ArticleJournal of imaging2021
Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks.
Article in Journal of imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- Next generation of non-contact and wireless vital sign monitoring technology in the neonatal intensive care unit: a systematic review.Pediatric research · 2026Pooled it
- Skin Pigmentation Influence on Pulse Oximetry Accuracy: A Systematic Review and Bibliometric Analysis.Sensors (Basel, Switzerland) · 2022Pooled it
- Artificial intelligence and digital technologies transforming neonatal respiratory assessment: a scoping review.Journal of perinatology : official journal of the California Perinatal Association · 2026Review
- Video-based artificial intelligence for automated neonatal respiratory monitoring.European journal of pediatrics · 2026Article
- Exploring reference standards for the measurement of respiratory rate in children under 5 years of age: a scoping review.BMJ paediatrics open · 2026Article
- Automated hypoxia and apnea identification for neonates via enhanced respiratory signal modeling with deep learning.Scientific reports · 2025Article
- Continuous non-contact vital sign monitoring of neonates in intensive care units using RGB-D cameras.Scientific reports · 2025Article
- FMCW-based contactless heart rate monitoring.Scientific reports · 2025Article
- A Review of Patient Bed Sensors for Monitoring of Vital Signs.Sensors (Basel, Switzerland) · 2024Review
- Emerging innovations in neonatal monitoring: a comprehensive review of progress and potential for non-contact technologies.Frontiers in pediatrics · 2024Review
- Contactless assessment of heart rate in neonates within a clinical environment using imaging photoplethysmography.Frontiers in pediatrics · 2024Article
- Challenges and prospects of visual contactless physiological monitoring in clinical study.NPJ digital medicine · 2023Review
- E-Health: A Game Changer in Fetal and Neonatal Cardiology?Journal of clinical medicine · 2023Review
- Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth.Journal of imaging · 2023Article
- Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates.Journal of clinical monitoring and computing · 2023Article
- Sensor Fusion for the Robust Detection of Facial Regions of Neonates Using Neural Networks.Sensors (Basel, Switzerland) · 2023Article
- High-Speed Continuous Wavelet Transform Processor for Vital Signal Measurement Using Frequency-Modulated Continuous Wave Radar.Sensors (Basel, Switzerland) · 2022Article
- A Setup for Camera-Based Detection of Simulated Pathological States Using a Neonatal Phantom.Sensors (Basel, Switzerland) · 2022Article
- Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts.Biomedical engineering online · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 2 countries.
Funding
Abstract
Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.