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Video-Based Respiratory Rate Estimation for Infants in the NICU
Soodeh Ahani1,2, Nikoo Niknafs2,3, Pascal M Lavoie2,3
1Department of Electrical and Computer EngineeringThe University of British Columbia Vancouver BC V6T 1Z4 Canada.
IEEE Journal of Translational Engineering in Health and Medicine
|November 19, 2024
Summary
This study introduces a new non-contact method for estimating infant respiratory rate (RR) using RGB video. The novel algorithm provides reliable and accurate RR measurements in neonatal intensive care units (NICU).
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Infant Monitoring
Background:
- Non-contact respiratory rate (RR) estimation is crucial for infants due to sensitive skin.
- Existing methods may face challenges in neonatal intensive care units (NICU) due to environmental factors.
Purpose of the Study:
- To develop and validate a novel RGB video-based method for contactless RR estimation in infants.
- To address challenges such as low light, shallow breathing, and infant swaddling.
Main Methods:
- Utilized Eulerian video magnification (EVM) with an adaptive peak prominence threshold.
- Recruited 13 infants, recording 4 hours per case.
- Evaluated performance on randomly selected 1-minute video segments.
Main Results:
- Achieved excellent reliability with an Intraclass Correlation Coefficient (ICC) of 0.91 for manual ROIs and 0.88 for automatic ROIs.
- Bland-Altman analysis demonstrated superior agreement compared to impedance sensors and a previous EVM-based method.
- The algorithm performed well in real-life NICU conditions.
Conclusions:
- The proposed algorithm offers a robust solution for non-contact neonatal respiratory rate monitoring.
- It demonstrates effectiveness even in challenging NICU environments with varying lighting and infant coverings.
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