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Published in: Journal of Clinical Monitoring and Computing 6/2021

01-12-2021 | Original Research

Non-contact thermography-based respiratory rate monitoring in a post-anesthetic care unit

Authors: Hye-Mee Kwon, Keita Ikeda, Sung-Hoon Kim, Robert H. Thiele

Published in: Journal of Clinical Monitoring and Computing | Issue 6/2021

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Abstract

In patients at high risk of respiratory complications, pulse oximetry may not adequately detect hypoventilation events. Previous studies have proposed using thermography, which relies on infrared imaging, to measure respiratory rate (RR). These systems lack support from real-world feasibility testing for widespread acceptance. This study enrolled 101 spontaneously ventilating patients in a post-anesthesia recovery unit. Patients were placed in a 45° reclined position while undergoing pulse oximetry and bioimpedance-based RR monitoring. A thermography camera was placed approximately 1 m from the patient and pointed at the patient’s face, recording continuously at 30 frames per second for 2 min. Simultaneously, RR was manually recorded. Offline imaging analysis identified the nares as a region of interest and then quantified nasal temperature changes frame by frame to estimate RR. The manually calculated RR was compared with both bioimpedance and thermographic estimates. The Pearson correlation coefficient between direct measurement and bioimpedance was 0.69 (R2 = 0.48), and that between direct measurement and thermography was 0.95 (R2 = 0.90). Limits of agreement analysis revealed a bias of 1.3 and limits of agreement of 10.8 (95% confidence interval 9.07 to 12.5) and − 8.13 (− 6.41 to − 9.84) between direct measurements and bioimpedance, and a bias of −0.139 and limits of agreement of 2.65 (2.14 to 3.15) and − 2.92 (− 2.41 to 3.42) between direct measurements and thermography. Thermography allowed tracking of the manually measured RR in the post-anesthesia recovery unit without requiring patient contact. Additional work is required for image acquisition automation and nostril identification.
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Literature
16.
go back to reference Viola PMJ (2001) Rapid object detection using a boosted cascade of simple features. Paper presented at the Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 8–14 Dec; 2001. Viola PMJ (2001) Rapid object detection using a boosted cascade of simple features. Paper presented at the Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 8–14 Dec; 2001.
Metadata
Title
Non-contact thermography-based respiratory rate monitoring in a post-anesthetic care unit
Authors
Hye-Mee Kwon
Keita Ikeda
Sung-Hoon Kim
Robert H. Thiele
Publication date
01-12-2021
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 6/2021
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-020-00595-8

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