ArticleIEEE journal of translational engineering in health and medicine2019
Vision-Based Heart and Respiratory Rate Monitoring During Sleep - A Validation Study for the Population at Risk of Sleep Apnea.
Article in IEEE journal of translational engineering in health and medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Non-Invasive Contactless Tracking of Respiratory Rate and Heart Rate During Sleep.Sensors (Basel, Switzerland) · 2026Article
- Decoding menstrual health across the lifespan: a scoping review of digital health tools in research.medRxiv : the preprint server for health sciences · 2026Article
- Decoding menstrual health across the lifespan: a scoping review of digital health tools in research.npj women's health · 2026Article
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- Wearable Artificial Intelligence for Sleep Disorders: Scoping Review.Journal of medical Internet research · 2025Article
- Overview of Respiratory Sensor Solutions to Support Patient Diagnosis and Monitoring.Sensors (Basel, Switzerland) · 2025Review
- Flexible Chitosan-Based Capacitive Humidity Sensors for Respiratory Monitoring.Sensors (Basel, Switzerland) · 2024Article
- Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement.Frontiers in bioengineering and biotechnology · 2024Review
- Non-Contact Measurement of Cardiopulmonary Activity Using Software Defined Radios.IEEE journal of translational engineering in health and medicine · 2024Article
- A Novel Chest-Based PPG Measurement System.IEEE journal of translational engineering in health and medicine · 2024Article
- Contactless and continuous monitoring of respiratory rate in a hospital ward: a clinical validation study.Frontiers in physiology · 2024Article
- Vision-based detection and quantification of maternal sleeping position in the third trimester of pregnancy in the home setting-Building the dataset and model.PLOS digital health · 2023Article
- Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring.Sensors (Basel, Switzerland) · 2023Article
- Contactless remote monitoring of sleep: evaluating the feasibility of an under-mattress sensor mat in a real-life deployment.Health systems (Basingstoke, England) · 2023Article
- Noncontact Sleep Monitoring With Infrared Video Data to Estimate Sleep Apnea Severity and Distinguish Between Positional and Nonpositional Sleep Apnea: Model Development and Experimental Validation.Journal of medical Internet research · 2021Article
- Towards Accurate, Cost-Effective, Ultra-Low-Power and Non-Invasive Respiration Monitoring: A Reusable Wireless Wearable Sensor for an Off-the-Shelf KN95 Mask.Sensors (Basel, Switzerland) · 2021Article
- Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications.Sensors (Basel, Switzerland) · 2021Article
- Distinguishing Obstructive Versus Central Apneas in Infrared Video of Sleep Using Deep Learning: Validation Study.Journal of medical Internet research · 2020Article
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6 authors.
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Abstract
A reliable, accessible, and non-intrusive method for tracking respiratory and heart rate is important for improving monitoring and detection of sleep apnea. In this study, an algorithm based on motion analysis of infrared video recordings was validated in 50 adults referred for clinical overnight polysomnography (PSG). The algorithm tracks the displacements of selected feature points on each sleeping participant and extracts respiratory rate using principal component analysis and heart rate using independent component analysis. For respiratory rate estimation (mean ± standard deviation), 89.89 % ± 10.95 % of the overnight estimation was accurate within 1 breath per minute compared to the PSG-derived respiratory rate from the respiratory inductive plethysmography signal, with an average root mean square error (RMSE) of 2.10 ± 1.64 breaths per minute. For heart rate estimation, 77.97 % ± 18.91 % of the overnight estimation was within 5 beats per minute of the heart rate derived from the pulse oximetry signal from PSG, with mean RMSE of 7.47 ± 4.79 beats per minute. No significant difference in estimation of RMSE of either signal was found according to differences in body position, sleep stage, or amount of the body covered by blankets. This vision-based method may prove suitable for overnight, non-contact monitoring of respiratory rate. However, at present, heart rate monitoring is less reliable and will require further work to improve accuracy.
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