Cargando…

On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications

This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses sign...

Descripción completa

Detalles Bibliográficos
Autores principales: Maalej, Asma, Ben-Romdhane, Manel, Tlili, Mariam, Rivet, François, Dallet, Dominique, Rebai, Chiheb
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255352/
https://www.ncbi.nlm.nih.gov/pubmed/32565605
http://dx.doi.org/10.1016/j.measurement.2020.108031
_version_ 1783539720892973056
author Maalej, Asma
Ben-Romdhane, Manel
Tlili, Mariam
Rivet, François
Dallet, Dominique
Rebai, Chiheb
author_facet Maalej, Asma
Ben-Romdhane, Manel
Tlili, Mariam
Rivet, François
Dallet, Dominique
Rebai, Chiheb
author_sort Maalej, Asma
collection PubMed
description This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses signals compared to conventional ADC but further compression is needed especially for long-time monitoring applications. The orthogonal matching pursuit algorithm is simulated to evaluate ECG compression with 54 orthogonal and biorthogonal wavelets. For LC-ADC amplitude output compression, Biorthogonal3.1 (bior3.1) wavelet achieves optimal performances in terms of compression ratio (CR) while ensuring 2-% percentage root-mean-square difference (PRD). The PRD must be limited to this value to ensure a very good quality signals after decompression. For circuit implementation purposes, bior3.1 wavelet is proposed as a multiplier-free decomposition step and a noncomplex global and hard thresholding process is achieved. The average CR is 63% and PRD varies between 0.1 and 2.1% leading to a very good diagnostic quality.
format Online
Article
Text
id pubmed-7255352
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-72553522020-05-28 On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications Maalej, Asma Ben-Romdhane, Manel Tlili, Mariam Rivet, François Dallet, Dominique Rebai, Chiheb Measurement (Lond) Article This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses signals compared to conventional ADC but further compression is needed especially for long-time monitoring applications. The orthogonal matching pursuit algorithm is simulated to evaluate ECG compression with 54 orthogonal and biorthogonal wavelets. For LC-ADC amplitude output compression, Biorthogonal3.1 (bior3.1) wavelet achieves optimal performances in terms of compression ratio (CR) while ensuring 2-% percentage root-mean-square difference (PRD). The PRD must be limited to this value to ensure a very good quality signals after decompression. For circuit implementation purposes, bior3.1 wavelet is proposed as a multiplier-free decomposition step and a noncomplex global and hard thresholding process is achieved. The average CR is 63% and PRD varies between 0.1 and 2.1% leading to a very good diagnostic quality. Elsevier Ltd. 2020-11 2020-05-27 /pmc/articles/PMC7255352/ /pubmed/32565605 http://dx.doi.org/10.1016/j.measurement.2020.108031 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Maalej, Asma
Ben-Romdhane, Manel
Tlili, Mariam
Rivet, François
Dallet, Dominique
Rebai, Chiheb
On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title_full On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title_fullStr On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title_full_unstemmed On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title_short On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications
title_sort on the wavelet-based compressibility of continuous-time sampled ecg signal for e-health applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255352/
https://www.ncbi.nlm.nih.gov/pubmed/32565605
http://dx.doi.org/10.1016/j.measurement.2020.108031
work_keys_str_mv AT maalejasma onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications
AT benromdhanemanel onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications
AT tlilimariam onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications
AT rivetfrancois onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications
AT dalletdominique onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications
AT rebaichiheb onthewaveletbasedcompressibilityofcontinuoustimesampledecgsignalforehealthapplications