Intelligent Analysis of Quasiperiodic Bioosignals in Medical Diagnostic Problems (with the Example of a Pulse Signal)

We identify the main stages of intelligent analysis of the pulse signal of the radial artery, used to obtain a set of informative parameters in medical diagnostic problems for various diseases. We show the results of expert and formalized classifications of the parameters of the analyzed signal, inc...

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Veröffentlicht in:Automation and remote control Jg. 79; H. 11; S. 1953 - 1962
Hauptverfasser: Desova, A. A., Guchuk, V. V., Pokrovskaya, I. V., Dorofeyuk, A. A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Moscow Pleiades Publishing 01.11.2018
Springer Nature B.V
Schlagworte:
CAE) and Design
Calculus of Variations and Optimal Control; Optimization
Computer-Aided Engineering (CAD
Control
Control Problems for the Development of Large-Scale Systems
Diagnostic systems
Hypertension
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Parameters
Robotics
Systems Theory
pulse shape
rhythmic structure of the signal
qualitative and quantitative characteristics of the signal
data mining
pulse signal of the radial artery
ISSN:0005-1179, 1608-3032
Online-Zugang:Volltext
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Zusammenfassung:We identify the main stages of intelligent analysis of the pulse signal of the radial artery, used to obtain a set of informative parameters in medical diagnostic problems for various diseases. We show the results of expert and formalized classifications of the parameters of the analyzed signal, including the parameters of the shape of the pulse wave within the main quasiperiod and parameters that determine the rhythmic structure of the signal. We develop a multi-stage scheme for obtaining a set of informative parameters of the pulse signal that allows to take into account their characteristic features. The effectiveness of the developed approaches is demonstrated with the example of the problem of diagnosing early stages of arterial hypertension.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0005-1179
1608-3032
DOI:10.1134/S0005117918110012