Classifier for the functional state of the respiratory system via descriptors determined by using multimodal technology
Filist S.A. Al-kasasbeh R.T. Shatalova O.V. Aikeyeva A.A. Al-Habahbeh O.M. Alshamasin M.S. Alekseevich K.N. Khrisat M. Myasnyankin M.B. Ilyash M.
2023Taylor and Francis Ltd.
Computer Methods in Biomechanics and Biomedical Engineering
2023#26Issue 121400 - 1418 pp.
Currently, intelligent systems built on a multimodal basis are used to study the functional state of living objects. Its essence lies in the fact that a decision is made through several independent information channels with the subsequent aggregation of these decisions. The method of forming descriptors for classifiers of the functional state of the respiratory system includes the study of the spectral range of the respiratory rhythm and the construction of the wavelet plane of the monitoring electrocardiosignal overlapping this range. Then, variations in the breathing rhythm are determined along the corresponding lines of the wavelet plane. Its analysis makes it possible to select slow waves corresponding to the breathing rhythm and systemic waves of the second order. Analysis of the spectral characteristics of these waves makes it possible to form a space of informative features for classifiers of the functional state of the respiratory system. To construct classifiers of the functional state of the respiratory system, hierarchical classifiers were used. As an example, we took a group of patients with pneumonia with a well-defined diagnosis (radiography, X-ray tomography, laboratory data) and a group of volunteers without pulmonary pathology. The diagnostic sensitivity of the obtained classifier was 76% specificity with a diagnostic specificity of 82%, which is comparable to the results of X-ray studies. It is shown that the corresponding lines of the wavelet planes are correlated with the respiratory system and, using their Fourier analysis, descriptors can be obtained for training neural network classifiers of the functional state of the respiratory system.
breathing rhythm , Cardiac rhythm , descriptor , Fourier transform , respiratory system , systemic rhythms , trained classifier , wavelet transform
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Department of Biomedical Engineering, Faculty of Fundamental and Applied Informatics, Southwestern State University, Kursk, Russian Federation
Department of Mechatronics Engineering, School of Engineering, University of Jordan, Amman, Jordan
Department of Radio Engineering, Electronics and Telecommunications, Faculty of Physics and Technology, L.N. Gumilyov Eurasian National University, Nur-Sultan, Kazakhstan
Mechatronics Engineering Department, The University of Jordan, Amman, Jordan
Department of Mechatronics Engineering, Al-Balqa Applied University, Faculty of Engineering Faculty, Amman, Jordan
National Research University of Information Technologies, Mechanics and Optics (ITMO University), Saint-Petersburg, Russian Federation
Department of Biomedical Engineering
Department of Mechatronics Engineering
Department of Radio Engineering
Mechatronics Engineering Department
Department of Mechatronics Engineering
National Research University of Information Technologies
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