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Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors

Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an...

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Autores principales: Chamaani, Somayyeh, Akbarpour, Alireza, Helbig, Marko, Sachs, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434276/
https://www.ncbi.nlm.nih.gov/pubmed/34502626
http://dx.doi.org/10.3390/s21175735
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author Chamaani, Somayyeh
Akbarpour, Alireza
Helbig, Marko
Sachs, Jürgen
author_facet Chamaani, Somayyeh
Akbarpour, Alireza
Helbig, Marko
Sachs, Jürgen
author_sort Chamaani, Somayyeh
collection PubMed
description Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method.
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spelling pubmed-84342762021-09-12 Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors Chamaani, Somayyeh Akbarpour, Alireza Helbig, Marko Sachs, Jürgen Sensors (Basel) Article Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method. MDPI 2021-08-26 /pmc/articles/PMC8434276/ /pubmed/34502626 http://dx.doi.org/10.3390/s21175735 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
Chamaani, Somayyeh
Akbarpour, Alireza
Helbig, Marko
Sachs, Jürgen
Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title_full Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title_fullStr Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title_full_unstemmed Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title_short Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
title_sort matrix pencil method for vital sign detection from signals acquired by microwave sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434276/
https://www.ncbi.nlm.nih.gov/pubmed/34502626
http://dx.doi.org/10.3390/s21175735
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