Construction of wavelet dictionaries for ECG modeling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F21%3A00009609" target="_blank" >RIV/46747885:24510/21:00009609 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2215016121001072?via=ihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2215016121001072?via=ihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.mex.2021.101314" target="_blank" >10.1016/j.mex.2021.101314</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Construction of wavelet dictionaries for ECG modeling

Popis výsledku v původním jazyce

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 two building blocks. The first one is a 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. The second step is an 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 are illustrated by reducing the dimensionality of ECG records taken from the MIT-BIH Arrhythmia Database.

Název v anglickém jazyce

Construction of wavelet dictionaries for ECG modeling

Popis výsledku anglicky

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 two building blocks. The first one is a 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. The second step is an 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 are illustrated by reducing the dimensionality of ECG records taken from the MIT-BIH Arrhythmia Database.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20602 - Medical laboratory technology (including laboratory samples analysis; diagnostic technologies) (Biomaterials to be 2.9 [physical characteristics of living material as related to medical implants, devices, sensors])

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MethodsX

ISSN

2215-0161

e-ISSN

—

Svazek periodika

2021

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

20

Strana od-do

—

Kód UT WoS článku

000707181600015

EID výsledku v databázi Scopus

2-s2.0-85103632882