Dynamic digital signal processing algorithm for vital signs extraction in continuous-wave radars

Detalhes bibliográficos
Autor(a) principal: Gouveia, Carolina
Data de Publicação: 2021
Outros Autores: Albuquerque, Daniel, Vieira, José, Pinho, Pedro
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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spelling 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
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instacron_str RCAAP
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