Objective: Monitoring infants’ breathing activity is crucial in research and clinical applications but remains a challenge. This study aims to develop a contactless method to monitor breathing patterns and thoracoabdominal asynchronies in infants inside the incubator, using depth cameras. Methods: We proposed an algorithm to extract the 3D displacements of the ribcage and abdomen from the analysis of depth images. We evaluated the accuracy of the system in-vitro vs. a reference motion capture analyzer. We also conducted a feasibility study on 12 patients receiving non-invasive respiratory support to estimate the mean and the variability of the chest wall displacements in preterm infants and evaluate the suitability of the proposed system in the clinical setting. Results: In-vitro, the mean (95% CI) error in the measurement of amplitude, frequency and phase shift between compartmental displacements was -0.14 (-0.57, 0.28) mm, 0.02 (-0.99, 1.03) bpm, and -0.40 (-1.76, 0.95)°, respectively. In-vivo, the mean (95% CI) amplitude of the ribcage and abdomen displacements were 0.99 (0.34, 2.67) mm and 1.20 (0.40, 2.15) mm, respectively. Conclusions: The developed system proved accurate in-vitro and was suitable for the clinical environment. Clinical Impact: The proposed method has value for evaluating infants’ breathing patterns in research applications and, after further development, may represent a simple monitoring tool for infants’ respiratory activity inside the incubator.

Contactless Monitoring of Breathing Pattern and Thoracoabdominal Asynchronies in Preterm Infants Using Depth Cameras: A Feasibility Study

Ottaviani V.;Veneroni C.;Dellaca' R.;Zannin E.
2022-01-01

Abstract

Objective: Monitoring infants’ breathing activity is crucial in research and clinical applications but remains a challenge. This study aims to develop a contactless method to monitor breathing patterns and thoracoabdominal asynchronies in infants inside the incubator, using depth cameras. Methods: We proposed an algorithm to extract the 3D displacements of the ribcage and abdomen from the analysis of depth images. We evaluated the accuracy of the system in-vitro vs. a reference motion capture analyzer. We also conducted a feasibility study on 12 patients receiving non-invasive respiratory support to estimate the mean and the variability of the chest wall displacements in preterm infants and evaluate the suitability of the proposed system in the clinical setting. Results: In-vitro, the mean (95% CI) error in the measurement of amplitude, frequency and phase shift between compartmental displacements was -0.14 (-0.57, 0.28) mm, 0.02 (-0.99, 1.03) bpm, and -0.40 (-1.76, 0.95)°, respectively. In-vivo, the mean (95% CI) amplitude of the ribcage and abdomen displacements were 0.99 (0.34, 2.67) mm and 1.20 (0.40, 2.15) mm, respectively. Conclusions: The developed system proved accurate in-vitro and was suitable for the clinical environment. Clinical Impact: The proposed method has value for evaluating infants’ breathing patterns in research applications and, after further development, may represent a simple monitoring tool for infants’ respiratory activity inside the incubator.
2022
Abdomen
breathing pattern
Cameras
depth camera
Monitoring
newborn infants
Pediatrics
Point cloud compression
respiratory movements
RGB-D sensors
Sensors
thoracoabdominal displacements
Three-dimensional displays
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1210624
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