ArticleSensors (Basel, Switzerland)2021
Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Estimation of Respiratory Volumes During Tidal Breathing Using Two Depth Cameras.Sensors (Basel, Switzerland) · 2026Article
- DeepRespNet: a hybrid attention-recurrent framework for non-contact respiratory rate estimation.Frontiers in physiology · 2026Article
- A hybrid CNN-spectral architecture for non-contact respiratory rate estimation using multi-region optical-flow analysis.PloS one · 2026Article
- Adaptive Thermal Imaging Signal Analysis for Real-Time Non-Invasive Respiratory Rate Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Benefit of long-wave infrared camera in the measurement of respiratory rate: A pilot study.The Journal of international medical research · 2025Article
- Fundamental limits of light-wave sensing for non-contact respiration monitoring.Biomedical optics express · 2024Article
- Towards the Instrumentation of Facemasks Used as Personal Protective Equipment for Unobtrusive Breathing Monitoring of Workers.Sensors (Basel, Switzerland) · 2024Article
- Remote Heart Rate Estimation Based on Transformer with Multi-Skip Connection Decoder: Method and Evaluation in the Wild.Sensors (Basel, Switzerland) · 2024Article
- Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks.Sensors (Basel, Switzerland) · 2023Article
- Respiratory Rate Estimation during Walking and Running Using Breathing Sounds Recorded with a Microphone.Biosensors · 2023Article
- Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise.Biosensors · 2023Article
- Breathing-Associated Facial Region Segmentation for Thermal Camera-Based Indirect Breathing Monitoring.IEEE journal of translational engineering in health and medicine · 2023Article
- Breathing Pattern Monitoring by Using Remote Sensors.Sensors (Basel, Switzerland) · 2022Article
- Electrodeless Heart and Respiratory Rate Estimation during Sleep Using a Single Fabric Band and Event-Based Edge Processing.Sensors (Basel, Switzerland) · 2022Article
- Multi-ROI Spectral Approach for the Continuous Remote Cardio-Respiratory Monitoring from Mobile Device Built-In Cameras.Sensors (Basel, Switzerland) · 2022Article
- Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview.Frontiers in physiology · 2022Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate (fR) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of fR value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the fR range 6 to 60 breaths/min (bpm), the FO allows measuring fR values with bias of -0.03 ± 1.38 bpm and -0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively.
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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.