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Open AccessArticle

Estimating Respiratory Rate in Post-Anesthesia Care Unit Patients Using Infrared Thermography: An Observational Study

1
Department of Anesthesiology, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany
2
Philips Chair for Medical Information Technology, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074 Aachen, Germany
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1618; https://doi.org/10.3390/s18051618
Received: 29 March 2018 / Revised: 4 May 2018 / Accepted: 14 May 2018 / Published: 18 May 2018
(This article belongs to the Special Issue Advances in Infrared Imaging: Sensing, Exploitation and Applications)
The post-anesthesia care unit (PACU) is the central hub for recovery after surgery, especially when the surgery is performed under general anesthesia. Aside from clinical aspects, respiratory impairment is one of the major causes of morbidity and affected recovery in the PACU and should therefore be monitored. In previous studies, infrared thermography was applied to assess the breathing rate (BR) of healthy volunteers. Here, the transferability of published methods for postoperative patients in the PACU was examined. Video recordings of 28 patients were acquired using a long-wave infrared camera, and analyzed offline. For validation purposes, BRs derived from body surface electrocardiography were measured simultaneously. In general, a close agreement between the two techniques (r = 0.607, p = 0.002 upon arrival, and r = 0.849, p < 0.001 upon discharge from the PACU) was obtained. In conclusion, the algorithm was demonstrated to be feasible and reliable under these challenging conditions. View Full-Text
Keywords: infrared thermography; breathing rate detection; long-wave infrared infrared thermography; breathing rate detection; long-wave infrared
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Hochhausen, N.; Barbosa Pereira, C.; Leonhardt, S.; Rossaint, R.; Czaplik, M. Estimating Respiratory Rate in Post-Anesthesia Care Unit Patients Using Infrared Thermography: An Observational Study. Sensors 2018, 18, 1618.

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