Feasibility of Camera-Based Continuous Bilirubin Level Monitoring for Neonates

This study explores the feasibility of using an RGB camera to estimate the bilirubin level of neonates with an emphasis on applications within the Neonatal Intensive Care Unit (NICU), aiming to provide a non-contact, real-time, and continuous monitoring solution for neonatal jaundice. We investigated two fundamental models for camera-based bilirubin level monitoring: blood perfusion (AC component) based and skin reflectance (DC component) based. The blood perfusion model used the ratio of AC components in the blue and green channels, while the skin reflectance model employed the ratio of DC components in these two channels. Videos of 68 neonates in the NICU were recorded using an RGB camera and custom-built dual-wavelength light sources (460 nm and 570 nm). Clinical results showed that the blood perfusion based method negatively correlated with bilirubin concentration, contrary to our modeling and expectation, likely due to the interference of concentration in arterial blood. In contrast, the skin reflectance model demonstrated an expected strong negative correlation between DC ratio and bilirubin (i.e., r=-0.652 and p <0.005) and better consistency with the reference of transcutaneous bilirubin meter (agreement limits range = -5.72 mg/dL to 4.06 mg/dL) in intermittent bilirubin level estimation experiments. Additionally, camera-based continuous bilirubin level monitoring of resting neonates shows high potential (MAE = 4.57 mg/dL) in the NICU.

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Publication Details

Journal
IEEE Transactions on Biomedical Engineering
Published
2025-06-09
DOI
https://doi.org/10.1109/tbme.2025.3577783
Citations
1
Primary Topic
Neonatal Health and Biochemistry
Type
article
Field-Weighted Citation Impact
3.49
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article

Feasibility of Camera-Based Continuous Bilirubin Level Monitoring for Neonates

Wenjin Wang, Yonglong Ye, Huaijing Shu, Xiaoyan Song
1 citations
IEEE Transactions on Biomedical Engineering
Neonatal Health and Biochemistry
3.49
article

Feasibility of Camera-Based Continuous Bilirubin Level Monitoring for Neonates

Wenjin Wang, Yonglong Ye, Huaijing Shu, Xiaoyan Song
article en
1 citations

Abstract

This study explores the feasibility of using an RGB camera to estimate the bilirubin level of neonates with an emphasis on applications within the Neonatal Intensive Care Unit (NICU), aiming to provide a non-contact, real-time, and continuous monitoring solution for neonatal jaundice. We investigated two fundamental models for camera-based bilirubin level monitoring: blood perfusion (AC component) based and skin reflectance (DC component) based. The blood perfusion model used the ratio of AC components in the blue and green channels, while the skin reflectance model employed the ratio of DC components in these two channels. Videos of 68 neonates in the NICU were recorded using an RGB camera and custom-built dual-wavelength light sources (460 nm and 570 nm). Clinical results showed that the blood perfusion based method negatively correlated with bilirubin concentration, contrary to our modeling and expectation, likely due to the interference of concentration in arterial blood. In contrast, the skin reflectance model demonstrated an expected strong negative correlation between DC ratio and bilirubin (i.e., r=-0.652 and p <0.005) and better consistency with the reference of transcutaneous bilirubin meter (agreement limits range = -5.72 mg/dL to 4.06 mg/dL) in intermittent bilirubin level estimation experiments. Additionally, camera-based continuous bilirubin level monitoring of resting neonates shows high potential (MAE = 4.57 mg/dL) in the NICU.

IEEE Transactions on Biomedical EngineeringVol. 73(1)
Southern University of Science and Technology (CN), Nanfang Hospital (CN), Southern Medical University (CN)
Zero hunger
Openalex Percentile: Top 9%
Neonatal Health and Biochemistry
3.49
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Feasibility of Camera-Based Continuous Bilirubin Level Monitoring for Neonates — Wenjin Wang, Yonglong Ye, et al. · IEEE Transactions on Biomedical Engineering (2025) | TGRS Research Map | TGRS