气候变化领域集成服务门户(CCPortal): Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients

CCPortal

DOI	10.1073/pnas.2026610118
	Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients
	Ni X.; Ouyang W.; Jeong H.; Kim J.-T.; Tzaveils A.; Mirzazadeh A.; Wu C.; Lee J.Y.; Keller M.; Mummidisetty C.K.; Patel M.; Shawen N.; Huang J.; Chen H.; Ravi S.; Chang J.-K.; Lee K.H.; Wu Y.; Lie F.; Kang Y.J.; Kim J.U.; Chamorro L.P.; Banks A.R.; Bharat A.; Jayaraman A.; Xu S.; Rogers J.A.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:19
英文摘要	Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Biomarkers; COVID-19; Digital health; Respiratory disease; Wearable electronics
语种	英语
scopus关键词	biological marker; biological marker; adult; aged; Article; automation; biometry; clinical article; clinical feature; cohort analysis; controlled study; convolutional neural network; coronavirus disease 2019; coughing; demography; disease course; disease severity; droplet transmission; female; home care; hospital care; hospital patient; human; laughter; male; methodology; patient monitoring; priority journal; speech; time; vital sign; abnormal respiratory sound; breathing rate; clinical trial; heart rate; pathophysiology; physiologic monitoring; wireless communication; Biomarkers; COVID-19; Heart Rate; Humans; Monitoring, Physiologic; Respiratory Rate; Respiratory Sounds; SARS-CoV-2; Wireless Technology
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238924
作者单位	Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL 60208, United States; Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, United States; Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, United States; Medical Scientist Training Program, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States; College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, United States; Sibel Inc., Niles, IL 60714, United States; Sonica Health, Niles, IL 60714, United States; Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL 60611, United States; College of Medicine, University of Illinois at Chicago, Chicago, IL 60612, United States; Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States; Division of Thoracic Surgery, Feinberg School of Medicine,...
推荐引用方式 GB/T 7714	Ni X.,Ouyang W.,Jeong H.,et al. Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients[J],2021,118(19).
APA	Ni X..,Ouyang W..,Jeong H..,Kim J.-T..,Tzaveils A..,...&Rogers J.A..(2021).Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients.Proceedings of the National Academy of Sciences of the United States of America,118(19).
MLA	Ni X.,et al."Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients".Proceedings of the National Academy of Sciences of the United States of America 118.19(2021).