structural Methods of Empirical Data Processing), Moscow: Nauka, 1983.
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Original Russian Text © A.A. Desova, A.A. Dorofeyuk, V.V. Guchuk, Yu.A. Dorofeyuk, I.V. Pokrovskaya, 2008, published in Avtomatika i Telemekhanika, 2008, No. 6, pp. 143–152.
This work was supported in part by the Russian Foundation for Basic Research, project no. 05-08-50312-a. Recommended for printing by the Program Committee of the 3rd Intern. Confer. on Control Problems (June 20–22, 2006, Moscow).
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Desova, A.A., Dorofeyuk, A.A., Guchuk, V.V. et al. Classified analysis procedures in the problem of formation of informative signs in investigation of the rhythmic structure of a biosignal. Autom Remote Control 69, 1035–1044 (2008). https://doi.org/10.1134/S0005117908060131
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DOI: https://doi.org/10.1134/S0005117908060131