Cargando…
ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals
This paper presents an innovative method for multiple lead electrocardiogram (ECG) monitoring based on Compressed Sensing (CS). The proposed method extends to multiple leads signals, a dynamic Compressed Sensing method, that were previously developed on a single lead. The dynamic sensing method make...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587449/ https://www.ncbi.nlm.nih.gov/pubmed/34770310 http://dx.doi.org/10.3390/s21217003 |
_version_ | 1784598145074724864 |
---|---|
author | Daponte, Pasquale De Vito, Luca Iadarola, Grazia Picariello, Francesco |
author_facet | Daponte, Pasquale De Vito, Luca Iadarola, Grazia Picariello, Francesco |
author_sort | Daponte, Pasquale |
collection | PubMed |
description | This paper presents an innovative method for multiple lead electrocardiogram (ECG) monitoring based on Compressed Sensing (CS). The proposed method extends to multiple leads signals, a dynamic Compressed Sensing method, that were previously developed on a single lead. The dynamic sensing method makes use of a sensing matrix in which its elements are dynamically obtained from the signal to be compressed. In this method, for the application to multiple leads, it is proposed to use a single sensing matrix for which its elements are obtained from a combination of multiple leads. The proposed method is evaluated on a wide set of signals and acquired on healthy subjects and on subjects affected by different pathologies, such as myocardial infarction, cardiomyopathy, and bundle branch block. The experimental results demonstrated that the proposed method can be adopted for a Compression Ratio ([Formula: see text]) up to 10, without compromising signal quality. In particular, for [Formula: see text] 10, it exhibits a percentage of root-mean-squared difference average among a wide set of ECG signals lower than 3%. |
format | Online Article Text |
id | pubmed-8587449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85874492021-11-13 ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals Daponte, Pasquale De Vito, Luca Iadarola, Grazia Picariello, Francesco Sensors (Basel) Article This paper presents an innovative method for multiple lead electrocardiogram (ECG) monitoring based on Compressed Sensing (CS). The proposed method extends to multiple leads signals, a dynamic Compressed Sensing method, that were previously developed on a single lead. The dynamic sensing method makes use of a sensing matrix in which its elements are dynamically obtained from the signal to be compressed. In this method, for the application to multiple leads, it is proposed to use a single sensing matrix for which its elements are obtained from a combination of multiple leads. The proposed method is evaluated on a wide set of signals and acquired on healthy subjects and on subjects affected by different pathologies, such as myocardial infarction, cardiomyopathy, and bundle branch block. The experimental results demonstrated that the proposed method can be adopted for a Compression Ratio ([Formula: see text]) up to 10, without compromising signal quality. In particular, for [Formula: see text] 10, it exhibits a percentage of root-mean-squared difference average among a wide set of ECG signals lower than 3%. MDPI 2021-10-22 /pmc/articles/PMC8587449/ /pubmed/34770310 http://dx.doi.org/10.3390/s21217003 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Daponte, Pasquale De Vito, Luca Iadarola, Grazia Picariello, Francesco ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title | ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title_full | ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title_fullStr | ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title_full_unstemmed | ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title_short | ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals |
title_sort | ecg monitoring based on dynamic compressed sensing of multi-lead signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587449/ https://www.ncbi.nlm.nih.gov/pubmed/34770310 http://dx.doi.org/10.3390/s21217003 |
work_keys_str_mv | AT dapontepasquale ecgmonitoringbasedondynamiccompressedsensingofmultileadsignals AT devitoluca ecgmonitoringbasedondynamiccompressedsensingofmultileadsignals AT iadarolagrazia ecgmonitoringbasedondynamiccompressedsensingofmultileadsignals AT picariellofrancesco ecgmonitoringbasedondynamiccompressedsensingofmultileadsignals |