Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/14012 |
Resumo: | Radar systems have been widely explored as a monitoring tool able to assess the subject's vital signs remotely. However, their implementation in real application scenarios is not straightforward. Received signals encompass parasitic reflections that occur in the monitoring environment. Generally, those parasitic components, often treated as a complex DC (CDC) offsets, must be removed in order to correctly extract the bio-signals information. Fitting methods can be used, but their implementation were revealed to be challenging when bio-signals are weak or when these parasitic reflections arise from non-static targets, changing the CDC offset properties over time. In this work, we propose a dynamic digital signal processing algorithm to extract the vital signs from radar systems. This algorithm includes a novel arc fitting method to estimate the CDC offsets on the received signal. The method revealed being robust to weaker signals, presenting a success rate of 95%, irrespective of the considered monitoring conditions. Furthermore, the proposed algorithm is able to adapt to slow changes in the propagation environment. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radarsArc fittingBio-radarContinuous-waveDC offsetsDigital signal processing algorithmVital signsRadar systems have been widely explored as a monitoring tool able to assess the subject's vital signs remotely. However, their implementation in real application scenarios is not straightforward. Received signals encompass parasitic reflections that occur in the monitoring environment. Generally, those parasitic components, often treated as a complex DC (CDC) offsets, must be removed in order to correctly extract the bio-signals information. Fitting methods can be used, but their implementation were revealed to be challenging when bio-signals are weak or when these parasitic reflections arise from non-static targets, changing the CDC offset properties over time. In this work, we propose a dynamic digital signal processing algorithm to extract the vital signs from radar systems. This algorithm includes a novel arc fitting method to estimate the CDC offsets on the received signal. The method revealed being robust to weaker signals, presenting a success rate of 95%, irrespective of the considered monitoring conditions. Furthermore, the proposed algorithm is able to adapt to slow changes in the propagation environment.MDPIRCIPLGouveia, CarolinaAlbuquerque, DanielVieira, JoséPinho, Pedro2021-11-18T14:08:54Z2021-10-132021-10-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/14012engGOUVEIA, Carolina; [et al] – Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars. Remote Sensing. eISSN 2072-4292. Vol. 13, N.º 20 (2021), pp. 1-2310.3390/rs132040792072-4292info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T10:09:37ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
title |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
spellingShingle |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars Gouveia, Carolina Arc fitting Bio-radar Continuous-wave DC offsets Digital signal processing algorithm Vital signs |
title_short |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
title_full |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
title_fullStr |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
title_full_unstemmed |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
title_sort |
Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars |
author |
Gouveia, Carolina |
author_facet |
Gouveia, Carolina Albuquerque, Daniel Vieira, José Pinho, Pedro |
author_role |
author |
author2 |
Albuquerque, Daniel Vieira, José Pinho, Pedro |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Gouveia, Carolina Albuquerque, Daniel Vieira, José Pinho, Pedro |
dc.subject.por.fl_str_mv |
Arc fitting Bio-radar Continuous-wave DC offsets Digital signal processing algorithm Vital signs |
topic |
Arc fitting Bio-radar Continuous-wave DC offsets Digital signal processing algorithm Vital signs |
description |
Radar systems have been widely explored as a monitoring tool able to assess the subject's vital signs remotely. However, their implementation in real application scenarios is not straightforward. Received signals encompass parasitic reflections that occur in the monitoring environment. Generally, those parasitic components, often treated as a complex DC (CDC) offsets, must be removed in order to correctly extract the bio-signals information. Fitting methods can be used, but their implementation were revealed to be challenging when bio-signals are weak or when these parasitic reflections arise from non-static targets, changing the CDC offset properties over time. In this work, we propose a dynamic digital signal processing algorithm to extract the vital signs from radar systems. This algorithm includes a novel arc fitting method to estimate the CDC offsets on the received signal. The method revealed being robust to weaker signals, presenting a success rate of 95%, irrespective of the considered monitoring conditions. Furthermore, the proposed algorithm is able to adapt to slow changes in the propagation environment. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-11-18T14:08:54Z 2021-10-13 2021-10-13T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/14012 |
url |
http://hdl.handle.net/10400.21/14012 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
GOUVEIA, Carolina; [et al] – Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars. Remote Sensing. eISSN 2072-4292. Vol. 13, N.º 20 (2021), pp. 1-23 10.3390/rs13204079 2072-4292 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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1777304545880178688 |