Article 7318

Title of the article

APPLICATION OF A MODIFIED HILBERT – HUANG TRANSFORM FOR DIGITAL
PROCESSING OF MEDICAL SIGNALS 

Authors

Tychkov Aleksandr Yur'evich, Candidate of engineering sciences, deputy director of scientific research institute of basic and applied research, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: tychkov-a@mail.ru 

Index UDK

004.9 

DOI

10.21685/2072-3059-2018-3-7 

Abstract

Background. Modern development of medical instrumentation leads to the emergence of new directions for the development of personalized medicine. In order to create and develop systems for diagnosing health conditions that allow one to adapt to the individual characteristics and parameters of the patient, it is necessary to introduce new methods and algorithms for diagnosing various biological signaling systems, medical signals of various nature being their carriers. The aim of this paper is to modify a mathematical model of the Hilbert-Huang transform to solve the problems of adaptive digital processing of medical signals.
Materials and methods. To analyze medical signals, we have used the classical mathematical model of the Hubert-Huang transform and its modifications, as well as programming in Matlab, LabVIEW and RStudio.
Results. The paper presents an improved mathematical model of the Hilbert-Huang transform, which differs from the known analogues by introducing additional stages of adaptive ensemble decomposition, and noise adaptive in terms of the sampling rate of the signal.
Conclusions. A new mathematical model of the Hilbert-Huang transform has been developed and investigated for solving problems in digital processing of medical signals of different nature, allowing to reduce the level of frequency mixing of signal amplitude-time components and to increase detection reliability of informatively significant medical parameters for the purposes of functional diagnostics. 

Key words

Hilbert-Huang transform, amplitude-time components, mathematical model, medical signals, level of frequency mixing 

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Дата создания: 19.04.2019 14:04
Дата обновления: 22.04.2019 08:20