ArticleSensors (Basel, Switzerland)2020
Non-Contact Respiratory Measurement Using a Depth Camera for Elderly People.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Contactless Technologies, Sensors, and Systems for Cardiac and Respiratory Measurement during Sleep: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Estimation of Respiratory Volumes During Tidal Breathing Using Two Depth Cameras.Sensors (Basel, Switzerland) · 2026Article
- Contactless Respiratory Waveform Estimation Using a Depth Camera and AI-Based Body Detection.Sensors (Basel, Switzerland) · 2026Article
- Touchless monitoring of neonatal activity: a multi-center study.Pediatric research · 2026Article
- Real-Time Current Volume Estimation System from an Azure Kinect Camera in Pediatric Intensive Care: Technical Development.Sensors (Basel, Switzerland) · 2025Article
- Three-Dimensional Imaging Sensor-Based Non-Contact Measurement of Neonatal Head Circumference in Incubators.Sensors (Basel, Switzerland) · 2025Article
- Continuous non-contact monitoring of neonatal activity.BMC pediatrics · 2025Article
- Challenges and prospects of visual contactless physiological monitoring in clinical study.NPJ digital medicine · 2023Review
- Depth-Based Measurement of Respiratory Volumes: A Review.Sensors (Basel, Switzerland) · 2022Review
- Automatic Separation of Respiratory Flow from Motion in Thermal Videos for Infant Apnea Detection.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Measuring respiration at home for cardiac patients, a simple method that can detect the patient's natural respiration, is needed. The purpose of this study was to develop an algorithm for estimating the tidal volume (TV) and respiratory rate (RR) from the depth value of the chest and/or abdomen, which were captured using a depth camera. The data of two different breathing patterns (normal and deep) were acquired from both the depth camera and the spirometer. The experiment was performed under two different clothing conditions (undressed and wearing a T-shirt). Thirty-nine elderly volunteers (male = 14) were enrolled in the experiment. The TV estimation algorithm for each condition was determined by regression analysis using the volume data from the spirometer as the objective variable and the depth motion data from the depth camera as the explanatory variable. The RR estimation was calculated from the peak interval. The mean absolute relative errors of the estimated TV for males were 14.0% under undressed conditions and 10.7% under T-shirt-wearing conditions; meanwhile, the relative errors for females were 14.7% and 15.5%, respectively. The estimation error for the RR was zero out of a total of 206 breaths under undressed conditions and two out of a total of 218 breaths under T-shirt-wearing conditions for males. Concerning females, the error was three out of a total of 329 breaths under undressed conditions and five out of a total of 344 breaths under T-shirt-wearing conditions. The developed algorithm for RR estimation was accurate enough, but the estimated occasionally TV had large errors, especially in deep breathing. The cause of such errors in TV estimation is presumed to be a result of the whole-body motion and inadequate setting of the measurement area.
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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.