Construction of wavelet dictionaries for ECG modeling

Technical details, algorithms, and MATLAB implementation for a method advanced in the paper ``Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals'', are presented. This work aims to be the companion of that publication, in which an adaptive mathematical model for a given...

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Main Authors: Dana Černá, Laura Rebollo-Neira
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:MethodsX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016121001072
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spelling doaj-8cfa5da314304df78c645238c6aa80ed2021-04-04T04:19:30ZengElsevierMethodsX2215-01612021-01-018101314Construction of wavelet dictionaries for ECG modelingDana Černá0Laura Rebollo-Neira1Department of Mathematics and Didactics of Mathematics, Technical University of Liberec, Studentská 2, Liberec, Czech Republic; Corresponding author.Mathematics Department, Aston University, Birmingham B3 7ET, UKTechnical details, algorithms, and MATLAB implementation for a method advanced in the paper ``Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals'', are presented. This work aims to be the companion of that publication, in which an adaptive mathematical model for a given ECG record is proposed. The method comprises the following building blocks. (i) Construction of a suitable redundant set, called 'dictionary', for decomposing an ECG signal as a superposition of elementary components, called 'atoms', selected from that dictionary. (ii) Implementation of the greedy strategy Optimized Orthogonal Matching Pursuit (OOMP) for selecting the atoms intervening in the signal decomposition.This paper gives the details of the algorithms for implementing stage (i), which is not fully elaborated in the previous publication. The proposed dictionaries are constructed from known wavelet families, but translating the prototypes with a shorter step than that corresponding to a wavelet basis. Stage (ii) is readily implementable by the available function OOMP. • The use of the software and the power of the technique is illustrated by reducing the dimensionality of ECG records taken from the MIT-BIH Arrhythmia Database. • The MATLAB software has been made publicly available on a dedicated website. • We provide the explanations, algorithms and software for the construction of scaling functions and wavelet prototypes for 17 different wavelet families. The procedure is designed to allow for straightforward extension of the software by the inclusion of additional options for the wavelet families.http://www.sciencedirect.com/science/article/pii/S2215016121001072Software for Constructing Wavelet Dictionaries with Application to ECG Signal, Modeling
collection DOAJ
language English
format Article
sources DOAJ
author Dana Černá
Laura Rebollo-Neira
spellingShingle Dana Černá
Laura Rebollo-Neira
Construction of wavelet dictionaries for ECG modeling
MethodsX
Software for Constructing Wavelet Dictionaries with Application to ECG Signal, Modeling
author_facet Dana Černá
Laura Rebollo-Neira
author_sort Dana Černá
title Construction of wavelet dictionaries for ECG modeling
title_short Construction of wavelet dictionaries for ECG modeling
title_full Construction of wavelet dictionaries for ECG modeling
title_fullStr Construction of wavelet dictionaries for ECG modeling
title_full_unstemmed Construction of wavelet dictionaries for ECG modeling
title_sort construction of wavelet dictionaries for ecg modeling
publisher Elsevier
series MethodsX
issn 2215-0161
publishDate 2021-01-01
description Technical details, algorithms, and MATLAB implementation for a method advanced in the paper ``Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals'', are presented. This work aims to be the companion of that publication, in which an adaptive mathematical model for a given ECG record is proposed. The method comprises the following building blocks. (i) Construction of a suitable redundant set, called 'dictionary', for decomposing an ECG signal as a superposition of elementary components, called 'atoms', selected from that dictionary. (ii) Implementation of the greedy strategy Optimized Orthogonal Matching Pursuit (OOMP) for selecting the atoms intervening in the signal decomposition.This paper gives the details of the algorithms for implementing stage (i), which is not fully elaborated in the previous publication. The proposed dictionaries are constructed from known wavelet families, but translating the prototypes with a shorter step than that corresponding to a wavelet basis. Stage (ii) is readily implementable by the available function OOMP. • The use of the software and the power of the technique is illustrated by reducing the dimensionality of ECG records taken from the MIT-BIH Arrhythmia Database. • The MATLAB software has been made publicly available on a dedicated website. • We provide the explanations, algorithms and software for the construction of scaling functions and wavelet prototypes for 17 different wavelet families. The procedure is designed to allow for straightforward extension of the software by the inclusion of additional options for the wavelet families.
topic Software for Constructing Wavelet Dictionaries with Application to ECG Signal, Modeling
url http://www.sciencedirect.com/science/article/pii/S2215016121001072
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