ArticleScientific reports2025
Continuous non-contact vital sign monitoring of neonates in intensive care units using RGB-D cameras.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review.World journal of clinical pediatrics · 2026Article
- A multimodal vision dataset for nursing action recognition and quality assessment in NICU.Scientific data · 2026Article
- Neonatal pose estimation in the unaltered clinical environment with fusion of RGB, depth and IR images.NPJ digital medicine · 2025Article
- Real-Time Current Volume Estimation System from an Azure Kinect Camera in Pediatric Intensive Care: Technical Development.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neonates in intensive care require continuous monitoring. Current measurement devices are limited for long-term use due to the fragility of newborn skin and the interference of wires with medical care and parental interactions. Camera-based vital sign monitoring has the potential to address these limitations and has become of considerable interest in recent years due to the absence of physical contact between the recording equipment and the neonates, as well as the introduction of low-cost devices. We present a novel system to capture vital signs while offering clinical insights beyond current technologies using a single RGB-D camera. Heart rate and oxygen saturation were measured using colour and infrared signals with mean absolute errors (MAE) of 7.69 bpm and [Formula: see text], respectively. Using the depth signals, an MAE of 4.83 breaths per minute was achieved for respiratory rate. Tidal volume measurements were obtained with a MAE of 0.61 mL. Flow-volume loops can also be calculated from camera data, which have applications in respiratory disease diagnosis. Our system demonstrates promising capabilities for neonatal monitoring, augmenting current clinical recording techniques to potentially improve outcomes for neonates.
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Registered trials
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