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Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates
Respiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10175339/ https://www.ncbi.nlm.nih.gov/pubmed/36463541 http://dx.doi.org/10.1007/s10877-022-00945-8 |
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author | Maurya, Lalit Zwiggelaar, Reyer Chawla, Deepak Mahapatra, Prasant |
author_facet | Maurya, Lalit Zwiggelaar, Reyer Chawla, Deepak Mahapatra, Prasant |
author_sort | Maurya, Lalit |
collection | PubMed |
description | Respiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signals due to displacement of electrodes. Thermal imaging has recently gained significance as a non-contact method for RR detection because of its many advantages. However, due to the lack of information in thermal images, the selection and tracking of the region of interest (ROI) in thermal images for neonates are challenging. This paper presents the integration of visible (RGB) and thermal (T) image sequences for the selection and tracking of ROI for breathing rate extraction. The deep-learning based tracking-by-detection approach is employed to detect the ROI in the RGB images, and it is mapped to the thermal images using the RGB-T image registration. The mapped ROI in thermal spectrum sequences gives the respiratory rate. The study was conducted first on healthy adults in different modes, including steady, motion, talking, and variable respiratory order. Subsequently, the method is tested on neonates in a clinical settings. The findings have been validated with a contact-based reference method.The average absolute error between the proposed and belt-based contact method in healthy adults reached 0.1 bpm and for more challenging conditions was approximately 1.5 bpm and 1.8 bpm, respectively. In the case of neonates, the average error is 1.5 bpm, which are promising results. The Bland–Altman analysis showed a good agreement of estimated RR with the reference method RR and this pilot study provided the evidence of using the proposed approach as a contactless method for the respiratory rate detection of neonates in clinical settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10877-022-00945-8. |
format | Online Article Text |
id | pubmed-10175339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-101753392023-05-13 Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates Maurya, Lalit Zwiggelaar, Reyer Chawla, Deepak Mahapatra, Prasant J Clin Monit Comput Original Research Respiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signals due to displacement of electrodes. Thermal imaging has recently gained significance as a non-contact method for RR detection because of its many advantages. However, due to the lack of information in thermal images, the selection and tracking of the region of interest (ROI) in thermal images for neonates are challenging. This paper presents the integration of visible (RGB) and thermal (T) image sequences for the selection and tracking of ROI for breathing rate extraction. The deep-learning based tracking-by-detection approach is employed to detect the ROI in the RGB images, and it is mapped to the thermal images using the RGB-T image registration. The mapped ROI in thermal spectrum sequences gives the respiratory rate. The study was conducted first on healthy adults in different modes, including steady, motion, talking, and variable respiratory order. Subsequently, the method is tested on neonates in a clinical settings. The findings have been validated with a contact-based reference method.The average absolute error between the proposed and belt-based contact method in healthy adults reached 0.1 bpm and for more challenging conditions was approximately 1.5 bpm and 1.8 bpm, respectively. In the case of neonates, the average error is 1.5 bpm, which are promising results. The Bland–Altman analysis showed a good agreement of estimated RR with the reference method RR and this pilot study provided the evidence of using the proposed approach as a contactless method for the respiratory rate detection of neonates in clinical settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10877-022-00945-8. Springer Netherlands 2022-12-04 2023 /pmc/articles/PMC10175339/ /pubmed/36463541 http://dx.doi.org/10.1007/s10877-022-00945-8 Text en © The Author(s) 2022 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 Maurya, Lalit Zwiggelaar, Reyer Chawla, Deepak Mahapatra, Prasant Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title | Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title_full | Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title_fullStr | Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title_full_unstemmed | Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title_short | Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
title_sort | non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10175339/ https://www.ncbi.nlm.nih.gov/pubmed/36463541 http://dx.doi.org/10.1007/s10877-022-00945-8 |
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