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The Hemodynamic Parameters Values Prediction on the Non-Invasive Hydrocuff Technology Basis with a Neural Network Applying.

Authors :
Markuleva, Marina
Gerashchenko, Mikhail
Gerashchenko, Sergey
Khizbullin, Robert
Ivshin, Igor
Source :
Sensors (14248220). Jun2022, Vol. 22 Issue 11, p4229-4229. 13p.
Publication Year :
2022

Abstract

The task to develop a mechanism for predicting the hemodynamic parameters values based on non-invasive hydrocuff technology of a pulse wave signal fixation is described in this study. The advantages and disadvantages of existing methods of recording the ripple curve are noted in the published materials. This study proposes a new hydrocuff method for hemodynamic parameters and blood pressure values measuring. A block diagram of the device being developed is presented. Algorithms for processing the pulse wave contour are presented. A neural network applying necessity for the multiparametric feature space formation is substantiated. The pulse wave contours obtained using hydrocuff technology of oscillation formation for various age groups are presented. According to preliminary estimates, by the moment of the dicrotic surge formation, it is possible to judge the ratio of the heart and blood vessels work, which makes it possible to form an expanded feature space of significant parameters based on neural network classifiers. This study presents the characteristics accounted for creating a database for training a neural network. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
22
Issue :
11
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
157368813
Full Text :
https://doi.org/10.3390/s22114229