ArticleSensors (Basel, Switzerland)2021
Towards Continuous Camera-Based Respiration Monitoring in Infants.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05175560 (Baby Breathing Monitoring @Home), which is not on this map. Cited by 17 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.
Baby Breathing Monitoring @Home
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Next generation of non-contact and wireless vital sign monitoring technology in the neonatal intensive care unit: a systematic review.Pediatric research · 2026Pooled it
- Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Camera-based respiratory rate monitoring in unmodified neonatal intensive care - a cross-sectional study in a UK hospital.EClinicalMedicine · 2026Article
- Artificial intelligence in sleep diagnostics for children under 2 years of age: state of the evidence and future directions.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Clinical Evaluation of an AI-Based Prototype for Contactless Respiratory Monitoring in Children.Children (Basel, Switzerland) · 2026Article
- Contactless Vital Sign Monitoring: A Review Towards Multi-Modal Multi-Task Approaches.Sensors (Basel, Switzerland) · 2025Review
- A Wireless Neonatal Intensive Care Unit: Fiction or Closer Reality?Neonatology · 2025Article
- Thermal Cameras for Continuous and Contactless Respiration Monitoring.Sensors (Basel, Switzerland) · 2024Review
- Emerging innovations in neonatal monitoring: a comprehensive review of progress and potential for non-contact technologies.Frontiers in pediatrics · 2024Review
- Challenges and prospects of visual contactless physiological monitoring in clinical study.NPJ digital medicine · 2023Review
- Review
- Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates.Journal of clinical monitoring and computing · 2023Article
- Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals.Sensors (Basel, Switzerland) · 2023Article
- Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions.Sensors (Basel, Switzerland) · 2022Review
- Polymeric piezoresistive airflow sensor to monitor respiratory patterns.Journal of the Royal Society, Interface · 2021Article
- Automatic Separation of Respiratory Flow from Motion in Thermal Videos for Infant Apnea Detection.Sensors (Basel, Switzerland) · 2021Article
- Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks.Journal of imaging · 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
7 authors.
Funding
Abstract
Aiming at continuous unobtrusive respiration monitoring, motion robustness is paramount. However, some types of motion can completely hide the respiration information and the detection of these events is required to avoid incorrect rate estimations. Therefore, this work proposes a motion detector optimized to specifically detect severe motion of infants combined with a respiration rate detection strategy based on automatic pixels selection, which proved to be robust to motion of the infants involving head and limbs. A dataset including both thermal and RGB (Red Green Blue) videos was used amounting to a total of 43 h acquired on 17 infants. The method was successfully applied to both RGB and thermal videos and compared to the chest impedance signal. The Mean Absolute Error (MAE) in segments where some motion is present was 1.16 and 1.97 breaths/min higher than the MAE in the ideal moments where the infants were still for testing and validation set, respectively. Overall, the average MAE on the testing and validation set are 3.31 breaths/min and 5.36 breaths/min, using 64.00% and 69.65% of the included video segments (segments containing events such as interventions were excluded based on a manual annotation), respectively. Moreover, we highlight challenges that need to be overcome for continuous camera-based respiration monitoring. The method can be applied to different camera modalities, does not require skin visibility, and is robust to some motion of the infants.
Indexed as
Identifiers
What OpenQuestion holds
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.