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Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications
Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate ([Formula: see text]) over time, even in unconstrained environments. Pro...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347288/ https://www.ncbi.nlm.nih.gov/pubmed/34372363 http://dx.doi.org/10.3390/s21155126 |
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author | Romano, Chiara Schena, Emiliano Silvestri, Sergio Massaroni, Carlo |
author_facet | Romano, Chiara Schena, Emiliano Silvestri, Sergio Massaroni, Carlo |
author_sort | Romano, Chiara |
collection | PubMed |
description | Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate ([Formula: see text]) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of [Formula: see text] value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the [Formula: see text] range 6 to 60 breaths/min (bpm), the FO allows measuring [Formula: see text] values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively. |
format | Online Article Text |
id | pubmed-8347288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83472882021-08-08 Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications Romano, Chiara Schena, Emiliano Silvestri, Sergio Massaroni, Carlo Sensors (Basel) Article Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate ([Formula: see text]) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of [Formula: see text] value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the [Formula: see text] range 6 to 60 breaths/min (bpm), the FO allows measuring [Formula: see text] values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively. MDPI 2021-07-29 /pmc/articles/PMC8347288/ /pubmed/34372363 http://dx.doi.org/10.3390/s21155126 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 Romano, Chiara Schena, Emiliano Silvestri, Sergio Massaroni, Carlo Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title | Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title_full | Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title_fullStr | Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title_full_unstemmed | Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title_short | Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications |
title_sort | non-contact respiratory monitoring using an rgb camera for real-world applications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347288/ https://www.ncbi.nlm.nih.gov/pubmed/34372363 http://dx.doi.org/10.3390/s21155126 |
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