On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals

Bibliographic Details
Main Author: Esgalhado, Filipa
Publication Date: 2022
Other Authors: Vassilenko, Valentina, Batista, Arnaldo, Ortigueira, Manuel
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/148292
Summary: Funding Information: This work was funded by the Fundação para a Ciência e Tecnologia (FCT, Portugal) and NMT, S.A in the scope of the PhD grant PD/BDE/150312/2019 and by FCT within the scope of the CTS Research Unit—Center of Technology and Systems—UNINOVA, under the project UIDB/00066/2020 (FCT). Publisher Copyright: © 2022 by the authors.
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spelling On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signalsdeep learningheart rate variabilityphotoplethysmogramreal-timeSimulinkHuman-Computer InteractionComputer Networks and CommunicationsFunding Information: This work was funded by the Fundação para a Ciência e Tecnologia (FCT, Portugal) and NMT, S.A in the scope of the PhD grant PD/BDE/150312/2019 and by FCT within the scope of the CTS Research Unit—Center of Technology and Systems—UNINOVA, under the project UIDB/00066/2020 (FCT). Publisher Copyright: © 2022 by the authors.Heart Rate Variability (HRV) is a biomarker that can be obtained non-invasively from the electrocardiogram (ECG) or the photoplethysmogram (PPG) fiducial points. However, the accuracy of HRV can be compromised by the presence of artifacts. In the herein presented work, a Simulink® model with a deep learning component was studied for overly noisy PPG signals. A subset with these noisy signals was selected for this study, with the purpose of testing a real-time machine learning based HRV estimation system in substandard artifact-ridden signals. Home-based and wearable HRV systems are prone to dealing with higher contaminated signals, given the less controlled environment where the acquisitions take place, namely daily activity movements. This was the motivation behind this work. The results for overly noisy signals show that the real-time PPG-based HRV estimation system produced RMSE and Pearson correlation coefficient mean and standard deviation of 0.178 ± 0.138 s and 0.401 ± 0.255, respectively. This RMSE value is roughly one order of magnitude above the closest comparative results for which the real-time system was also used.LIBPhys-UNLUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasRUNEsgalhado, FilipaVassilenko, ValentinaBatista, ArnaldoOrtigueira, Manuel2023-01-27T22:20:10Z2022-12-062022-12-06T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article9application/pdfhttp://hdl.handle.net/10362/148292engPURE: 51495392https://doi.org/10.3390/computers11120177info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:08:37Zoai:run.unl.pt:10362/148292Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:39:19.478874Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
title On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
spellingShingle On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
Esgalhado, Filipa
deep learning
heart rate variability
photoplethysmogram
real-time
Simulink
Human-Computer Interaction
Computer Networks and Communications
title_short On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
title_full On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
title_fullStr On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
title_full_unstemmed On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
title_sort On the Feasibility of Real-Time HRV Estimation Using Overly Noisy PPG Signals
author Esgalhado, Filipa
author_facet Esgalhado, Filipa
Vassilenko, Valentina
Batista, Arnaldo
Ortigueira, Manuel
author_role author
author2 Vassilenko, Valentina
Batista, Arnaldo
Ortigueira, Manuel
author2_role author
author
author
dc.contributor.none.fl_str_mv LIBPhys-UNL
UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
CTS - Centro de Tecnologia e Sistemas
RUN
dc.contributor.author.fl_str_mv Esgalhado, Filipa
Vassilenko, Valentina
Batista, Arnaldo
Ortigueira, Manuel
dc.subject.por.fl_str_mv deep learning
heart rate variability
photoplethysmogram
real-time
Simulink
Human-Computer Interaction
Computer Networks and Communications
topic deep learning
heart rate variability
photoplethysmogram
real-time
Simulink
Human-Computer Interaction
Computer Networks and Communications
description Funding Information: This work was funded by the Fundação para a Ciência e Tecnologia (FCT, Portugal) and NMT, S.A in the scope of the PhD grant PD/BDE/150312/2019 and by FCT within the scope of the CTS Research Unit—Center of Technology and Systems—UNINOVA, under the project UIDB/00066/2020 (FCT). Publisher Copyright: © 2022 by the authors.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-06
2022-12-06T00:00:00Z
2023-01-27T22:20:10Z
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/10362/148292
url http://hdl.handle.net/10362/148292
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv PURE: 51495392
https://doi.org/10.3390/computers11120177
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 9
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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