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Contactless Measurement of Vital Signs Using Thermal and RGB Cameras: A Study of COVID 19-Related Health Monitoring

In this study, a contactless vital signs monitoring system was proposed, which can measure body temperature (BT), heart rate (HR) and respiration rate (RR) for people with and without face masks using a thermal and an RGB camera. The convolution neural network (CNN) based face detector was applied a...

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Detalles Bibliográficos
Autores principales: Yang, Fan, He, Shan, Sadanand, Siddharth, Yusuf, Aroon, Bolic, Miodrag
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777727/
https://www.ncbi.nlm.nih.gov/pubmed/35062589
http://dx.doi.org/10.3390/s22020627
Descripción
Sumario:In this study, a contactless vital signs monitoring system was proposed, which can measure body temperature (BT), heart rate (HR) and respiration rate (RR) for people with and without face masks using a thermal and an RGB camera. The convolution neural network (CNN) based face detector was applied and three regions of interest (ROIs) were located based on facial landmarks for vital sign estimation. Ten healthy subjects from a variety of ethnic backgrounds with skin colors from pale white to darker brown participated in several different experiments. The absolute error (AE) between the estimated HR using the proposed method and the reference HR from all experiments is [Formula: see text] beats/min (mean ± std), and the AE between the estimated RR and the reference RR from all experiments is [Formula: see text] breaths/min (mean ± std) at a distance of 0.6–1.2 m.