title: Estimation of breathing rate in thermal imaging videos: a pilot study on healthy human subjects.
abstract: Diverse studies have demonstrated the importance of monitoring breathing rate (BR). Commonly, changes in BR are one of the earliest and major markers of serious complications/illness. However, it is frequently neglected due to limitations of clinically established measurement techniques, which require attachment of sensors. The employment of adhesive pads or thoracic belts in preterm infants as well as in traumatized or burned patients is an additional paramount issue. The present paper proposes a new robust approach, based on data fusion, to remotely monitor BR using infrared thermography (IRT). The algorithm considers not only temperature modulation around mouth and nostrils but also the movements of both shoulders. The data of these four sensors/regions of interest need to be further fused to reach improved accuracy. To investigate the performance of our approach, two different experiments (phase A: normal breathing, phase B: simulation of breathing disorders) on twelve healthy volunteers were performed. Thoracic effort (piezoplethysmography) was simultaneously acquired to validate our results. Excellent agreements between BR estimated with IRT and gold standard were achieved. While in phase A a mean correlation of 0.98 and a root-mean-square error (RMSE) of 0.28 bpm was reached, in phase B the mean correlation and the RMSE hovered around 0.95 and 3.45 bpm, respectively. The higher RMSE in phase B results predominantly from delays between IRT and gold standard in BR transitions: eupnea/apnea, apnea/tachypnea etc. Moreover, this study also demonstrates the capability of IRT to capture varied breathing disorders, and consecutively, to assess respiratory function. In summary, IRT might be a promising monitoring alternative to the conventional contact-based techniques regarding its performance and remarkable capabilities.
authors: Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany. pereira@hia.rwth-aachen.de.
authors: Carina
authors: http://orcid.org/0000-0003-1788-4562
authors: C
authors: Barbosa Pereira
authors: Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.
authors: Xinchi
authors: X
authors: Yu
authors: Department of Anesthesiology, University Hospital RWTH Aachen, Aachen, Germany.
authors: Michael
authors: M
authors: Czaplik
authors: Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.|Czech Institute of Informatics, Robotics and Cybernetics (CIIRC), CTU Prague, Prague, Czech Republic.
authors: Vladimir
authors: V
authors: Blazek
authors: Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.
authors: Boudewijn
authors: B
authors: Venema
authors: Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.
authors: Steffen
authors: S
authors: Leonhardt
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D008991:Monitoring, Physiologic / Q000379:methods*; D009068:Movement; D010865:Pilot Projects; D012119:Respiration; D056152:Respiratory Rate; D012815:Signal Processing, Computer-Assisted; D014741:Video Recording
keywords: Breathing disorders; Data fusion; Physiological monitoring; Respiratory rate; Thermal imaging