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Wearable lung sounds, fluid, and body temperature monitoring for patients with COVID-19

适用于 COVID-19 患者的可穿戴式肺音、体液和体温监测

基本信息

批准号：
10163297
负责人：
Omer Tolga Inan
金额：
$ 39.65万
依托单位：
GEORGIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-27 至 2021-07-12
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10163297
关键词：
Accident and Emergency department Acoustics Acute Address Affect Algorithms American Area Auscultation Biological Markers Biomedical Engineering Body Temperature COVID-19 COVID-19 pandemic Cardiopulmonary Cardiovascular system Caring Characteristics Chronic Childhood Arthritis Clinic Clinical Collection Communicable Diseases Community Healthcare Data Analytics Deterioration Development Devices Diagnosis Early identification Electronics Emergency Medical Technicians Emergency Medicine Ensure Equipment Event Future Goals Health Health Personnel Healthcare Healthcare Systems Home environment Hospitals Intensive Care Units Investigation Joints Knee Knee Injuries Liquid substance Lung Machine Learning Measurement Measures Mechanical ventilation Medical center Methods Modality Monitor Movement Output Patient Monitoring Patient Recruitments Patients Persons Physiologic pulse Physiological Procedures Process Reading Regulatory Pathway Reporting Research Respiratory Sounds Respiratory distress Rest Resuscitation Risk Signal Transduction Site Skin Skin Temperature Societies Spectrum Analysis Stethoscopes System Techniques Technology Testing Time Translations Triage Ursidae Family Validation Work Writing base clinical decision-making commercialization cost design digital healthy volunteer improved indexing innovation kinematics miniaturize multimodality new technology novel novel coronavirus pandemic disease prevent prototype respiratory screening sensor sensor technology synergism wearable sensor technology

项目摘要

The COVID-19 pandemic has tremendously impacted society, communities, and the healthcare system across the world, and threatens to continue to challenge society for the coming months and years. More than 1 million Americans have been diagnosed with COVID-19, and more than 60,000 Americans have lost their lives as of the writing of this proposal. The ultimate goal of this research is to create a wearable physiological sensing solution for COVID-19 patient management, including diagnosis, triage, and monitoring of patients based on lung sounds, lung fluid, body temperature, and inertial measures captured with the same device. The central innovation lies in the hardware and algorithms that have been proposed for this purpose, building upon the team’s prior work in other areas of wearable bio-acoustic sensing and bioimpedance spectroscopy. The following two specific aims are proposed for the research: (1) to design, implement, and validate a wearable sensing system for lung sounds, lung fluid, body temperature, and inertial measurements; and (2) to test and evaluate this system to assess efficacy and potential information derived in patients hospitalized with COVID-19 and persons under investigation for COVID-19 longitudinally. Successful completion of this project would result in a validated prototype for sensing multiple parameters of cardiopulmonary health in patients with COVID-19, with imminent feasibility to transition the technology to commercialization and through regulatory pathways. This would provide a much-needed patient management technology for this novel coronavirus to healthcare practitioners and ultimately a means to monitor patients remotely to ensure that any deterioration in health is detected as early as possible.

COVID-19大流行对全球社会、社区及医疗系统造成巨大影响，并有可能在未来数月及数年继续对社会构成挑战。超过100万美国人被诊断出感染COVID-19，截至本提案撰写之时，已有6万多美国人丧生。这项研究的最终目标是为COVID-19患者管理创建一个可穿戴的生理传感解决方案，包括基于同一设备捕获的肺音、肺液、体温和惯性测量值对患者进行诊断、分诊和监测。核心创新在于为此目的提出的硬件和算法，建立在该团队在可穿戴生物声学传感和生物阻抗谱等其他领域的先前工作基础上。该研究提出了以下两个具体目标：（1）设计、实现和验证用于肺音、肺液、体温和惯性测量的可穿戴传感系统;以及（2）测试和评估该系统，以纵向评估COVID-19住院患者和接受COVID-19调查的人员的疗效和潜在信息。该项目的成功完成将产生一个经过验证的原型，用于检测COVID-19患者的心肺健康的多个参数，即将实现将该技术商业化并通过监管途径的可行性。这将为医疗保健从业者提供一种急需的新型冠状病毒患者管理技术，并最终提供一种远程监测患者的手段，以确保尽早发现任何健康恶化。

项目成果

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（1）

An Interpretable Experimental Data Augmentation Method to Improve Knee Health Classification Using Joint Acoustic Emissions.

一种利用关节声发射改善膝关节健康分类的可解释实验数据增强方法。

DOI：
10.1007/s10439-021-02788-x
发表时间：
2021
期刊：
Annals of biomedical engineering
影响因子：
3.8
作者：
Ozmen,GoktugC;Gazi,AsimH;Gharehbaghi,Sevda;Richardson,KristineL;Safaei,Mohsen;Whittingslow,DanielC;Prahalad,Sampath;Hunnicutt,JenniferL;Xerogeanes,JohnW;Snow,TeresaK;Inan,OmerT
通讯作者：
Inan,OmerT

Estimating Knee Joint Load Using Acoustic Emissions During Ambulation.

使用行走过程中的声发射估计膝关节负荷。