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Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera

PURPOSE: Respiratory rate (RR) is one of the most common vital signs with numerous clinical uses. It is an important indicator of acute illness and a significant change in RR is often an early indication of a potentially serious complication or clinical event such as respiratory tract infection, res...

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Autores principales: Addison, Paul S, Antunes, André, Montgomery, Dean, Smit, Philip, Borg, Ulf R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068187/
https://www.ncbi.nlm.nih.gov/pubmed/37010708
http://dx.doi.org/10.1007/s10877-023-01003-7
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author Addison, Paul S
Antunes, André
Montgomery, Dean
Smit, Philip
Borg, Ulf R.
author_facet Addison, Paul S
Antunes, André
Montgomery, Dean
Smit, Philip
Borg, Ulf R.
author_sort Addison, Paul S
collection PubMed
description PURPOSE: Respiratory rate (RR) is one of the most common vital signs with numerous clinical uses. It is an important indicator of acute illness and a significant change in RR is often an early indication of a potentially serious complication or clinical event such as respiratory tract infection, respiratory failure and cardiac arrest. Early identification of changes in RR allows for prompt intervention, whereas failing to detect a change may result in poor patient outcomes. Here, we report on the performance of a depth-sensing camera system for the continuous non-contact ‘touchless’ monitoring of Respiratory Rate. METHODS: Seven healthy subjects undertook a range of breathing rates from 4 to 40 breaths-per-minute (breaths/min). These were set rates of 4, 5, 6, 8, 10, 15, 20, 25, 30, 35 and 40 breaths/min. In total, 553 separate respiratory rate recordings were captured across a range of conditions including body posture, position within the bed, lighting levels and bed coverings. Depth information was acquired from the scene using an Intel D415 RealSense(TM) camera. This data was processed in real-time to extract depth changes within the subject’s torso region corresponding to respiratory activity. A respiratory rate RR(depth) was calculated using our latest algorithm and output once-per-second from the device and compared to a reference. RESULTS: An overall RMSD accuracy of 0.69 breaths/min with a corresponding bias of -0.034 was achieved across the target RR range of 4–40 breaths/min. Bland-Altman analysis revealed limits of agreement of -1.42 to 1.36 breaths/min. Three separate sub-ranges of low, normal and high rates, corresponding to < 12, 12–20, > 20 breaths/min, were also examined separately and each found to demonstrate RMSD accuracies of less than one breath-per-minute. CONCLUSIONS: We have demonstrated high accuracy in performance for respiratory rate based on a depth camera system. We have shown the ability to perform well at both high and low rates which are clinically important.
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spelling pubmed-100681872023-04-03 Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera Addison, Paul S Antunes, André Montgomery, Dean Smit, Philip Borg, Ulf R. J Clin Monit Comput Original Research PURPOSE: Respiratory rate (RR) is one of the most common vital signs with numerous clinical uses. It is an important indicator of acute illness and a significant change in RR is often an early indication of a potentially serious complication or clinical event such as respiratory tract infection, respiratory failure and cardiac arrest. Early identification of changes in RR allows for prompt intervention, whereas failing to detect a change may result in poor patient outcomes. Here, we report on the performance of a depth-sensing camera system for the continuous non-contact ‘touchless’ monitoring of Respiratory Rate. METHODS: Seven healthy subjects undertook a range of breathing rates from 4 to 40 breaths-per-minute (breaths/min). These were set rates of 4, 5, 6, 8, 10, 15, 20, 25, 30, 35 and 40 breaths/min. In total, 553 separate respiratory rate recordings were captured across a range of conditions including body posture, position within the bed, lighting levels and bed coverings. Depth information was acquired from the scene using an Intel D415 RealSense(TM) camera. This data was processed in real-time to extract depth changes within the subject’s torso region corresponding to respiratory activity. A respiratory rate RR(depth) was calculated using our latest algorithm and output once-per-second from the device and compared to a reference. RESULTS: An overall RMSD accuracy of 0.69 breaths/min with a corresponding bias of -0.034 was achieved across the target RR range of 4–40 breaths/min. Bland-Altman analysis revealed limits of agreement of -1.42 to 1.36 breaths/min. Three separate sub-ranges of low, normal and high rates, corresponding to < 12, 12–20, > 20 breaths/min, were also examined separately and each found to demonstrate RMSD accuracies of less than one breath-per-minute. CONCLUSIONS: We have demonstrated high accuracy in performance for respiratory rate based on a depth camera system. We have shown the ability to perform well at both high and low rates which are clinically important. Springer Netherlands 2023-04-03 2023 /pmc/articles/PMC10068187/ /pubmed/37010708 http://dx.doi.org/10.1007/s10877-023-01003-7 Text en © The Author(s) 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. 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 Original Research
Addison, Paul S
Antunes, André
Montgomery, Dean
Smit, Philip
Borg, Ulf R.
Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title_full Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title_fullStr Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title_full_unstemmed Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title_short Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera
title_sort robust non-contact monitoring of respiratory rate using a depth camera
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068187/
https://www.ncbi.nlm.nih.gov/pubmed/37010708
http://dx.doi.org/10.1007/s10877-023-01003-7
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