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Automatic radar-based 2-D localization exploiting vital signs signatures
In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090773/ https://www.ncbi.nlm.nih.gov/pubmed/35538128 http://dx.doi.org/10.1038/s41598-022-11671-1 |
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author | Mercuri, Marco Russo, Pietro Glassee, Miguel Castro, Ivan Dario De Greef, Eddy Rykunov, Maxim Bauduin, Marc Bourdoux, André Ocket, Ilja Crupi, Felice Torfs, Tom |
author_facet | Mercuri, Marco Russo, Pietro Glassee, Miguel Castro, Ivan Dario De Greef, Eddy Rykunov, Maxim Bauduin, Marc Bourdoux, André Ocket, Ilja Crupi, Felice Torfs, Tom |
author_sort | Mercuri, Marco |
collection | PubMed |
description | In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29[Formula: see text] and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04[Formula: see text] in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment. |
format | Online Article Text |
id | pubmed-9090773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90907732022-05-12 Automatic radar-based 2-D localization exploiting vital signs signatures Mercuri, Marco Russo, Pietro Glassee, Miguel Castro, Ivan Dario De Greef, Eddy Rykunov, Maxim Bauduin, Marc Bourdoux, André Ocket, Ilja Crupi, Felice Torfs, Tom Sci Rep Article In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29[Formula: see text] and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04[Formula: see text] in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment. Nature Publishing Group UK 2022-05-10 /pmc/articles/PMC9090773/ /pubmed/35538128 http://dx.doi.org/10.1038/s41598-022-11671-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Mercuri, Marco Russo, Pietro Glassee, Miguel Castro, Ivan Dario De Greef, Eddy Rykunov, Maxim Bauduin, Marc Bourdoux, André Ocket, Ilja Crupi, Felice Torfs, Tom Automatic radar-based 2-D localization exploiting vital signs signatures |
title | Automatic radar-based 2-D localization exploiting vital signs signatures |
title_full | Automatic radar-based 2-D localization exploiting vital signs signatures |
title_fullStr | Automatic radar-based 2-D localization exploiting vital signs signatures |
title_full_unstemmed | Automatic radar-based 2-D localization exploiting vital signs signatures |
title_short | Automatic radar-based 2-D localization exploiting vital signs signatures |
title_sort | automatic radar-based 2-d localization exploiting vital signs signatures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090773/ https://www.ncbi.nlm.nih.gov/pubmed/35538128 http://dx.doi.org/10.1038/s41598-022-11671-1 |
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