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Published in: Measurement Techniques 12/2022

05-05-2022 | MEDICAL AND BIOLOGICAL MEASUREMENTS

An Integrated Methodology for Wavelet Filtering of a Pulse Wave Signal

Author: A. A. Fedotov

Published in: Measurement Techniques | Issue 12/2022

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Abstract

The problem of digital filtering of a pulse wave signal relevant in cardiological diagnostics is considered, which is affected by various physiological interferences, such as baseline wander and motion artifacts. A integrated method of wavelet filtering of the pulse wave signal has been developed, which makes it possible to eliminate baseline wander and motion artifacts that distort the shape of the biosignal. The proposed technique is based on multiscale wavelet decomposition of a biosignal in terms of orthogonal Daubechies wavelets. The technique includes sequential procedures for digital processing of the pulse wave: multiscale wavelet transform; modification of the detail coefficients of the wavelet decomposition based on thresholding; reconstruction of the pulse wave signal based on original approximation coefficients and modified detailing coefficients using the inverse wavelet transform. A comparative analysis of the proposed methodology and existing approaches to filtering pulse waves (moving average filtering, median and bandpass filtering) is carried out. To obtain quantitative characteristics of the filtration efficiency assessment, simulation modeling of a pulse wave with noise of various intensity and nature was used. The high quality of pulse wave filtering using the developed technique based on multiscale wavelet transforms can serve as a reliable basis for the development of highly efficient algorithms and hardware and software systems for cardiology diagnostics.
Literature
2.
go back to reference A. A. Fedotov and S. A. Akulov, Measuring Transducers of Biomedical Signals of Clinical Monitoring Systems, Radio i Svyaz, Moscow (2013). A. A. Fedotov and S. A. Akulov, Measuring Transducers of Biomedical Signals of Clinical Monitoring Systems, Radio i Svyaz, Moscow (2013).
3.
go back to reference L. I. Kalakutsky and E. S. Manelis, Apparatus and Methods of Clinical Monitoring, Vysshaya Shkola, Moscow (2004). L. I. Kalakutsky and E. S. Manelis, Apparatus and Methods of Clinical Monitoring, Vysshaya Shkola, Moscow (2004).
4.
go back to reference G. Strang and T. Nguyen, Wavelets and Filters Banks, Wellesley-Cambridge-Press (1996). G. Strang and T. Nguyen, Wavelets and Filters Banks, Wellesley-Cambridge-Press (1996).
8.
go back to reference T. H. Fu, S. H. Liu, and K. T. Tang, “Heart rate extraction from photople- thysmogram waveform using wavelet multiresolution analysis,” J. Med. Biol. Eng., 28, No. 4, 229–232 (2008). T. H. Fu, S. H. Liu, and K. T. Tang, “Heart rate extraction from photople- thysmogram waveform using wavelet multiresolution analysis,” J. Med. Biol. Eng., 28, No. 4, 229–232 (2008).
Metadata
Title
An Integrated Methodology for Wavelet Filtering of a Pulse Wave Signal
Author
A. A. Fedotov
Publication date
05-05-2022
Publisher
Springer US
Published in
Measurement Techniques / Issue 12/2022
Print ISSN: 0543-1972
Electronic ISSN: 1573-8906
DOI
https://doi.org/10.1007/s11018-022-02040-5